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Development and application of an innovative-methodologicalapproach to the design of frameworks for targeted SchoolDental Service programmes; using empirical predictive dataAlsharif, A. T. Y. (2016). Development and application of an innovative-methodological approach to thedesign of frameworks for targeted School Dental Service programmes; using empirical predictive data
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Download date: 21. May. 2018
I
Development and application of an innovative-
methodological approach to the design of frameworks for
targeted School Dental Service programmes; using empirical
predictive data
Alla T. Alsharif
BDS (KSA), MDPH (AUS), MRACDS
This thesis is presented for the degree of
Doctor of Philosophy
of The University of Western Australia
School of Anatomy, Physiology and Human Biology
2016
II
DEDICATION
To my parents, Talal Alsharif and Adlyah Aqeel. Without their prayers and continual
support, this thesis would not be what it is today.
To my shining armor, amazing & loving husband, Dr. Khalid, whose sacrificial care for
me and our children made it possible for me to complete this work.
To my children, AlWaleed, Reem and Noor, who are indeed a treasure from God. For
their eternal love and understanding.
To my brothers and sisters, for being there for me throughout the entire process.
‘Science, like art, is not a copy of nature but a re-creation of her’.~ Jacob Bronowski
III
ABSTRACT
BACKGROUND AND AIM: This thesis sought to analyse a decade of dental admission
patterns in Western Australian children under the age of 15 years, examining
associations with socio-demographic characteristics, insurance coverage, economic cost
and future projected admission rates. This thesis has also developed and tested a model
system of service prioritisation, based on risk, using identified risk indicators, and state-
of-the-art geographic tools.
MATERIAL AND METHODS: This study analysed the data obtained for 43,937 child
patients under the age of 15 years, hospitalised for an oral-health related condition, as
determined by principal diagnosis (ICD-10AM), using the Western Australian Hospital
Morbidity Dataset for the period 1999–2000 to 2008–2009. Primary place of residency,
age, gender, insurance status, Indigenous status and socioeconomic status were also
analysed. The Australian Refined Diagnosis Related Group (AR-DRG) version 5.1 was
used to calculate the direct cost. An analysis of costs was broken down by the previously
mentioned risk indicators. Two separate methods (Linear method and the exponentially
weighted moving average method) were used to project future cases through to the year
2026. Both methods accounted for the projected increase in both the population and the
incidence of these conditions over time, using ten years’ worth of data. The residential
location of each child hospitalised due to an oral-condition during the study period, and
socioeconomic data in relation to existing services (School Dental Service clinics), at
metropolitan areas of Perth were geocoded and mapped using Quantum Geographic
Information Systems (QGIS).
IV
RESULTS: The total DRG cost of these admissions, both public and private, was
approximately AUS $92 million over ten years. Most of these funds went towards treating
‘dental caries’ and ‘Embedded and impacted teeth’ conditions of children under the age
of 15 years. ‘Dental caries’ were the most common in non-Indigenous patients, with ‘pulp
and periapical’ most prevalent in Indigenous patients. The Age Adjusted Rate (AAR) of
hospitalisation for Indigenous children in the last decade increased to reach that of non-
Indigenous children in 2009. When insurance status was considered, a total of 47.3% of
children reported lack of dental insurance coverage. Lack of health insurance coverage
was strongly associated with Indigenous children and children living in Remote areas.
Disparities in dental insurance coverage are also evident by socioeconomic status.
Moreover, a clear specific geographical areas, where no services are located, but where
high hospital-admission rates are occurring, especially among school-age children. The
least-disadvantaged areas and areas of high rates of school-age child hospital-admissions
were more likely to be within 2km of the School Dental Service clinics than not. More of
high-risk-areas (socioeconomically deprived areas combined with high oral health-
related hospital admissions rates), were found within 2km of the clinics than elsewhere.
The projected admission rate increase was 43% from 2000 to 2026. The admission rates
are expected to more than double over time for those children living in metropolitan
areas.
RECOMMENDATIONS AND CONCLUSION: Dental caries, embedded and impacted teeth,
and pulp and periapical conditions were and will continue to remain the mostly
preventable causes of admission throughout this time. Better understanding of
disparities in access to care among children, the socioeconomic divide in oral health and
V
insurance coverage, will be critical to improve Australian children’s oral health and
reduce financial burden on health budgets.
VI
Table of Contents
Title page ……………………………..…………………………………………………………………………………... I
Dedication ……………………………………………….…………………………………………………………….… II
Abstract ………………………………………….…………………………………………………………………….... III
Table of Contents ………………………………….………………………………………………………….…...... VI
List of Tables …………………………………………………….….…………………………………..………......... XI
List of Figures ………………………………………………………..…….……………..……………………..…. XIII
List of Abbreviations …………………………………….………….………………………………..….....….... XVI
Acknowledgments………………………………………………………………….……….………………….... XVII
Statement of Candidate Contribution ……………………..………………..……….…………...……….. XX
Publications Arising from Thesis ……………………………………………………………….………….. XXI
Chapter One …..…...…………………………………………………….……..……………………………….…..…. 1
1. Introduction...………………………………………………….…………………………………………….. 2
Chapter Two ………..…………………………………………………….……………………………………….…... 8
2. Literature Review …………………………………………………………………………………….……. 8
2.1. Introduction ……………………………………………………………………………….………. 9
2.1.1. Impact of poor health …………………………………………………………….……….. 9
2.2. Australian dental health care system and infrastructure ………………..…….. 10
2.2.1. Private dental practice and private dental health insurance ……..………11
2.2.2. School Dental Service …………………………………………………………………… 13
2.2.3. Hospital admission ……………………………………………………………………… 19
2.2.3.1. Children oral related hospital admissions ………………………….. 19
2.3. Determinants of oral health-related hospital admissions ………………….… 21
2.3.1. Age and gender …………………………………………………………………………… 21
2.3.2. Indigenous status ………………………………………………………………………… 22
2.3.3. Socioeconomic status …………………………………………………………………… 24
2.3.4. Accessibility and remoteness ……………………………………………………….. 24
2.3.5. Insurance status …………………………………………………………………………... 26
2.4. Oral health expenditures …………………………………………………………………… 26
2.5. Oral health status of Australian children …………………………………………….. 29
2.5.1. Dental caries ...……………………………………………………………………………... 30
Table of Contents
VII
2.5.1.1. National trends ………………………………………………………………… 30
2.5.1.2. Western Australia trends …………………………………………………... 35
2.5.2. Embedded and impacted teeth …………………………………………………….. 39
2.5.3. Pulp and periapical conditions ……………………………………………………… 41
2.5.4. Other oral conditions …………………………………………………………………… 43
2.5.4.1. Oral cancer ……………………………………………………………………….. 43
2.5.4.2. Periodontal conditions ...……………………………………………………. 44
2.5.4.3. Oral cysts …………………………………………………………………………. 45
2.5.4.4. Birth defects and Dento-facial anomalies ……………………………. 45
2.5.4.5. Dental trauma and Dental fractures …………………………………… 47
2.6. Oral health cost …………………………………………………………………………………. 48
2.7. Recommendations and Conclusion ...…………..……………………………………… 52
Chapter Three ……….………………...…………………………………………………………………………… 54
3. Aims of the study and Hypothesis ………………………………………………………………… 55
Chapter Four ………………………………………………………………………………………………………… 57
4. Material and Methods.…….……………………………..…………………………………………….. 58
4.1. Material ……………..…………………………………….………………………………………. 58
4.2. Methods …………………………………………………..……………………………………….. 59
4.2.1. Study population ……………………………….………………………………………… 59
4.2.2. The data source …………………………………………………………………………… 59
4.3. Projection methods …………………………………………………………………………… 62
4.4. Developing framework maps …………………………………………………………….. 63
4.5. Statistical analysis …………………………………………………………………………….. 67
Chapter Five …………………………………………………………………………………………………………. 69
5. Dental Hospitalisation Trends in Western Australian Children under the Age of
15 Years: a Decade of Population Based-Study ………………………….……………..…… 69
5.1. Abstract ………………………………………………………………………………………….... 70
5.2. Introduction …………………………………………………………………………..………… 71
5.3. Material and Methods ……………………………………………………………………….. 72
5.3.1. Data source ……………………………………………………………………………….... 72
5.3.2. Statistical analysis ………………………………………………………………………. 73
5.4. Results …………………………………………………………………………………………….. 74
5.4.1. Overall data summary ………………………………………………………………… 74
Table of Contents
VIII
5.4.2. All children ……………………………………………………………………………….... 74
5.4.3. Aboriginal and Torres Strait Islander children …………………………..…. 79
5.5. Discussion …………………………………………………………………………………...…… 82
5.6. Recommendations and Conclusion ..…………………………………………...……... 85
Chapter Six ………………………………………………………………………………………………...………… 86
6. Disparities in Dental Insurance Coverage among Hospitalised Western Australian
Children ……………………………………………………………………………………………….…….. 86
6.1. Abstract ………………………………………………………………………………………….... 87
6.2. Introduction …………………………………………………………………………………….. 88
6.3. Material and Methods …………………………………………………………………..…… 89
6.3.1. Data source ...………………………………………………………………………………. 89
6.3.2. Statistical analysis ...……………………………………………………………………. 91
6.4. Results ………………….…………………………………………………………………………. 91
6.4.1. Dental insurance (all children) ………………….…………………………………. 91
6.4.2. Dental insurance (Indigenous status) ………….……………………………….. 95
6.5. Discussion ……………………………………………………………………………………… 100
6.6. Recommendations and Conclusion ………………………………..…………….….. 104
Chapter Seven ……………………………………………………………………………………………….…… 106
7. A Population Based Cost Description Study of Oral Treatment of Hospitalised
Western Australian Children Aged Younger than 15 Years Old ……………….…… 106
7.1. Abstract …………………………………………………………………………………………. 107
7.2. Introduction …………………………………………………………………………………… 108
7.3. Material and Methods ……………………………………………………………………... 109
7.3.1. Data source ………...…………………………………………………………………….. 109
7.3.2. Principal diagnosis ……………………………………………………………………. 110
7.3.3. Determination of direct cost ………………………………………………………. 110
7.3.4. Indirect cost ……………………………………………………………………………… 111
7.3.5. Statistical analysis …………………………………………………………………….. 112
7.4. Results …………………………………………………………………………………………… 112
7.4.1. Direct cost (all children) ………………………………………………….………… 112
7.4.2. Direct cost (based on the most common oral conditions) ……………. 116
7.5. Discussion ……………………………………………………………………………………… 120
7.6. Recommendations and Conclusion ……………………………………...…………... 124
Table of Contents
IX
Chapter Eight ……………………………………………………………………………………………………... 125
8. Future projections of child oral health-related hospital admission rates in
Western Australia …………………………………………………...………………………………… 125
8.1. Abstract …………………………………………………………………………………………. 126
8.2. Introduction …………………………………………………………………………………… 127
8.3. Material and Methods …………………………………………………………………...… 128
8.3.1. Data source ………………………………………………………………………………. 128
8.3.2. Statistical analysis …………………………………………………………………….. 129
8.3.3. Cost projections ………………………………………………………………………… 130
8.4. Results …………………………………………………………………………………………… 131
8.4.1. Projections of all oral health-related hospitalisation rates .………….. 131
8.4.2. Projections of dental caries hospitalisation rates ………………………... 134
8.4.3. Projections of hospitalisation rates for embedded and impacted teeth
…………………………………………………………………………………………………. 136
8.4.4. Projections of hospitalisation rates for pulp and periapical conditions
…………………………………………………………………………………………………. 137
8.5. Discussion ……………………………………………………………………………………… 139
8.6. Recommendations and Conclusion ……………………………………..…………... 142
Chapter Nine ……………………………………………………………………………………………………… 143
9. Identifying and prioritising areas of child dental service need: a GIS-based
approach …………………………………………………………………………………………………... 143
9.1. Abstract …………………………………………………………………………………………. 144
9.2. Introduction …………………………………………………………………………………… 145
9.3. Material and Methods …………………………………………………………….……….. 146
9.3.1. Hospitalisation data …………………………………………………………………... 147
9.3.2. Census Collection District (CD) ………………………………………………….. 147
9.3.3. Population data ………………………………………………………………………… 148
9.3.4. Socioeconomic status ………………………………………………………………… 148
9.3.5. School Dental Service Locations ………………………………………………… 149
9.3.6. Geographic Information System methodology ……………………………. 149
9.4. Results …………………………………………………………………………………………… 149
9.5. Discussion …………………………………………………………………………………….... 157
9.6. Recommendations and Conclusion ……………………………………………...…... 160
Table of Contents
X
Chapter Ten ……………………………………………………………………………………………………….. 161
10. Discussion ………………………………………………………………………………………………… 161
10.1. Introduction …………………………………………………………………………………… 162
10.2. Trends of children oral health-related hospitalization …………………….... 163
10.3. Trends of children oral health-related hospitalisation for most prevalent
conditions ……………………………………………………………………………………… 168
10.4. Framework model ………………………………………………………………………….. 172
10.5. Future studies ………………………………………………………………………………… 174
10.6. Recommendations and Conclusion ……………………………………………...…... 174
References …………………………………………………………………………………………………………. 176
Appendices ………………………………………………………………………………………………………… 197
Appendix A ……………………………………………………………………………………………………. 198
Appendix B ……………………………………………………………………………………………………. 200
Appendix C ……………………………………………………………………………………………………. 209
Appendix D …………………………………………………………………………………………...………. 219
Appendix E ……………………………………………………………………………………………………. 228
Appendix F ……………………………………………………………………………………………………. 235
XI
List of Tables
Table 2.1
Key effectiveness indicators of disease prevention and health promotion of SDS in
metropolitan areas of WA over time.
Table 2.2
A summary of the total oral health Australian budget (in $ million) by source of fund, over
time.
Table 2.3
Percentages of children attending a School Dental Service with dmft + DMFT > 0 by age,
over time.
Table 2.4
Age-specific average caries experience (dmft) in children attending a School Dental
Service, over time.
Table 2.5:
Age-specific average caries experience (DMFT) in children attending a School Dental
Service, over time.
Table 2.6:
Comparison of the average caries experience in children based on age and State and
Territory, 2007.
Table 2.7:
Average numbers of decayed, missing or filled teeth (DMFT) for school children living in
metropolitan areas, over time.
Table 4.1.
Percentage of hospital admissions of those demographic variables in the data set.
Table 5.1
Hospitalisation of WA children for most common oral conditions across different variables.
Table 5.2
Age-specific rates of hospitalisation for oral health conditions across age groups, gender and
geographical location.
List of Tables
XII
Table 6.1
Represent percentage of hospitalisation of WA children based on insurance status
compared with different variables.
Table 6.2
Percentages of insurance coverage among hospitalised WA children based on indigenous
status and different variables.
Table 7.1
The Australian Refine Diagnosis Related Group cost of hospitalisation of Western
Australian children based on different variables.
Table 7.2
The Australian Refine Diagnosis Related Group cost (in $ millions) of hospitalisation of
Western Australian children based most common oral conditions and different variables.
Table 9.1
Zero to four years old child population distribution by hospital admission rates and
socioeconomic status inside/outside the 2km Zone of existing SDS clinics.
Table 9.2
Five to nine years old child population distribution by hospital admission rates and
socioeconomic status inside/outside the 2km Zone of existing SDS clinics.
Table 9.3
Ten to fourteen years old child population distribution by hospital admission rates and
socioeconomic status inside/outside the 2km Zone of existing SDS clinics.
XIII
List of Figures
Figure 4.1.
Map of Western Australia.
Figure 5.1
Hospitalisation rates by age, over time.
Figure 5.2
Age-adjusted hospitalisation rates of WA children by condition, over time.
Figure 5.3
Hospitalisation age-adjusted rates of WA children by Indigenous status, over time.
Figure 6.1a
The percentages of hospitalisation among WA children based on insurance status.
Figure 6.1b
The percentages of insured hospitalised WA children over time based on age.
Figure 6.1c
The percentages of uninsured hospitalised WA children over time based on age.
Figure 6.2
The percentages of hospitalisation among WA Indigenous children based on insurance
status.
Figure 6.3
The percentages of hospitalisation among WA non-Indigenous children based on
insurance status.
Figure 7.1
The Australian Refine Diagnosis Related Group cost of dental hospitalisation of Western
Australian children over time in million.
Figure 7.2
The Australian Refine Diagnosis Related Group cost of dental hospitalisation of Western
Australian children over time in million.
List of Figures
XIV
Figure 8.1
Projection of children’s Age Adjusted hospitalisation Rates due to oral conditions over
time and based on age.
Figure 8.2
Age-adjusted hospitaliation rates projection to 2026 of hospitalised children based
location.
Figure 8.3
The projected DRG cost of dental hospitalisation of Western Australian children through
to 2026 in millions of dollars.
Figure 8.4
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to
caries conditions based on age.
Figure 8.5
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to
dental caries based on location.
Figure 8.6
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to
impacted or embedded tooth removal based on age.
Figure 8.7
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to
impacted or embedded dental removal based on location.
Figure 8.8
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to pulp
and periapical conditions based on age.
Figure 8.9
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to pulp
and periapical dental conditions based on location.
Figure 9.1
High age-adjusted oral related admission rates of children living in low socioeconomic
areas (SEIFA<6) inside 2km zones of existing School Dental Service clinics in Perth.
List of Figures
XV
Figure 9.2
High age-adjusted oral related admission rates of children living in low socioeconomic
areas (SEIFA<6) outside 2km zones of existing School Dental Service clinics in Perth.
Figure 9.3
High age-adjusted oral related admission rates of children living in high socioeconomic
areas (SEIFA>5) inside 2km zones of existing School Dental Service clinics in Perth.
Figure 9.4
High age-adjusted oral related admission rates of children living in high socioeconomic
areas (SEIFA>5) outside 2km zones of existing School Dental Service clinics in Perth.
XVI
List of Abbreviations
AAR Age Adjusted Rates
ABS Australian Bureau of Statistics
AIHW Australian Institution of Health and Welfare
AR-DRG Australian Refined Diagnosis Related Group.
ARIA Accessibility/Remoteness Index of Australia.
AUD Australian Dollar.
CD Collection Districts.
CI Confidence Interval.
DALY Disability Adjusted Life Years
DMFT Decayed, Missing and Filled permanent tooth.
Dmft decayed, missing and filled deciduous tooth.
ECC Early Childhood Caries.
GIS Geographic Information System.
ICD-10AM International Classification of Diseases Tenth-Australian Modification.
INDIGENOUS Aboriginal and territory Islander.
MTDP Medicare Teen Dental Plan
SDS School Dental Services.
SEIFA Socio-Economic Index of Areas.
SPSS Software Package for Social Sciences.
SLA Statistical Local Area.
USA United States of America.
WA Western Australia
WHO World Health Organization.
XVII
Acknowledgements
I would like to take the opportunity to individually express gratitude to the people who
deserved it.
Professional Acknowledgments
I would like to express my appreciation to all of my supervisors in the School of Anatomy,
Physiology and Human Biology, at The University of Western Australia: Emeritus
Professor John McGeachie, Winthrop Professor Marc Tennant, and Associate Professor
Estie Kruger for their continued support and guidance throughout the duration of this
thesis. First and foremost, I would like to thank my co-ordaining supervisor Prof. Marc
Tennant, for accepting me as a PhD candidate, assisting me with the selection of such a
brilliant topic, and for maintaining faith in me to finish this endeavor. Throughout the
years, I often wonder if he had more confidence in me, than I did in myself. This was
reflected by the many wonderful opportunities he passed my way. I would not be here
today without the help of Marc. I would like to extend my very sincere gratitude to Dr.
Estie Kruger –Associate Professor at the Centre for Rural and Remote Oral Health, The
University of Western Australia, who has been my thesis supervisor, for her generous
help, mentoring and never failing enthusiasm for my work. She always makes me think
outside the box. Her passion, dedication and brilliant accomplishments to academia
inspire me. Estie has taught me much of what I know about Dental Public Health. Her
concern and continual patient encouragement has been invaluable and a quality I was yet
to experience with any other teacher during my student life.
Acknowledgements
XVIII
My warm thanks to Emeritus Professor John McGeachie, my other thesis supervisor, for
his skilled guidance, inspiring words and for being supportive of my career endeavors
throughout my study period and beyond. It is a great privilege for me to be able to share
in his vast scientific knowledge and experiences.
I would like to extend my thanks to Taibah University Collage of Dentistry, Saudi Arabia,
for sponsoring my PhD studies.
Personal Acknowledgements
I thank Allah for his blessings on me. May I never forget to praise and thank him in
everything I do.
A little closer to home, I want to express gratitude to several people who are dearest to
me. If it were not for the unconditional love, sacrifices and support which exceedingly
warranted and without their assistance I don’t know where I would be. Thank you my
mother and father, Adlyah Aqeel and Talal Alsharif, as they have always instilled in me,
that I can achieve anything I set my mind to; thank you for everything, as I am deeply
indebted to you.
Appreciation and gratitude must be extended to Dr. Khalid my husband, for everything
he has made and continue to make for me; I would not be who I am today. No word can
ever describe how grateful I am to them. Khalid’s confidence in me has allowed me to
achieve my dreams. He is my soul mate until the end of time.
Acknowledgements
XIX
Finally, a special thanks to my children, sisters and brothers, who have made sacrifices in
their lives so that I may achieve my ambitions and goals. Throughout my journey, they
have provided me courage, support and motivation to never let your dreams die.
XX
Statement of Candidate Contribution
I hereby declare that all of the included work in this thesis is entirely my own. The
research was conducted under the supervision of A/Professor Estie Kruger, W/Professor
Marc Tennant and Professor John McGeachie. For the co-authored published work, my
contribution was 80%. Contributions with other colleagues are mentioned accordingly
and listed as co-authorships in the published papers.
Alla Talal Alsharif
BDS, MPH, MRACDS
W/Prof. Marc Tennant A/Prof. Estie Kruger
School of Anatomy, Physiology and Human Biology School of Anatomy, Physiology and Human
Biology
E/Prof. John McGeachie
School of Anatomy, Physiology and Human Biology
XXI
Publications Arising from Thesis
Chapter 5: Alsharif, Alla, Kruger, Estie & Tennant, Marc. (2014). Dental hospitalization
trends in Western Australian children under the age of 15 years: a decade of
population-based study. International Journal Paediatric Dentistry. 25(1), 35-42.
Chapter 6: Alsharif, Alla, Kruger, Estie & Tennant, Marc. (2014). Disparities in dental
insurance coverage among hospitalized Western Australian children.
International Dental Journal. 64(5), 252-259.
Chapter 7: Alsharif, A. T., Kruger, E. & Tennant, M. (2015). A population-based cost
description study of oral treatment of hospitalized Western Australian children
aged younger than 15 years. Journal of Public Health Dentistry. 75(3), 202-209.
Chapter 8: Alsharif, Alla, Kruger, Estie & Tennant, Marc. (2016). Future projections of
child oral health-related hospital admission rates in Western Australia. Australian
Journal of Primary Health. http://dx.doi.org/10.1071/PY15132.
Chapter 9: Alsharif, Alla, Kruger, Estie & Tennant, Marc. (2016). Identifying and
prioritising areas of child dental service need: A GIS-based approach. Community
Dental Health. 33(1), 33-38.
These chapters have been formatted to the same layout of the thesis. In addition, the
references for these chapters are incorporated in the bibliography; published versions
have been included in Appendices B, C, D, E & F.
1
Chapter One
1. Introduction
Chapter One
2
1.1. Introduction
Oral Health is fundamental to overall health, wellbeing and quality of life. The impact of oral
disease on people’s everyday lives is subtle and invasive, influencing eating, sleeping,
working and social roles (Australian Institute of Health and Welfare, 2004). Over the past 20
years, the prevalence of caries among school children has diminished. This can be attributed
to improved oral health care, water fluoridation, lifestyle changes and the introduction of
School Dental Services (SDS) as preventive and early intervention centres.
In the 1970s the Australian Government established the SDS to provide a range of oral health
care for registered school age children who are unable to obtain treatment from private
dentists. The Government funded the development of infrastructure and the education of
dental therapists as the workforce for SDS (Australian Dental Association, 2010). These
services achieved wide coverage of the target primary school population in most Australian
States and Territories aiming at reducing the occurrence of dental caries among school
children (Australian Dental Association, 2010). Shortly after, most SDS were then extended
through the secondary school population. School children had access to free dental checkups
at least once every year and covering basic restorative and preventive care, and some limited
orthodontic care. The SDS is considered to be effective in reaching a substantial percentage
of children. The unit cost of the services is low and the health outcomes continue to improve,
providing an excellent base on which the oral health of Australians can be built.
Although significant improvements have occurred in the oral health of children in the last 30
years, high levels of oral disease and disability among a minority of Australian children still
Chapter One
3
persist (Australian Institute of Health and Welfare, 2004). Since the late 1990s, a clear and
increasing trend of caries in the deciduous dentition of children attending SDSs has been
observed (Australian Research Centre for Population Oral Health, 2011). In 2004, this trend
has become apparent (Australian Research Centre for Population Oral Health, 2011), as
these services only reach a little less than 30 % of enrolled school children (Spencer, 2012).
By 2006, there was an increase of 28% in deciduous caries experience (Australian Research
Centre for Population Oral Health, 2011). The mean decayed, missing and filled deciduous
surface (dmfs) was 2.28±6.00 of pre-school age children (Hallett & O’Rourke, 2002). In
contrast, 49% and 57% of children aged 5-6 years and 12–15 years respectively, had had
some history of tooth decay, (Australian Institute of Health and Welfare, 2006a). The 10% of
children with the most extensive history of permanent tooth decay had between 5 and 8
permanent teeth affected, which was about 4.5 times the national average (Australian
Institute of Health and Welfare, 2006a).
The publically funded SDS face additional challenges especially among isolated communities
and in most disadvantaged geographical areas. Poor oral health in Australia is most evident
among Indigenous peoples, rural and remote populations, particularly people with low
incomes (Australian Institute of Health and Welfare, 2004; 2007a). Children in low
socioeconomic groups experience almost twice as much caries as those in high
socioeconomic groups (An Advocacy Kit for Community & Welfare, 2010). About half of
children from low income families experienced dental decay. Most of preschool children and
those living in the rural and remote areas of WA have minimal access to dental services
before they become registered with a publically funded School (Dogar, Kruger, Dyson, &
Tennant, 2011; Kruger, Dyson, & Tennant, 2005). Hence, the prevalence of dental caries in
Chapter One
4
rural areas is higher than in metropolitan areas. Indigenous children have the highest
prevalence of dental caries. Recent studies have also indicated that most Indigenous
Australians children still do not have access to tooth brushes, and less than 5% of remote
Indigenous pre-school children brush their teeth on a regular basis (Australian Institute of
Health and Welfare, 2007b). Therefore, Indigenous children had consistently higher levels
of dental caries in the deciduous and permanent dentition than their non- Indigenous
counterparts at all ages between 4 and 14 years (Australian Institute of Health and Welfare,
2007b; Williams, Jamieson, MacRae, & Gray, 2011). Unfortunately, the oral health of
Indigenous children has continued to worsen over recent decades, in contrast to the progress
seen among non-Indigenous children. Indigenous children most affected were in socially
disadvantaged groups and those living in rural/remote areas. Failure and delays in seeking
treatment will lead to more complex conditions and thus hospitalisation might be inevitable.
Dental caries is the 5th most prevalent cause of hospitalisation in children in Western
Australia (WA) (Tennant, Namjoshi, Silva, & Codde, 2000). During 1999- 2003, dental
conditions accounted for nearly 26,000 avoidable hospital admissions (Kruger, Dyson, &
Tennant, 2006). The majority of cases were for extractions due to dental caries, and they cost
the WA State more than $40 million (Kruger Dyson, & Tennant, 2006). Admission for dental
care is substantially more common in rural children compared to their metropolitan
counterparts (Kruger Dyson, & Tennant, 2006; Australian Institute of Health and Welfare,
1998). In the 13-17 year age group, admission rates are more than 31 times higher among
non- Indigenous, compared to Indigenous children (Kruger Dyson, & Tennant, 2006).
Additionally, some children require a general anesthetic because they have comorbid health
conditions; for others it is because their teeth are in such poor condition. Indigenous children
Chapter One
5
aged <5 years had almost 1.5 times the rate of hospitalisation for dental care compared with
other Australian children (Australian Institute of Health and Welfare, 2007b). The rate of
Indigenous children receiving hospital dental care increased with increasing geographic
remoteness (Steele, Pacza, & Tennant, 2000). Many young remote Indigenous children
experienced extensive destruction of their deciduous teeth which require complex
treatment. Children aged less than 10 years, especially those at socioeconomic disadvantage,
are substantially more likely to be hospitalised for dental conditions than other age groups
(Australian Institute of Health and Welfare, 2007a). Hospitalisation could generally be
avoided, when they are given early access to appropriate services.
This thesis will examine oral related hospitalisations to determine the trends in Western
Australian children, and to determine the socio-demographic characteristics of at high risk
groups of the population. Previously, Kruger Dyson, & Tennant (2006) determined that
hospital admissions in children mainly included Indigenous and other disadvantaged
children living in rural areas. Against the recent period of very rapid demographic change
and changing patterns of oral disease in Australian children, current population-based
studies become fundamental to determine time trends in hospitalisation rates and to identify
those groups at high risk of hospital admissions. Therefore, this study analysed a decade of
population hospital data of children aged between 0–14 years old (n=43,937), to establish
the current trend of oral admissions, which will also help in identifying the
sociodemographic characteristics of the minority of population at higher risk of admission.
In Australia, oral and general health-care systems operate differently (in terms of funding
and access), therefore differences between private health coverage of the same population
should be addressed. As in privately driven markets (such as dental markets), where well-
Chapter One
6
insured patients are common, public dental care coverage in children alone will not be
sufficient to remove disparities in dental care utilisation. For instance, wealthy individuals
with private dental cover have better use of services and subsequently better oral health. By
contrast, individuals with poor oral health and subjected to long waiting lists for public
dental care are much less fortunate outcomes for uninsured counterparts (Haas & Anderson,
2005). These facts clearly indicate that different health coverage among the same population,
may yield very different results. Previously, there have been no comparative studies of
private oral health coverage among Western Australian children. Therefore, this study
examines the disparities in dental insurance coverage among Western Australian children
hospitalised due to oral health-related conditions. The study also investigates associated
factors to address the inequalities that currently exist.
Continuous remodeling of the primary oral health service (e.g. SDS) to meet changing
demands is crucial. This is necessary in order to reduce the burden of oral related conditions
on childrens’ secondary oral health service (hospitals) on both individual and population
levels. A strategy to identify and address access issues should be based on relevant and
reliable information (such as population based studies). In a dental public health context, the
research undertaken for this thesis is aimed at understanding the oral health hospital
admissions issues of children living in WA, and also to highlight associated system costs. This
is designed to enable, or facilitate the determination of projected costs and utilisation of oral
health services in the future, based on predicted demand for services, as well as the maximal
utilisation of limited resources.
Chapter One
7
Thereby, this thesis aims to examine the optimisation of the current primary oral health
service (SDS) to identify and prioritise areas of high need for dental services among the child
population in metropolitan Western Australia, based on published hospitalisation data. It is
proposed that this will lead to the development of a model to provide an understanding
of the distribution of demand for primary oral health services (in this case SDS). This model
may be used as a decision support tool to design/test new frameworks for targeted SDS
approaches, to enable the community to have timely access to preventively focused dental
care that meets the minimum standard benchmarks for oral health service provision.
In order to understand better the hypotheses tested and the specific aims of this research,
some background on the Australian oral health system, oral health determinants, and the
prevalence of oral health conditions reviewed in relevant detail. A summary of the oral
related hospitalisation trends among children and the associated costs are presented in the
following chapter.
8
Chapter Two
2. Literature Review
Chapter Two
9
2.1 Introduction
2.1.1 Impact of Poor Oral Health
Oral Health is a fundamental part of general health and quality of life. The impact of oral
disease on people’s everyday lives is subtle and invasive, influencing eating, sleeping,
working and social roles. It is evident that a quarter of Australians avoid eating some foods
as a consequence of pain and discomfort caused by their poor oral health (Roger, 2011), and
almost 25% of Australians report experiencing orofacial pain in the previous month (The
Steering Committee for the Review of Government Service Provision, 2010).
When Begg et al. (2003) compared the Disability Adjusted Life Years (DALY) lost from oral
conditions with other selected health problems; the results indicated that oral diseases were
responsible for the loss of 24,507 DALY. When only quality of life is considered, the impact
of oral conditions is estimated to be greater over a 12-month period than the effect of all
infectious diseases combined. Furthermore, these data revealed that the effects were greater
than either breast cancer or lung cancer (Begg et al., 2003). The total loss was predominantly
a result of dental caries (12,008 DALYL), pulpitis and edentulism data were 6,497 and 5,264,
respectively (Begg et al., 2003).
Poor oral health has also been linked to a range of health conditions. Despite the fact that
many oral conditions and chronic disease share many other risk indicators. There is strong
evidence that a small but significant relationship exists. Cullinan et al. (2009) provided a
current understanding of the mechanisms involved in poor oral health to systemic diseases.
Chapter Two
10
Their results revealed an increasing risk of respiratory conditions, cardiac disease and
osteoporosis, as well as increasing rates of diabetes complications (Cullinan et al., 2009).
Similarly, periodontitis contributes to poor glycaemic control among individuals with
diabetes, which can place them at risk for diabetic complications (Taylor & Borgnakke,
2008).
The impact of poor oral health is not only on the individual through pain and discomfort, but
also for the broader impact on their community through significant cost to the health system
and associated economy (Australian Health Ministers’ advisory Council, 2004). Oral
conditions are responsible for large numbers of acute preventable hospital admissions (The
Steering Committee for the Review of Government Service Provision, 2013). Therefore, it is
essential to improve preventable oral conditions at both individual and community levels.
This introductory chapter explores the following parameters: the oral health system and
School Dental Service; Australian children’s oral health patterns; and potentially preventable
oral health-related hospitalisation and associated costs, with a particular focus of at high risk
population.
2.2. Australian Dental Health Care System and Infrastructure
The Australian health care system’s fundamental goal is to ensure individual accessibility to
care based on need rather than ability to pay. However, this goal has not been entirely met
in relation to oral or dental services. Historically, since the Australian Health Act (AHA) does
not consider dental care as part of general health care, dental conditions are not subjected
to publically-administered, universal, convenient, accessible and comprehensive service.
Chapter Two
11
Although, medical services are mainly publicly funded, most dental services are provided by
private practitioners and thus Australians are responsible for funding their own dental care.
In Australia, dental health care is provided through private practice (this service’s costs are
paid by private dental insurance or by paying directly out-of-pocket), or through
government-subsidised programmes such as School Dental Services for children, or through
public hospital clinics for adults (Haas & Anderson, 2005). This thesis will focus on children
directed-oral health programs.
2.2.1. Private Dental Practice and Private Dental Health
Insurance
Australians can attain private dental insurance by purchasing either hospital cover
combined with an ‘extras’ option that includes dental services, or the ‘extras only’ option.
Two levels of dental services coverage are provided: general dental and major dental
coverage. General dental coverage normally includes services such as cleaning, removal of
plaque, X-rays and small fillings. On the other hand, in addition to previously mentioned
services, major dental coverage includes services such as orthodontics, third molar
extractions, crowns, bridges and dentures. Although, owning private health insurance seems
to be promising, it covers only a proportion of costs, based on the level of insurance; leaving
the consumer to face a relatively high out-of-pocket cost for dental services. This section will
emphasise private health insurance levels in Australian, however, out-of-pocket and
treatment cost will be discussed later in this chapter.
Chapter Two
12
In 1996, 40% of Australian children aged 5–11 years were covered by private dental
insurance, (Bagramain et al., 2009). Despite the introduction of the Private Health Insurance
Incentives Scheme (PHIIS) in 1997, dental insurance coverage among children 5–11 years
declined to reach 35.6% in 1999 (Fisher-Owens, 2007). This scheme had a higher impact on
families with adolescents due to the higher cost of dental care associated with orthodontic
treatment. However, following the introduction of the 30% rebate scheme in 1999 and
Lifetime Health Cover in 2000, private health insurance coverage increased to 42.1% in 2002
and 43.8% in 2005 among children aged 5-11, and from 45.7% (1999) to 51.7% (2002) in
children aged 12-17 (Ellershaw & Spencer, 2009; Watt, 2007). From 1996 to 2005, the level
of private dental coverage among Australians has increased by only 3.8% (Bagramain et al.,
2009). In 2009, more than half (54%) of children aged 5–14 reported some level of private
dental cover, with those living in urban areas (59%) having higher rates of insurance than
those in rural and remote regions (47%) (Ellershaw & Spencer, 2009).
Insured children were more likely to have visited a dentist for a check-up within the previous
12 months compared to uninsured counterparts (Ellershaw & Spencer, 2009). Insured
children are more likely to regularly visit a dentist for a check-up or preventable care than
non-insured. Private dental coverage was similar among male and female children aged 5–
11 years. Private dental insurance is an important factor modifying access to dental care.
Insured children were significantly more likely to have visited a private practice than
uninsured children (Ellershaw & Spencer, 2009). Furthermore, insured children are more
likely to be hospitalised for proper treatment than uninsured counterparts who were more
likely to receive extractions in dental clinics as out-patients and would have considerable
difficulty paying a $100 dental bill.
Chapter Two
13
The presence of private dental coverage increased the inequity in access to care, as wealthy
individuals have better oral health and use more complex and expensive services (Haas &
Anderson, 2005). Whereas waiting lists for public dental care have grown by 20% per year
(Haas & Anderson, 2005), which leads to limited access to dental care and bears the greatest
burden of untreated disease (An Advocacy Kit for Community & Welfare, 2010). There is a
general agreement that most deprived families, Indigenous and children living in remote
areas are the most marginalised groups by the current dental care system (An Advocacy Kit
for Community & Welfare, 2010). However, to the best of the author’s knowledge, no
published study has indicated the level of private insurance among those subgroups.
2.2.2. School Dental Services (SDS)
When one analyses the socioeconomic divide in oral health, different policies have been
suggested to address those inequalities (Haas & Anderson, 2005). Several challenges face the
public dental health services, especially among isolated communities and in disadvantaged
geographical areas. Therefore, the Australian government has established SDS, which is a
publically delivered children’s dental program, to address those inequalities.
Most children enroll in the SDS when they start school, usually at the age of 5 years
(Government of Western Australia, 2008a) and continue to receive dental health care up to
17 years. The SDS aims at reducing the occurrence of dental caries among school children,
mainly those unable to obtain treatment from private dentists. The services are available to
government and non-government schools, which increases the number of children accessing
early dental care in WA (Hallett & O’Rourke, 2003). In other situations, where SDS is difficult
to be accessed, mobile dental clinics are provided to school children. School children are
Chapter Two
14
examined by dentists to determine the state of their dental health. Dental therapists are also
used in the provision of SDS (Bratthall, 2000). Therapists who provide these services are
usually under the control of registered dentists in most Australian states (Government of
Western Australia, 2008a). Though, dental therapists are used in areas where dentists are
too expensive. Dental laboratory services in field clinics are provided by dental technicians
(Government of Western Australia, 2008a). Dental health educators also participate in the
SDS by carrying out dental health education lectures, such as brushing techniques, oral
hygiene, plaque control, fluoridation and the importance of dental health (Rayner, Holt,
Blinkhorn, & Duncan, 2003; Government of Western Australia, 2008b). Small groups of
children in classrooms are taught the importance of fluoridation in preventing dental caries
(Brennan et al., 2008). Young children attend demonstrations hosted by the dental service
providers, which explain brushing techniques and application of fluoride. Older children
attend lectures where dentists discuss signs of dental caries and prevention procedures
(Nainar & Straffon, 2003). Dental therapists also aim at changing the children’s attitudes
towards oral health care and other aspects of health behaviour.
The services provide access to free dental checkups at least once every year and children
diagnosed with dental problems continue receiving free dental services from the SDS clinics.
SDS staff provide oral health intervention treatment for controlling dental caries. Children
undergo screening examination procedures such as bite-wing radiographs which aim at
identifying dental diseases such as caries (Government of Western Australia, 2008a).
Children with signs of dental caries undergo simple restorative treatment such as excavation
of softened dentine and temporary restorations, and children with severe dental caries
undergo restorations or extractions (Armfield, Slade, & Spencer, 2006). Those services
Chapter Two
15
include preventive procedures such as topical fluoride application and prophylaxis. Oral
prophylaxis of fluoride solutions is also provided to children especially those with limited
access to fluoridated water as a preventive measure (Government of Western Australia,
2008a). The unit cost of the services is low and the health outcomes continue to improve,
providing an excellent base on which the oral health of Australians can be built.
Although, treatments provided are cheap and considered to be an efficient way of combating
dental caries among school children, the comprehensiveness of these programmes differs
significantly among State and Territories in terms of the types of services covered, age
restrictions and limits on the frequency of dental visits and enrolment levels. Some services,
for instance, the SDS comprehensive dental care programmes in WA, were not extended
through the secondary school population, and only limited to school children under the age
of 15 years (Government of Western Australia, 2008a). Therefore, the Western Australian
Government has introduced the Medicare Teen Dental Plan (MTDP) in 2008 (Australian
Institute of Health and Welfare, 2012), where families, who are receiving Family Tax Benefit
A, were provided with preventive dental check vouchers. These are worth $150 and are
issued annually to children between the age of 12 and 17 years (Australian Institute of Health
and Welfare, 2012). The preventive dental check covers oral examination, scale and cleaning,
oral hygiene instruction, fluoride application, and fissure sealants, depending on the child’s
requirements (Government of Western Australia, 2013). These vouchers can be used in both
private and public dental clinics. However, they can only be redeemed for free at specific
clinics. However, the (MTDP) closed on 31 December 2013, and was replaced by The Child
Dental Benefits Schedule (CDBS) which was available only to eligible children since the
beginning of 2014 (Australian Institute of Health and Welfare, 2013a). This $2.7 billion
Chapter Two
16
measure will provide a Commonwealth funded capped benefit entitlement for basic dental
services for children (Australian Institute of Health and Welfare, 2013a). Around 3.4 million
children aged 2-17 in families who meet a means test will be eligible for benefits each year
(Australian Institute of Health and Welfare, 2013a). The total benefit entitlement will be
capped at $1,000 per child over a 2-year period (Australian Institute of Health and Welfare,
2013a).
The Western Australia Health Department assists the Metropolitan School Dental Services
Key performance indicators. An annual report of the service’s effectiveness indicators is
released to assess and monitor the extent to which Government outcomes are being achieved
through the resource used and the community service delivered. The key performance
indicators in table 2.1 show the extent to which the Metropolitan School Dental Service is
performing in Western Australia.
Chapter Two
17
Table 2.1:
Key effectiveness indicators of disease prevention and health promotion of SDS in
metropolitan areas of WA over time.
Percentage of 2001 2002 2003 2004 2005 2006 2007 2008 2009
Eligible school children
who are enrolled in the
SDS program:
Pre-primary program
Primary program Secondary
program
84.2
85.9
77.2
82.6
85.2
82.2
84.3
85.2
82.2
83.7
84.7
84.4
83.3
84.5
80.7
82.6
84
81.2
80.3
83.5
82.9
78.5
82.7
82
76.8
80
79.4
Children under care:
Pre-primary program
Primary program Secondary
program
84.2
85.9
58.9
82.6
85.2
58.9
84.3
85.2
58.5
83.7
84.7
70
83
84.5
58.3
82.6
84
58.7
80.3
83.5
60.4
78.5
82.7
59.7
76.8
80
57.9
Children free of
active dental caries
on recall
67.1
67.2
67.6
67.6
66.7
66.0
66.7
65.9
65.4
Data source: WA Metropolitan Health Service Annual reports of 2005-06 and 2009-10
Although, over the past 20 years, the introduction of SDS has reduced the prevalence of
caries among school children due to preventive measures and early treatment (Gussy,
Waters, & Kilpatrick, 2006), dental caries is still a common disease among WA school
children (Hallett & O’Rourke, 2002). Furthermore, decay is the fifth common cause of
hospitalisation for school children in WA (Tennant et al., 2000). Thus, improving dental
health of children is a major step towards improving their general health (Australasian
Academy of Paediatric Dentistry, 2004).
Although, SDS is effective in reaching a high percentage of children, there are several
limitations associated with the application of these standards. Difficulties include the
Chapter Two
18
limitation that the service is restricted to registered school children. Children with no or
limited access to SDS or mobile dental clinics who are living in very remote areas (Steele,
2000), aged under 5, and thus not registered in SDS (Kruger, Dyson, & Tennant, 2005), and
children being home schooled, are not enrolled in the SDS, and this contributes to an under
estimation the burden of dental and oral disease in the state. Home-educated children can
only access SDS after booking appointments and showing evidence of registration. Lam et al.
claimed that in Perth WA metropolitan areas, children had a median of 13 SDS visits until 12
years of age, with 10% having less than 5 visits, and 4% having more than 25 visits (Lam et
al., 2012). On the other hand, Spencer (2012, p. 20) revealed that:
‘…..However, these services only reach a little less than 30
percent of primary and secondary school children. Services are
somewhat loosely targeted toward lower and middle income
families. While coverage has been declining rapidly since 2000,
there is still a backbone of school or community dental services
for children in Australia. What is desired is a system that
captures those not visiting in any one year and which can re-
orient dental services towards population and clinical
prevention.’
Additionally, treatment outside the scope of the SDS is referred to hospitals or other
specialist providers and any costs are the responsibility of the parent or guardian
(Government of Western Australia, 2008a). Stewart et al. (2012) published a review of the
reasons and sources of referral to hospital Paediatric dental service. The data showed that
salaried public dental services are responsible for more than half (56%) of hospital
consultations’ referrals; however, only 31.2% are from private dental practitioners (Stewart
et al., 2012). Additionally, almost 8% and 5% were from emergency departments and
Chapter Two
19
medical practitioners, respectively (Stewart et al., 2012). Researchers have also indicated
that 51% of the total public dental service referrals to the hospitals were for children who
had difficulty cooperating for dental treatment, and 22.7% were for treatment planning only
(Stewart et al., 2012). Referrals from private dental practitioners were mainly for treatment
planning only (Stewart et al., 2012). These findings reveal that public dental service
professionals are facing more problems dealing with anxious children who had difficulty
cooperating for dental treatment, than private dentists. At the same time, the proportion of
referrals for trauma or for extensive dental disease from private dental practitioners was
twice as high as from the public dental service (Stewart et al., 2012). However, almost all
attendances for dental trauma were from an emergency hospital department. The majority
of referrals from medical doctors were for medically at-risk children or oral disease induced
by other illness (Stewart et al., 2012).
2.2.3. Hospital Admissions
2.2.3.1. Children Oral Health-related Hospital Admissions
Dental diseases are the third most common cause for having general anaesthetics in children
(Sims, Stanley, & Milnes, 2005). Public hospitals are accountable for oral health-related child
admissions, in WA only few numbers of them are responsible for those admissions. However,
a significant number of potentially preventable hospitalisations occurred in private
hospitals. Firstly, it is important to define the Potentially Preventable Hospitalisation (PPHs),
which are ‘hospital separations’. This is a special term for hospitalisation data. In simple
terms it means discharged from hospital but it takes into account some specific factors like
being transferred to another hospital and also dying and being born in a hospital. In short is
Chapter Two
20
means being discarded from hospitals. In the context of this thesis it refers to the case where
the principal diagnosis of the hospitalisation is thought to be avoidable (Australian Institute
of Health and Welfare, 2014b). Preventable oral health-related hospital admission rates can
be considered as an indicator of inadequate access to dental care service. Furthermore, high
PPHs rates indicating an increased in the prevalence of those conditions within the
community, poor non-hospital care system performance or, alternatively, an appropriate use
of the hospital system to respond to greater need (Australian Institute of Health and Welfare,
2013a). In Australia, the total number of preventable dental conditions hospital separations
increased from 57,955 to 63,327, between 2007–08 and 2011–12 (Australian Institute of
Health and Welfare, 2014b). Along with the population growth the separation rate remained
steady at 2.8 per 1,000 population (Australian Institute of Health and Welfare, 2014b).
Children aged less than 15 had a preponderance of those PPHs (Australian Institute of Health
and Welfare, 2014a). Children aged 5–9 had the highest number of hospital admissions
(13,503 separation), followed by children aged 4 and younger (7,791 separations). Across
all States and Territories, Western Australia had by far the highest at 3.8 admissions per
1,000 population in 2010 (Australian Institute of Health and Welfare, 2014b). Tennant et al.
(2000) conducted a study similar to Kruger et al. (2006) comprising oral related admissions
of Western Australian children, aged 0 to 17 years. The results of those studies revealed
increasing trends in oral related admission over time. Tennant et al. (2000) confirmed that
a total of 3,754 episodes (4,395 bed days) were admitted for oral care. While Kruger et al’s
study estimated that between 1999 and 2003, a total of 26,497 episodes of care (31,431 bed
days). Of the latter admissions, 24% episodes were admitted in 1999-00, 23% in 2000-01,
25% in 2001-02 and 28% in 2002-03 (Kruger at al., 2006). Interestingly enough, although
Chapter Two
21
the state of WA demonstrated average or low dmft/DMFT score among children across ages,
high hospitalisations have been detected.
Hospitalisation rates of potentially preventable dental conditions thus provide an indicator
of the potential inadequacy of dental care in the community (Chrisopoulos & Harford, 2013).
Therefore, culturally-appropriate analysis for prevention and early intervention remains the
backbone of targeting approaches and a number of prospective and retrospective studies’
findings give a valuable insight into the extent of such oral health problem within particular
groups.
2.3. Determinants of Oral Health-related Hospital Admissions
Factors such as age, Indigenous status, socioeconomic status, private health insurance,
accessibility and remoteness influence whether a child attends a dental professional (Kruger
et al., 2005; Slack-Smith, 2003). There is, however, limited information regarding the factors
associated with oral hospital admissions among children.
2.3.1. Age and Gender
Dental conditions in children are almost entirely preventable (Mouradian, Wehr, & Crall,
2000). However, of all hospital admissions requiring general anaesthetics in Western
Australia in 2002–2003, 17% were for dental treatments, among children aged 1–4 years
(Sims et al., 2005). Reports on oral related hospital admissions indicate that the problem of
Early Childhood Caries (ECC) has been ongoing. For example, the rates all oral health-related
hospital admissions are considered to be high (842 and 1635 per 100,000 population in < 12
Chapter Two
22
months old and 1-4 years old children, respectively) (Kruger Dyson, & Tennant, 2006). The
majority of those admissions might attributed to ECC, as it is the most prevalent oral
condition in children aged 4 years or younger (American Academy of Pediatric Dentistry
Clinical Affairs Committee, 2006).
On the other hand, dental hospitalisations requiring general anaesthetics are most common
in school-age children. The rate in those aged 5–9 was 11 per 1,000 persons, with no
differences between males and females (Australian Institute of Health and Welfare, 2014a).
Another study revealed that children aged 13-17 had the highest rate of admissions (19.48
per 1,000 children aged 13-17), followed by those aged 5–12 (9.34 per 1,000 children aged
5-12) (Kruger Dyson, & Tennant, 2006). However, high school aged children admissions
rates are more likely to be attributed to third molar removal than treatment of decayed teeth,
in contrast, children aged 5-12 were more likely to be admitted for caries treatment.
2.3.2. Indigenous Status
In brief, the Australian bureau of Statistics (ABS) (2011) has estimated that the WA
Indigenous population represents around 3.8% of the total WA population and 13.2%
(669,736) of the total Australian Indigenous population (Australian Indigenous
HealthInfoNet, 2015). Higher proportions of Indigenous population were accounted for
children aged less than 15 years were observed compared to older age groups (Australian
Indigenous HealthInfoNet, 2012; 2013).
Indigenous Australians are disadvantaged on almost every health and social indicator
compared to non-Indigenous Australians (Australian Indigenous HealthInfoNet, 2015).
Chapter Two
23
Marked oral health disparities exist between Indigenous and non-Indigenous children in
Australia; with Indigenous children experiencing more caries in their deciduous teeth than
non-Indigenous children (Jamieson, Armfield, & Roberts-Thomson, 2007). Australia-wide,
dental hospitalisations that require general anaesthetics are most common in Indigenous
children aged 5–9 years, followed by children aged 0–4 compared to other age groups
(Australian Institute of Health and Welfare, 2014a). The rate of admissions in those aged 5–
9 was 14.9 per 1,000 Indigenous children aged 5–9 and for those aged 0–4 the rate of
admissions was 10.7 per 1000 years (Australian Institute of Health and Welfare, 2014a). No
significant differences were observed between Indigenous males and females (Australian
Institute of Health and Welfare, 2014a).
In Western Australia, a study investigated dental hospitalisations occurred between 1980-
1995, for all children aged less than 5 years (Slack-Smith et al., 2009). The findings indicated
that Indigenous children were 1.18 times more likely to be admitted than non-Indigenous
children. Other authors reported similar findings elsewhere in Australia. Jamieson et al.
(2006) found that Indigenous children aged less than 5 years had 1.4 times the admission
rate of similarly aged non-Indigenous children (Jamieson & Roberts-Thomson, 2006).
Furthermore, they claimed that Indigenous children living in remote areas had 1.5 times the
admission rate of urban living Indigenous children (Jamieson & Roberts-Thomson, 2006).
However, non-Indigenous children are more likely to be admitted than Indigenous
counterparts. Kruger et al. (2006) estimated that Western Australian non-Indigenous
children were 1.7 times more likely to be admitted than Indigenous children.
Chapter Two
24
The previous findings suggest that although the Indigenous child population has a greater
tendency to have more severe conditions than non-Indigenous counterparts, recent oral
admission trends among Indigenous children, however, indicate limited access toward more
invasive treatment. Therefore, there is an urgent need for the development of strategies
targeting Indigenous children oral health, along with a multifactorial risk factor approach.
2.3.3. Socioeconomic Status
Oral health is strongly linked to the socioeconomic position of individuals, which is reflected
in the patterns of oral disease in Australia (National Advisory Committee on Oral Health,
2004). Access to dental care in Western Australia also has a strong socioeconomic dimension
with disadvantaged people having serious access problems and extensive waiting times
(Kruger & Tennant, 2005; 2006). Several studies revealed different patterns of trends in
demand for dental caries hospital care among different socioeconomic status (SES) groups.
Evidence suggested that avoidable hospital admissions are substantially more common in
low SES children (Blustein Hanson, & Shea, 1998), as those from the lowest SES areas were
more likely to have more untreated decay than children from the highest SES areas
(Australian Institute of Health and Welfare, 2011a). Similarly, a recent New-Zealand analysis
indicated that higher rates of dental preventable hospitalisations in children were among the
most deprived (Whyman, Mahoney, Morrison, & Stanley, 2014).
2.3.4. Accessibility and Remoteness
Remoteness and accessibility are significant factors determining the level of basic health;
higher rates of poor oral health were observed in remote areas (Australian Institute of Health
Chapter Two
25
and Welfare, 2008b). Increasing remoteness has a negative impact oral health, where
environmental or geographical factors such as long distances to access services exist. For
example, in Victoria, avoidable dental hospitalisation rates are higher among rural dwellers,
especially in children younger than 9 years (Department of Human Services, 2007).
However, in Western Australia evidence indicate that hospital admissions do not reflect the
actual burden of the oral conditions. Tennant et al. (2000) found that the hospitalisation
rates for oral conditions (of children younger than 13 years) were higher among those living
in rural areas than metropolitan living counterparts. The trend, however, has been reversed
within the following decade. As in 2006, Kruger et al. (2006) published a 4-year period of
study (from 1999-00 to 2002-03) on oral hospitalisation in WA children and showed a
significant difference between the hospitalisation rates of Western Australian children living
in rural areas (1284.6 per 100,000 population), compared to urban living counterparts
(1391.1 per 100,000) (Kruger Dyson, & Tennant, 2006). Several studies, however, have
examined the oral health status of people attending rural and remote dental clinics (Smith,
Kruger, Dyson, & Tennant, 2007; Kruger et al., 2005; Dogar et al., 2011). The results indicate
that rural living pre-school children are experiencing a higher dmft average.
As Indigenous Australians are more likely to live outside metropolitan areas than non-
Indigenous Australians, the relationship of remoteness to oral health and oral health-related
admissions is particularly important. Some studies examined the rate of oral hospital
admission of Aboriginal children based on location, and found a higher rate of oral hospital
admission among WA Indigenous children living in remote or very remote areas (796.2 per
100,000), compared with urban living children (755 per 100,000) (Kruger Dyson, & Tennant,
2006). In contrast, rural living non-Indigenous children have a high rate of admissions
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26
compared with Indigenous children living in rural area. In rural/urban context, further
analyses of other socioeconomic and demographic variables are essential to ameliorate the
oral prevention approach.
2.3.5. Insurance Status
As previously discussed the percentages of privately-insured Australian children have
declined over the past decade, with only half of the child population insured. It is important
to note that in Australia, dental services are predominately provided in a private sector
setting, and therefore prices and wealth influence access. However, further evidence on the
insurance coverage among various conditions or socioeconomic subgroups does not exist.
2.4. Oral Health Expenditure
Over the last decades the health expenditure growth has largely been driven by increases in
inflation (37%), population growth (14%) and actual increase in expenditure per individual
(48.7%) (Australian Dental Association, 2006b). In the year 2001–02, nearly $3.7 billion was
spent on dental services, representing 5.5% of total health expenditure (Australian Institute
of Health and Welfare, 2003). Much of this was spent on repair and rehabilitation of tissue
destroyed by dental caries and periodontal disease; conditions that are amenable to
prevention through different levels of health measures (US Department of Health and
Human Services, 2000). The expenditure on dental care has risen from $1.9 billion to over
$4.7 billion in 1994–95 and 2004–05, respectively. Through the same period, dental
expenditure’s portion of total health expenditure rises from 3.8% to 5.7% (Australian Dental
Association, 2006b). Moreover, the following trends have been observed during the same
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27
period: State, Territory and Local Governments increase their outlay on dental care to reach
13% of total expenditure in 1999-00, then drop to 8.1% in 2001–02 before growing to 9.9%
in 2004–05 (Australian Dental Association, 2006b). Additionally, private health insurance
rebates continue to decrease. In 1994–95, spending by private health insurance funds
accounted for 28.1% of total dental expenditure. By 2004–05 this figure fell to 13.8%
(Australian Dental Association, 2005; 2006a). Based on an Australian Dental Association
(2006b) report, ‘expenditure by individuals continues to account for the majority share of total
dental expenditure, rising from 58.8% in 1994–95 to 67.3% in 2004–05’ (Australian Dental
Association, 2006b). In 2006, Australian total health expenditure on hospitals increased by
31%, whereas dental services expenditure only grew by 3.5% (Australian Dental
Association, 2006b).
In 2004–05, the WA dental service total outlay was around $52 million (NRHA, 2005; Graham
& Kucera, 2002). The total sector expenditure includes payment for public and SDSs that
provides free dental services to school children. Of the total dental health expenditure, $7.8
million was granted to the Oral Health Centre of Western Australia (OHCWA) to provide
some public dental service, as a governmental initiative to improve access to quality dental
care (NRHA, 2005). With this agreement, ‘the OHCWA provides specialist oral health care to
those eligible for state government subsidised dental care (Health Care Card holders) and
general dental care to eligible patients within their local catchment area’ (Western Australia.
Department of Health, 2007). According to the WA Department of Health annual report
2011–12, OHCWA has treated 8,262 cases in their general practice and more than 38,000
cases in different specialty areas during the period of 2007–2012 (Western Australia.
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28
Department of Health, 2012). Consequently, waiting times and shorter hospitalisation lists
have been diminished which indicate more access to affordable services.
Table 2.2:
A summary of the total oral health Australian budget in ($ million) by source of fund, over
time.
Year Federal
government
direct outlay
State & local
government
Federal
government
premium
rebates
Health
insurance
funds
Individuals Other Total
2005-06 110 600 398 907 4,107 11 6,133
2006- 07 125 583 404 949 4,234 10 6,306
2007-08 235 614 448 983 4,182 10 6,473
2008-09 558 690 440 1,069 4,271 23 7,052
2009-10 768 652 509 1,076 4,737 32 7.775
*Source: Australian Institute of Health and Welfare (2014b) health expenditure data cubes
The latest expenditure figures on dental health show a real growth in most areas, with an
outlay of 7.5% for dental services ($8 million) (Australian Institute of Health and Welfare,
2011b) (Table 2.2). This is an increase of 13% from the total expenditure on dental services
than the previous year. Individuals are considered the largest contributor (61%) to the total
dental expenditure (Australian Institute of Health and Welfare, 2011b) (Table 2.2). The
estimated national average level of regular spending on health was $5,251 per person,
whereas in WA, the health budget has been experienced a 2.3% lower share ($5,128 per
eligible person) than the national average (Australian Institute of Health and Welfare,
2011b) (Table 2.2). Twenty percent of the total expenditure was spent on school-based
programmes (Leeder & Russell, 2007).
The State government is the primary financier of the SDS program to provide equipment,
maintain clinics, and conduct training sessions for school children (Australian Institute of
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29
Health and Welfare, 2006b). Although Australia’s health system is highly ranked on the
medical scale worldwide, refinements are needed in regards to SDS to enable equitable and
efficient care for all Australian children. According to Australian Institute of Health and
Welfare (2006b), in order to improve the condition of the existing SDS clinics, the State
government has to increase this funding (Australian Institute of Health and Welfare, 2006b).
Unfortunately, the majority of those clinics experienced either the lack of essential
equipment, such as computers, or fail to attract new staff due to low wages (Australian
Institute of Health and Welfare, 2006b). Contrary to this, the Australian Dental Association
has identified SDS as an area where more funds from the Federal government are required
(Australian Institute of Health and Welfare, 2006b). The numbers of school aged children
and adolescents have increased over time, and more funds are required for sustainable
dental health provision services. These funds should enable a universal coverage of those
children to access free or subsidised dental care services based on targeting approaches
(Tennant et al., 2000). Targeting approaches work on the principle that some groups of the
population are at greater risk compared with the whole population
(Daly, Batchelor, Treasure, & Watt, 2013).
2.5. Oral Health Status of Australian Children
In this section, an overview of oral health of the most common oral conditions among
Australian children is provided, with a particular focus on Western Australia.
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30
2.5.1. Dental Caries
Dental caries, which also known as dental decay, is the most common oral disease
worldwide. It is characterised by demineralisation (mineral ions loss) of the tooth surface
(enamel). Caries is stimulated largely by the presence and interaction of acid-producing
bacteria, fermentable carbohydrates and many host factors including teeth and saliva (HA et
al., 2011). Normally, saliva induces the growth of dissolved crystals through re-depositing of
lost minerals (remineralisation). However, under some circumstances, imbalance of the
demineralisation/remineralisation process leads to destruction of the hard tissue of the
tooth, which subsequently becomes a favorable place for bacterial growth. This may cause
considerable pain and, if not treated, caries will progress causing pulp inflammation and
pulp death then an abscess may occur and restorations or removal of the tooth may be
required.
2.5.1.1. National Trends
In Australia, oral health measures suggest that significant improvements have occurred over
the last 30 years. However, in Australia, tooth decay is considered the most prevalent dental
problem and is over 5 times more prevalent than Asthma among children (Armfield Slade, &
Spencer, 2007; Australian Bereau of Statisitics, 2009). In the last decade, approximately 8%
of children aged 5–11 years who made a dental visit within the previous year received an
extraction due to severe carious damage (Ellershaw & Spencer, 2009). Children who visited
the dentist for a problem were more than twice as likely to have received an extraction
compared to those who usually visited for a check-up (Ellershaw & Spencer, 2009).
Subsequently, over the last generation, the trends have either plateaued or have begun to
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31
decline. For example, the prevalence and incidence of deciduous caries among 5-year-old
children has been growing by 20% between 1996 and 1999 (Australian Institute of Health
and Welfare, 2014b). Similarly, a gradual increase of permanent teeth caries at age 12 has
occurred since the late 1990s (Australian Institute of Health and Welfare, 2014b).
Table 2.3:
Percentages of children attending a School Dental Service with dmft + DMFT > 0 by age, over
time.
Years
Percentage of dmft + DMFT > 0 by age
5 6 7 8 9 10 11 12
2002 80.5 73.1 63.6 66.7 65.0 48.4 50.4 48.0
2006 42.0 63.0 61.6 67.0 62.0 59.0 62.6 54.0
2009 41.8 52.5 61.1 67.3 66.6 63.8 56.0 54.0
*Source: (Chrisopoulos & Harford, 2013; Chrisopoulos et al., 2011; Armfield et al., 2007)
Table 2.3 shows the change in the proportion of children with caries (dmft + DMFT > 0), over
time. For 5-year-olds children the trend has taken a positive direction toward prevention
with less than half of them experiencing dental caries. This figure, however, might not be
representative of the whole population, as the number of children included in the 2006 and
2009 surveys were far fewer than the number of children examined in the 2002 national
survey. On the other hand, across all other ages, child caries experience has increased over
time. Although the Australian children oral health survey method is widely accepted, there
are several limitations associated with the application of these standards. Difficulties include
their restriction to enrolled school aged children and excluded children younger than 5
years. Therefore, many pre-school children (aged 4 or less) develop very severe and
extensive dental decay which is called ECC or also known as Nursing Bottle Caries. Diets rich
in carbohydrates are the main contributing factors of ECC. Many children with ECC
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32
frequently require hospitalisation for treatment under general anesthetic. Unfortunately,
population-based data about caries experience among children within this age group does
not exist.
Since the oral health care of children younger than 4 is not included in the SDS coverage
scheme, their ECC prevalence is not routinely collected, and not part of the child national oral
health survey. However, studies are replete with evidence suggesting that there has been an
increase in ECC in Australia. Wyne (1999) examined the prevalence of nursing caries among
2 to 3-year-olds pre-school children in Adelaide, South Australia. The results revealed that
the prevalence of ECC among those children was almost 17%, with some requiring
hospitalisation and invasive treatment. In Australia, the mean dmft for 4 year-olds has
gradually increased from 1.10 in 1997 to 1.44 in 1999, 1.64 in 2002 and 1.70 in 2003–2004
(Australian Institute of Health and Welfare, 2004; 2007a). The severe form of ECC affects a
child’s general health, learning ability and future oral health (Horowitz, 1998; Peretz, Ram,
Azo, & Efrat, 2003). Yet, ECC is largely preventable by targeting those in the high risk group.
Table 2.4:
Age-specific average caries experience (dmft) in children attending a School Dental Service,
over time.
Age (Years) Deciduous dentition: average dmft per year
2002 2005 2006 2007 2009
5 1.83 1.74 1.65 1.85 1.80
6 1.96 2.27 2.47 1.95 2.36
7 2.22 2.38 2.40 2.10 2.47
8 2.32 2.40 2.15 2.22 2.54
9 1.98 2.4 1.85 1.89 2.38
10 1.60 1.54 1.24 1.41 1.79
*Source: (Chrisopoulos & Harford, 2013; Mejia et al., 2012; Chrisopoulos et al., 2011; Armfield et al., 2007)
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33
Table 2.4 shows an increase in average dmft over time which displays a similar pattern
across ages. Children aged 6–9 years had the highest dmft score across all ages. Similar to
deciduous dentition, the average DMFT has increased for older age group (> 10 years)
compared to younger age groups (Table 2.5).
Table 2.5:
Age-specific average caries experience (DMFT) in children attending a School Dental Service,
over time.
Age (Years) Permanent dentition: average DMFT per year
2002 2006 2009
5 0.04 0.03 __
6 0.08 0.15 0.08
7 0.28 0.47 0.23
8 0.43 0.38 0.33
9 0.54 0.49 0.52
10 0.65 0.60 0.76
11 0.75 1.20 0.75
12 1.02 1.24 1.05
13 1.37 1.23 1.70
14 1.72 1.73 1.68
*Source: (Chrisopoulos & Harford, 2013; Chrisopoulos et al., 2011; Armfield et al., 2007)
Even the recent Australian national survey showed an increase in the percentages of children
affected by caries. Australian Institute of Health and Welfare published the Child Dental
Health Survey 2014 results. These data showed that the proportion of Australian children’s
dmft, who attend a SDS, has varied from about 48% to 63% for those aged 5 and 9,
respectively (Australian Institute of Health and Welfare, 2014b). Children aged 5 had an
average of 2.32 dmft, those aged 8 had 2.63, and those aged 10 had 1.78 (Australian Institute
of Health and Welfare, 2014b). This variation might be attributed to the fact that children
aged 10 years old have fewer deciduous teeth than their younger counterparts. However,
approximately 50% of children aged 12 had experienced caries in their permanent teeth
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34
(Australian Institute of Health and Welfare, 2014b). On average, 1 in every 10 children aged
12 to 15 years has an extensive history of permanent tooth decay (with between 5.2 and 8.6
permanent teeth affected). Those with very high levels of caries were more than 4 times the
national average of DMFT children of those ages (Australian Institute of Health and Welfare,
2014b). When only permanent teeth DMFT scores are compared by age, it is evident that
children aged 12 are more likely to have higher DMFT scores than their younger
counterparts. Vice versa, when dmft scores for deciduous teeth are compared between the
same age groups, higher rates are observed among those aged 6 or younger than those aged
12 or older. Unanimously, these differences in affected teeth with age are explained by the
increased time that their teeth have been at risk of decay.
Caries experience varied between States and Territories and over time. This variation might
be attributed to factors such as variation in service coverage policies, differences in targeting
practices, and varying levels of access to services. Variations in the severity of caries
experience between States and Territories are represented in the following table (Table 2.6).
Table 2.6:
Comparison of the average caries experience in children based on age and State and
Territory, 2007.
Age
(years)
State and Territory1
NSW Qld WA SA Tas ACT NT Australia
5-6 (dmft) 1.53 2.47 1.51 2.01 2.21 1.37 3.75 1.88
12 (DMFT) 0.75 1.32 0.84 0.93 1.10 0.80 0.74 0.95
*Source: Child dental health survey Australia 2007. (Mejia et al., 2012)
1 New South Wales (NSW), Queensland (Qld), Western Australia (WA), South Australia (SA), Tasmania (Tas), Australian Capital Territory (ACT) and Northern Territory (NT).
Chapter Two
35
Table 2.6 shows that dental caries in deciduous teeth were highest in the Northern Territory
(NT), while the Australian Capital Territory (ACT) had the lowest level of dental caries in
deciduous teeth. Moreover, WA children’s average dmft is lower than the national average.
The table has also shown that DMFT of Queensland 12 year-old children is the highest,
whereas WA reported a mean DMFT of (0.84).
2.5.1.2. Western Australia Trends
Several studies have investigated the Western Australian pre-school children caries
experience. For example, Kruger et al. (2005) assessed caries among a sample of pre-school
children in a rural community. Only 40% of the surveyed sample were caries free, which was
much lower than average figures reported in ‘Child Dental Health Survey’ in Western
Australian. The study also added that the prevalence of severe-ECC (s-ECC) was significantly
higher among Aboriginal compared with non-Aboriginal children. Similar results were found
when Dogar et al. (2011) examined the prevalence and severity of decay in pre-school
children in rural and remote WA and considered some of the factors associated with these
rates. The authors analysed the dental health of 253 children aged between 2 and 4 years
within five rural and remote communities in WA. The findings showed that more than 40%
of these children already had one or more decayed teeth. Of those, 19% had s-ECC and 15%
had already suffered toothache, with Indigenous children experiencing higher burdens than
non-Indigenous counterparts. Additionally, 69% of Indigenous children had decay; of those
34% experienced s-ECC. In contrast, of all non-Indigenous children who had dental decay,
only 25% had s-ECC (Dogar et al., 2011). Another study also confirmed that in some
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36
Indigenous communities, children aged older than 5 years are experiencing up to three times
the prevalence of caries as non-Indigenous children (Christian & Blinkhorn, 2012).
Presented below is a table of trends over the last decade, of caries experience among
Western Australian school aged children living in urban areas weighted by age. Across the
period 2000-2009, caries experience slightly decreased for most age groups, with only 15
year-olds appearing to indicate an increase in caries across this period.
Table 2.7:
Average numbers of decayed, missing or filled teeth (DMFT) for school children living in
metropolitan areas, over time.
Age 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
5 year-old
(dmft)
1.51 1.59 1.54 1.45 1.52 1.45 1.57 1.35 1.44 1.26
8-year-olds 0.37 0.34 0.35 0.30 0.31 0.28 0.30 0.30 0.22 0.27
12-year-olds 0.91 0.84 0.93 0.85 0.85 0.85 0.84 0.89 0.75 0.77
15-year-olds 1.68 1.51 1.57 1.61 1.69 1.49 1.67 1.68 1.69 1.70
Data source: WA Metropolitan Health Service Annual reports of 2005-06 and 2009-10
The pervious table indicates excellent status for dental health among school children in
Western Australia through consistently low DMFT average scores over the past decade.
However, those estimates do not represent the complete Western Australian child
population, as they were only based on that portion of the population that is enrolled in and
under the care of the metropolitan SDS clinic. Consequently, the results cannot be applied to
children who are not enrolled in school and eligible for SDS. It is important to note that
enrolment across Australia varies, but in all States and Territories, it is higher among
primary school aged children than those in high school. Hence, estimates for primary school
children might not differ substantially from those that would be obtained if all children were
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37
surveyed; in contrast, estimates for high school children would differ from those obtained if
all children were surveyed.
Australia-wide, children from less affluent areas still have poorer dental health than other
Australian children. Across all ages, children residing in low socioeconomic areas have
higher DMFT than children residing in the high socioeconomic areas. Additionally, when
dental diseases were compared between children living in metropolitan areas and rural or
remote regions of Australia, differences occur in relation to their social gradient. For
example, in rural and remote areas, the average amount of dental decay was high in children
who lived in the most disadvantaged areas. Children aged 4 years and younger who were
living in rural and remote areas experienced between 25% and 30% more extreme caries
than metropolitan children. Additionally, in urban areas there was a consistent trend of
increasing levels of decay with increasing levels of disadvantage.
In Australia, dental caries was the 5th most common reason for hospital admission for 1 to 4-
year-olds children in 1999–2000. Furthermore, dental conditions accounted for 7% of all
procedures performed in hospital for children aged up to 14 years (Al-Yaman, Bryant, &
Sargeant, 2002). A study by Slack-Smith et al. (2009) described the dental admissions
occurred in WA during 1980-1995 among children aged 4 years or under. Oral hospital
admissions of children less than 5 years accounted for 10,493 admitted cases. Of the total
admissions, 78% were for dental caries, with 62% of those admissions occurred in children
living in urban areas compared to 27% occurred in rural children. Further study using the
same data set investigated the dental admissions among children under the age of 5 years
found that 40% of admissions occurred in Indigenous children aged younger than 2 years
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38
old compared with 10% among non-Indigenous children of the same age (Slack-Smith et al.,
2011). When 3 years of data (1996–1998) were added to the previous analysis, Slack-Smith
et al. (2013) revealed similar dental hospital admission trend on children up to the age of 2
years. The study found that 39% of children were most frequently admitted for dental caries
(Slack-Smith et al., 2013).
More recently, Kruger et al.’s (2006) four year (1999–2003) analysis of oral admission in
children under the age of 18 years found that 28.3% of all admission episodes were for dental
caries. The highest rates of hospital admissions were in the pre-school age children, followed
by primary age school children. Non-Aboriginal pre-school and school-aged children were 2
and 1.4 times, respectively, more likely to be admitted for dental caries than their Aboriginal
counterparts. Although the prevalence of decay was somewhat higher in girls than in boys
(Australian Institute of Health and Welfare, 2014a), no study has confirmed significant
gender differences in children oral admissions.
On the other hand, children from the most deprived areas are experiencing higher decay
levels, as previously discussed, and accordingly it would be assumed that they have higher
service utilisation rates compared to children living in least deprived areas (who are
experienced lower dmft). However, evidence indicated that higher dental caries related-
hospitalisation rates were observed among children living in high SES. Madan et al. (2010)
studied the trend of dental admissions in children aged 0–19 years in relation to their
residential location, hospital service utilisation and their socioeconomic status. Children
living in metropolitan, highly accessible and least deprived areas have higher caries related
hospital admissions than children living in very remote and most deprived areas. Children
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39
living in highly accessible areas were more likely to be admitted for dental decay in a private
hospital than children living in very remote areas.
It is important to describe the current trend of dental decay admissions that occur in children
and to determine their related risk indicators in order to inform population and risk-group
based prevention strategies to minimise the burden of dental caries and other associated
disorders.
2.5.2. Embedded and Impacted Teeth
In case of children aged 14 years and younger, impaction of maxillary permanent canines is
the most frequently encountered clinical problem. Impacted canines are mostly
asymptomatic and its precise cause is unknown. Although, impacted canines are a common
dental anomaly among children as young as 9 years of age, it has the potential to damage the
adjacent teeth. The treatment of such a condition usually requires an interdisciplinary
approach such as surgical exposure of the impacted tooth and the complex orthodontic
treatment, which may lead to various degrees of destruction of the tooth’s supporting
structures (Manne, Gandikota, Juvvadi, Rama, & Anche, 2012); not to mention the long-term
therapy and the financial burden to the patient. Hence, it seems valuable to focus on the
means of early diagnosis and improving the outcome.
The fundamental aspect in the diagnosis and prevention of an impacted maxillary canine is
the ability to recognise and predict its subsequent failure of eruption. Ericson & Kurol (1998)
proposed that early diagnosis of canine displacement, in relation to the surrounding
structures, is primarily based on the radiographic examination (Ericson & Kurol, 1988;
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40
Ericson & Kurol, 1986a). However, it is vital to note that a radiographic examination in
children younger than 9 does not provide a reliable means to determine the future
unfavorable path of eruption of a maxillary canine (Lindauer, Rubenstein, Hang, Andersen,
& Isaacson, 1992). The same authors also studied the outcome of extracting a retained
deciduous canine in 10 to 13 year-old children in relation to the improvement of the
angulation and eruption path of an ectopic canine. The results demonstrated that 78% of
ectopic canines reverted to a normalised path of eruption after early extraction of their
deciduous canine (Ericson & Kurol, 1986a; Ericson & Kurol, 1986b). Therefore, evidence
suggested that early radiographic examination along with geometric measurements by the
age of 9-10 years can provide substantial information on the eruption pattern of a maxillary
canine, thus permitting early detection and proper intervention in order to minimise
invasive and costly hospital treatment of an impaction.
The prevalence of canine impaction in Western Australian children is currently unknown.
Unfortunately, as the SDS routine examination does not include impaction detection
measures, a considerable number of children are hospitalised due to impacted or embedded
teeth, and subsequent to this a massive cost is incurred. The only study to date conducted on
the prevalence of impacted and embedded teeth related to hospital admissions among
Western Australian children is by Kruger et al (2006). The results revealed that of all
admissions between 1999 and 2003, approximately 33% was attributed to embedded and
impacted teeth. About 10% of those admissions (8,797 episodes) occurred among high
school-aged children, with non-Aboriginal children in this age group being 31 times more
likely to be admitted for the removal of impacted teeth than their Aboriginal counterparts
(Kruger at al., 2006). Based on these findings, it appears that the rate of hospital admissions
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41
for impacted teeth removal may be considered as an indicator of service accessibility
(George, Kruger, & Tennant, 2011a). It is important to note that those data were based on
children aged 17 years or less, and a large number of these hospital admissions might be
attributed to wisdom teeth removal. Another study investigated the socioeconomic divide
on hospital based impacted tooth removal among young adults aged 10 years and older
(George, Kruger, & Tennant, 2011b). The results found that a higher socioeconomic group is
4 times more likely to have an impacted tooth removed in a hospital than those individuals
from a lower socioeconomic group. Similarly, individuals living in highly accessible urban
areas were 3 times more likely to be hospitalised for this procedure than those from the rural
areas. However, among children younger than 14 years, where the majority of hospital
admissions for impacted teeth were related to canine removal; evidence on socio-
demographics and economic disparities do not exist.
To overcome and improve this issue of early detection of potentially problematic erupting
teeth, early assessment should be part of the routine examination protocol for the eruption
status of permanent canines for all dental examinations for children in the School Dental
Service. This would necessitate a routine examination via the palpation for the un-erupted
tooth and visual assessment of the child’s dental development from the age of 8. Thus, when
possible canine impaction is suspected further diagnostic tests and referral for a specialist’s
opinion may be required.
2.5.3. Pulp and Periapical Conditions
Pulpal and periapical conditions are quite common, particularly in young children. Despite
the decline in dental caries in past decades, many children are still at risk of dental decay
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42
which allows bacteria to invade the pulp causing pulpal and periapical inflammation or
infections (Robertson & Smith, 2009). In most children, these infections usually present as
chronic inflammation which is localised to the offending tooth. Periapical abscesses are the
most common pulpal and periapical condition. The majority of dental abscesses in paediatric
patients occur secondary to dental caries, trauma, or unusual conditions which challenge
diagnosis and management (Robertson & Smith, 2009). In the primary dentition
management of localised pulpal infections includes root canal treatment, or extraction and
space maintenance (Seow, 2003). In contrast, the treatment for children who show spread
of the dental infection may require invasive hospital care for surgical drainage and removal
of the source of infection and parenterally administered antibiotics (Seow, 2003). In some
cases, extraction of the tooth may be required.
Acute dental abscesses are frequently underestimated in terms of morbidity and mortality.
Several studies have shown that dental abscesses predominantly accounted for a significant
number of oral related hospital admissions in children. In WA, despite a generally dentally
motivated population, a large retrospective study reported that 1,881 of paediatric patients
sought treatment for pulpal and periapical conditions over a 4-year period (Kruger Dyson, &
Tennant, 2006). Furthermore, the majority of those hospital admissions occurred among
pre-school aged children, with Indigenous children incurring the highest rates. The
treatment cost of those admissions was $2.4 million AUD. Another study examined the rate
of cellulitis-related hospital admissions in WA, as a measure of the extreme level of dental
disease at a population level (Anjrini, Kruger, & Tennant, 2014). This critical condition,
which develops as a result of caries-pulp necrosis, mainly occurs in pre-school age children
(Anjrini et al., 2014). An earlier study also revealed similar findings, suggesting that the high
Chapter Two
43
rates of hospital admissions among Aboriginal infants were mainly due to cellulitis,
lymphadenitis and stomatitis conditions (Tennant et al., 2000). Those results provided an
indicator of disease burden and the general dental service capability. Another study by Wang
et al. (2005) analysed a 5-year retrospective data of odontogenic maxillofacial infections in
children in a large urban public hospital. It was estimated that 1 per 2600 admissions was
accounted for by acute dental infections (Wang et al., 2005). In the USA, 47% of all dental-
related attendances at paediatric emergency rooms were for periapical abscesses (Graham,
Webb, & Seale, 2000).
Pulpal and periapical infections have significant implications on patient morbidity and
burdens on health care systems. Further detailed analyses are needed to mitigate the risk
indicators that can lead to pulpal and periapical conditions among different Australian child
population subgroups.
2.5.4. Other Conditions
Although oral conditions such as oral cancer, periodontal diseases, oral cysts, birth defect
and dento-facial anomalies are rare in children, evidence suggests that an increasing number
of cases have been reported over years.
2.5.4.1. Oral Cancer
Cancer is a complex disease in terms of diagnosis and treatment, and represents a significant
burden on both individual and community levels and the health system. Despite the fact that
most studies of oral cancer in Australia have been restricted to the adult age group, childhood
cancer is the leading disease-related cause of death among Australian children (Government
Chapter Two
44
of Western Australia. Department of Health, 2011). However, the risk indicators, incidence
and outcomes of oral cancer have not been systematically investigated. Therefore, the actual
extent and impact of cancer among children is probably underestimated.
2.5.4.2. Periodontal Conditions
Children rarely develop severe forms of periodontal disease; however, gingivitis is relatively
common among older children, especially in the Indigenous population. While gingivitis in
itself does not cause destruction of periodontal structures, its inflammation may increases
the likelihood of developing dental or root caries. In 2011, Williams et al. reviewed the oral
health of the Indigenous population. The study revealed that the level of gingival bleeding
was four times more likely to occur among 5 year-old Indigenous children than their non-
Indigenous counterparts (Williams et al., 2011). Similarly, almost half (48%) of 12 year-old
Indigenous children had gingival bleeding compared with 23% of non-Indigenous children
(Williams et al., 2011). In a rural context, 3-in-5 (60%) of Indigenous children living in
remote communities showed some evidence of gingivitis, and approximately one in every
five (20%) of children were at moderate risk of developing gingivitis (Williams et al., 2011).
In Australia, many studies suggested that the number of children receiving periodontal
preventive care has significantly declined over time. For instance, 47% of children aged 5–
11 years had received a professional scale and clean within the previous 12 months
(Ellershaw& Spencer, 2009). This figure has been decreased by 13% in 2005 (Ellershaw&
Spencer, 2009). This decline was particularly evident among uninsured children, rural and
remote living children (Ellershaw& Spencer, 2009). No up-to-date data have demonstrated
the extent of periodontal-related hospital admissions in Australian children.
Chapter Two
45
2.5.4.3. Oral Cysts
A cyst is a pathological cavity filled with fluid, semi-fluid or gas. Kalaskae et al. (2007)
investigated the most common bony lesions of the jaws in children. They found that of all the
epithelium-lined jaw cysts, Dentigerous cysts, which associated with the crown of an erupted
or partially erupted tooth, accounted for approximately 20-24% of cases (Kalaskar, Tiku, &
Damle, 2007). A preliminary study by Manor et al. (2012) showed that the most common
cystic lesions of the jaws in children aged 11 and 4 years were Dentigerous cysts (44%) and
Eruption cysts (21%), respectively. However, Traumatic bone cysts (18%), and Radicular
cysts (17%) were more common in 14 and 8 year-old children, respectively (Manor et al.,
2012). However, no statistically significant data have been reported among Australian
children on the incidence of oral cysts.
2.5.4.4. Birth Defects and Dento-facial Anomalies
Of all congenital anomalies, Orofacial clefts (OFCs) are the most prevalent. Children born
with OFCs have difficulty in feeding, with speech, hearing, and their often disfigured
appearance may lead to chronic adverse health and developmental outcomes. The treatment
of such conditions needs a multidisciplinary complex care from birth to adulthood. This
includes hospital admission for surgery, speech therapy, general dentistry, and orthodontics.
Mossey et al. (2009) observed a higher morbidity and mortality among children born with
OFCs when compared with healthy populations.
In Western Australia, 1 in every 20 babies (approximately 6%) is born with a developmental
anomaly (Abeywardana & Sullivan, 2008). This condition contributes to ongoing childhood
Chapter Two
46
health problems, disability and mortality. A study by Bell et al (2013) aimed to describe the
epidemiology of OFCs during the period of 1980 to 2009, among Western Australian
children. The results revealed that high prevalence rates of OFCs; Cleft Lip ± Palate 12.05 per
10,000; Cleft Palate only 10.12 per 10,000, compared with most other parts of the world (Bell
et al., 2013). The study has also identified some congenital deformities’ external variables
other than those of genetic origin in order to determine the risk indicators in Western
Australian children. For cleft lip and palate (CLP), rates were significantly 1.62 times higher
in males than females, while the prevalence rate of cleft palate only (CPO) is 1.31 times
higher in females than for males. The prevalence of CLP and CPO were 1.89, 1.30 times
higher, respectively, in non-Aboriginal Australians than for Aboriginal Australians.
Generally, the prevalence of OFC did not differ by geographic location or by socioeconomic
status (Bell et al., 2013).
Kruger et al. (2006), reported that, of all hospital admissions between 1999–2003; 4.1%
were attributed to congenital deformities among children, with an estimated cost of $3
million AUD. Both non-Aboriginal and Aboriginal infant groups had higher rates of admission
(584.3 and 454.4 (p<0.05)), respectively. The same authors also examined the demographics
of in-patient dento-facial anomalies among children. Over a 4-year period, 1,616 admissions
were for dento-facial anomalies, with an estimated cost of $2.4 million AUD. The majority of
those admissions occurred among high school aged children. Of this age group, non-
Aboriginal children were 32 times more likely to be admitted than their Aboriginal
counterparts.
Chapter Two
47
It is necessary to monitor the prevalence of OFCs in order to provide valuable insight
information regarding the potential causes, in order to prevent and quantify the burden of
disease and the subsequent management via the most appropriate health service.
2.5.4.5. Dental Trauma and Dental Fractures
Dental trauma is an injury to the teeth and/or oral cavity caused by a sudden accident and
often requires emergency attention. Dental trauma and dental fractures are more common
among children and teenagers, and is not limited to people’s poor health. Costs to the injured
individual and to the community can be substantial (Bastone, Freer, & McNamara, 2000).
Stockwell (1988) conducted a prospective study that determined the annual incidence of
trauma to the anterior permanent teeth. The study comprised of 66,500 children aged 6–12
years enrolled and treated in the Western Australian School Dental Service. Of the children
suffering trauma in one year, the incidence per 100 erupted teeth was almost 12 (Stockwell,
1988). Approximately 81% of children traumatised one tooth only per incident, but 35% of
all teeth that were traumatised involved trauma to two or more teeth (Stockwell, 1988). The
majority of all traumatised teeth were central incisors, with females being more likely to
receive trauma to their maxillary teeth than males (Sctockwell, 1988).
In a rural context, Lam et al. (2008) analysed six years of retrospective data to investigate
the prevalence, causes and presentation of dental trauma in a large rural centre in Western
Australia. The majority of injuries (76%) occurred among children and adolescents,
specifically the 0–4 year age group (30%) followed by the 5–9 year age (23%) and 10–14
year age groups (22%). Trauma mainly occurred due to falls, accidents while playing and
participating in sports activities.
Chapter Two
48
Kruger et al. (2006) attempted an analysis of all jaw fracture-related hospital admissions in
Western Australia from 1999 to 2003. More than 90% of fractures occurred between the
ages of 10 and 50 years with Indigenous people (especially the males) carrying the highest
burden of disease associated with jaw fractures (Kruger, Smith, & Tennant, 2006).
Indigenous people aged 0-19 years were 6.4 times more likely to be admitted for jaw
fractures than their non-Indigenous counterparts (Kruger Smith, & Tennant, 2006).
Regardless of the age, fractures rates were significantly (2.4 times) higher in rural areas than
in metropolitan areas. Additionally, the hospitalisation rate of fractures was 3.6 times higher
in very remote areas than in highly accessible areas. Over a 4-year period, the economic
impact of fracture-related hospital admissions is evidenced by the cost of more than US$ 7.6
million (Kruger Smith, & Tennant, 2006). Currently there is a paucity of data on the analysis
of dental trauma-related hospital admissions and associated variables among Australian
children.
2.6. Oral Health Cost
While dental health has been eliminated from the Australian Government’s health scheme,
(Medicare), considerable suffering arises especially among most deprived families. Massive
impacts were observed among low income and marginalised groups who identify the
financial barriers as a leading cause of not seeking help with dental problems. Therefore, oral
health becomes the second-most expensive disease burden group in Australia. In particular,
dental caries is the second most costly diet-related disease, with an economic impact
comparable with that of heart disease and diabetes (Australian Institute of Health and
Welfare, 2004). Rogers (2011) noted that, in 2004, the treatment costs of over $6 billion
annually, with additional care costs exceeding a further $1 billion. Additionally, when
Chapter Two
49
outpatient and inpatient dental treatment costs are combined with pharmaceutical costs, a
total of $500 million was spent in Australia, during 2004-05 (Richardson et al., 2011). Leeder
et al. (2007) found that the dental treatment cost for GP services ranged from $245–$350
million (Leeder & Russell, 2007). In addition, a total of $2 billion was spent, when combining
the total direct costs and lost productivity (Leeder & Russell, 2007). More specifically, the
WA Department of Health (2010) estimated the actual cost spent per capita of metropolitan
public health units over the last decade: the actual costs exceeded the target cost by 17-23%
each year (WA Metropolitan Health Service, 2010).
In general, the cost of dental health includes:
1. Direct costs arising from:
Dental care by oral health professionals
Dental care by dental health workers such as therapists or hygienists.
Treatment of oral health-induced illnesses such as periodontitis induced by ischemic
heart disease.
2. Indirect costs (lost productivity) arising from:
Time loss from the work and from school for dental treatment
Time loss attributable to oral conditions.
It is important to note that the Australian Government provides funds to support various
public health programmes addressing children with poor oral health. For example, the
Government has been actively funding various oral health screening programmes which
particularly focus on children for oral diseases (Merrick et al., 2012). Yet, the Government is
not entirely responsible for funding the hospital costs of children with oral health problems
(Barraclough & Gardner, 2007). Besides that, the majority of dentists are in private practice;
Chapter Two
50
consequently most hospitalisations concerning oral problems for children take place in
private hospitals (Kruger Dyson, & Tennant, 2006; Australian Institute of Health and
Welfare, 2010). Accordingly, parents are forced to pay the higher proportion of
hospitalisation costs directly out of pocket or indirectly through private health insurance for
the hospitalisation process. The Australian Government meets the operational costs of these
hospitals, thus leaving parents to pay the admission and treatment fees.
Tennant et al. (2000) affirms how expensive oral health-care for Western Australian children
is, by stating that in 1995, approximately AUD $111 million was used for the hospitalisation
of children under 18 years of age. In WA during 1999- 2000 and 2002-03, Kruger et al
conducted a study on 26,497 children to estimate the cost of avoidable oral related hospital
admissions (Kruger Dyson, & Tennant, 2006). Those admissions cost the State more than
$40 million, with the majority of cases were for impacted teeth extractions or dental caries
(Kruger Dyson, & Tennant, 2006). The analysis also showed that the State spent AUD $7.8
million on pulpal and periapical, dento-facial anomalies and birth trauma conditions
combined. Based on a National Health and Hospital Reform Commission (2009) report in
improving oral health and access to dental care, 50,000 persons were accounted for
preventable dental hospital admissions, in 2004–05 (National Health and Hospitals Reform
Commission, 2009). In 2010, the average annual oral health-related admissions direct cost
was AUD $223 million, with an average cost of AUD $4,471 per admission (Commonwealth
of Australia, 2010). Richardson et al. (2011) also noted that of those hospital admissions,
surgical treatment of dental problems including dental extractions cost the nation
approximately AUD $100 million. In contrast, for the same period, hospital treatment of
dental caries conditions only cost the nation about AUD $9.5 million (Victorian Oral Health
Chapter Two
51
Alliance, 2010). It has also noted that dental admissions are the largest category of acute
preventable hospital admissions and that oral health problems are the second-most
expensive disease group in Australia, with direct treatment costs of over AUD $6 billion
annually, and additional care costs exceeding a further AUD $1 billion (Rogers, 2011).
The economic costs of poor oral health go well beyond the health care budget, in terms of
lost productivity and absenteeism from school and work. In Australia, oral conditions cause
an estimated loss of 1,000,000 days of work per year (Australian Institute of Health and
Welfare, 2007). Additionally, Jackson, Vann, Kotch, Pahel & Lee (2011) determined the
relationship between children’s oral health status and school attendance. Children with poor
oral health were almost 3 times more likely to miss school as a result of dental pain than
their counterparts (Jackson et al., 2011).
There is a broad general consensus that indirect economic costs or loss of productivity costs
due to dental health care are more likely to be higher than the treatment cost itself. The
Commonwealth of Australia (2010) estimated the mean cost per hospital admission is
$4,471 plus avoidable productivity losses of $660 million arising from work days lost (Gift
Reisine, & Larach, 1992). A considerable portion of the cost of adult productivity loss is
attributed to their children’s hospitalisations. As in all circumstances, at least one parent or
a guardian must accompany their child during his/her admission, which results in an
additional time loss from both education and workforce. Other studies involving direct and
indirect costs estimated that avoidable dental treatment expenses could be as high as $2
billion (Leeder & Russell, 2007). These indirect dental health economic expenses could be
mainly avoided through better access to universal preventive dental services.
Chapter Two
52
The distinctions are essential, as the dental health workers treatment cost is offset by the
benefit of avoided illness. However, it is important to note that adequate dental care could
reduce the dental professional’s higher treatment costs. Furthermore, increased access to
SDS and preventive services would relieve pressure on hospitals and hospital waiting lists.
Therefore, to enable the community to have timely access to preventively focused dental care
that meets the minimum standard benchmarks for preventable oral health service provision,
increased funding is needed to those services. To date, there are no good data to indicate the
cost of oral health-related hospital admissions based on different variables in WA.
2.7. Recommendations and Conclusion
The impact of poor oral health is massive on both individuals and the community. In
Australia, dental care is provided by a mix of private and public services, with the latter
limited to provision of a safety net service for enrolled school age children. The majority of
School Dental Services in Western Australia remain funded by the State. Any treatments
outside the scope of SDS are referred to private practices or hospital clinics. Complex
interventions such as that provided by hospitals are funded by private sources (health
insurance funds and individuals).
Although the oral health of children has improved considerably over the past 30 years,
consequently, over the last generation, the trends of most oral conditions have either
plateaued or have begun to decline. Previous discussion indicated that hospital admissions
for most caries and other avoidable oral conditions are concentrated on a minority of
children. This has created an incentive to pursue risk identification and management
strategies to improve the effectiveness and efficiency of preventive dental care. Data on
Chapter Two
53
avoidable hospitalisations are increasingly used internationally as an indicator of access to
primary care and its effectiveness, and as a measure of the potential health gains from
primary care interventions. Thus, analyses of avoidable dental hospitalisations is necessary
to identify groups within the population at higher risk for hospital admissions, as well as
identifying time trends in hospitalisation rates against a background of rapidly changing
demographics. Useful population sub-group risk predictors need to be correlated with a
framework to target at-risk groups. Such predictors need to be based on relevant and reliable
data such as population based studies. Interestingly, no published study has modelled
children oral health-related hospital admission rates and their socioeconomic position in
relation to oral health services at a community level.
This chapter has pointed out the importance of preventing costly in-patient treatment, by
early detection, prevention, and implementing culturally-appropriate intervention. Though,
at a time when public health resources are limited, strategies need to be developed to focus
on high risk groups through best practice principles of care and demand management to
better utilise limited health resources. It is also important to address the need for the
redistribution of resources on the basis of regional need and the development of community-
based preventive framework, which will have a significant impact on reducing the incidence
of oral diseases among Australian children. This thesis will explore and attempt to resolve
some of the issues highlighted above through extensive analysis of data from Western
Australian child oral health-related hospital admissions. To this end, in the following chapter,
the specific aims of this thesis are outlined.
54
Chapter Three
3. Aims of the study and Hypotheses
Chapter Three
55
3.1. Aims and Hypotheses Given the background and the questions raised in the previous chapter, there are five
primary aims of this study, and the specific hypotheses are stated below. In the chapters that
follow, chapters Five to Nine, each of these aims are addressed individually and relevant
hypotheses restated.
1) Aim: To analyse a decade of dental admission patterns in Western Australian
children under the age of 15 years, examining associations with socio-demographic
characteristics and with particular focus on dental decay and Indigenous children.
Hypothesis: The hospital admissions for dental reasons (in children) are not
associated with socio-demographic characteristics.
2) Aim: This study examines the disparities in dental insurance coverage among
Western Australian children hospitalised due to oral health-related conditions and
associated factors to address the inequalities that currently exist.
Hypothesis: The children hospital admissions for dental conditions are not
associated with the presence of private health insurance.
.
3) Aim: To analyse the economic cost of a decade of dental hospital admissions in
Western Australian children under the age of 15 years, and to identify socio-
demographic characteristics associated with these costs.
Chapter Three
56
Hypothesis: The hospital admissions for dental reasons (in children) are not
associated with an increased economic burden on Australian dental health
expenditure.
4) Aim: To analyse projected oral-health related admission rates of Western Australian
children, with a particular focus on dental caries, embedded and impacted teeth, and
pulp and periapical conditions through to the year 2026, based on 10 years of past
hospitalisation data for robustness.
Hypothesis: The trend of oral hospital admissions is expected to plateau or head in
to positive direction.
5) Aim: The aim of this study was to identify and prioritise areas of high need for dental
services among the child population in metropolitan Western Australia. Central to
the derivation of identified priority areas was oral health related hospitalisation data
of all children over a ten year period.
Hypothesis: The trend in demand to primary oral health services would reflect
differences in demand to oral hospital treatment in relation to socioeconomic
perspective.
57
Chapter Four
4. Material and Methods
Chapter Four
58
4.1. Material
The following chapters detail analyses of de-identified hospitalisation data obtained from
the WA Hospital Morbidity Dataset (HMDS) for 10 financial years from 1999/2000 to
2008/09. This thesis has been conducted in full accordance with the World Medical
Association Declaration of Helsinki, and ethics approval was granted by the Ethics
Committee of The University of Western Australia (Ethics approval number RA/4/1/5502).
Children were not directly involved in the study, as this was an analysis of de-identified
hospitalisation data, as provided by the Health Department of Western Australia.
Principal diagnosis: Principal diagnosis, classified by the International Classification of
Diseases Tenth-Australian Modification (ICD-10AM) system, was obtained for every child
under the age of 15 years diagnosed and accordingly admitted for an oral health condition
from all private and public hospitals in Western Australia for the 10-year study period. The
principal diagnosis was determined by a clinician for each admission based on the primary
condition under treatment. All principal diagnoses of oral health conditions (ICD-10AM)
were included in the analysis which is the standard classification scheme now used for
reporting diagnoses in all hospital statistical collections, including the National Minimum
Data Set and the Hospital Casemix Protocol’ (Commonwealth Department of Health and Aged
Care, 1998).
Chapter Four
59
4.2. Methods
4.2.1. Study Population
The total child population in Western Australia was 399,889 in 1999, 404,211 in 2005 and
438,576 in 2009. In 2009, 5.9% of the WA child population were of Indigenous descent, and
94% of non-Indigenous child population resided in Metropolitan Perth (Australian Bereau
of Statisitics, 2006).
4.2.2. The Data Source
Between 2000 and 2009, a total of 43,937 children (0–14 years) were hospitalised due to
oral conditions. Of these 94 % (n=41,475) accounted for seven major categories of oral
conditions with half (50%) of those hospitalisations for ‘dental caries’, followed by,
‘embedded and impacted teeth’ (14%), ‘pulp and periapical’ tissue conditions (11%),
‘developmental and birth defects’ (5%), ‘dental fractures’ (5%) and ‘dentofacial anomalies’
4%. The remaining 6% were distributed across all other oral conditions.
Self-reported Indigenous status was used to compare Indigenous to non-Indigenous
populations. Overall 5% (n = 2119) of admissions were for Indigenous children.
For each child, age, gender and Indigenous status, insurance status, residential area and
hospital type were also included in the data set. The following table indicated the
percentages of hospital admissions of those demographic variables in the data set.
Chapter Four
60
Table 4.1.
The percentages of hospital admissions of those demographic variables in the data set.
Variables Raw Number of
admissions (N)
Percentages of hospital
admissions (%)
All children 43,937 100
Age
0–4 16367 37.3
5–9 15862 36.1
10–14 11708 26.6
Indigenous
status
Indigenous 2119 4.8
Non-Indigenous 21209 95.2
Gender
Male 22728 51.7
Female 21209 48.3
Insurance
status
Insured 23134 52.7
Uninsured 20803 47.3
Hospital type
Public 17303 39.4
Private 26591 60.5
Commonwealth 43 1
Residential
area
Rural 6525 14.9
Metropolitan 37412 85.1
Place of residency. Place of residency at the time of admission and the geographical
classification was categorised according to the Accessibility/Remoteness Index of Australia
(ARIA) which measures ‘remoteness in terms of access along the road network from populated
localities to each of five categories of Service Centre. Localities that are more remote have less
access to service centres; those that are less remote have greater access to service centres’
(Australian Population and Migration Research Centre, 2013). ARIA is grouped in to 5
categories: highly accessible; accessible; moderately accessible; remote; and very remote
(Commonwealth Department of Health and Aged Care, 2001).
Socioeconomic status. The population Census provides data on the income, housing,
education, employment, family structure, disability, transport, age, gender and ethnicity of
people all over Australia. The ABS has combined these in a set of indicators called the Socio-
Chapter Four
61
Economic Indexes for Areas (SEIFA) which give a summary measure of socioeconomic status
for people living in specific geographic regions in Australia. Socioeconomic status was
analysed using the (SEIFA) index which is developed by the ABS that ‘ranks areas in Australia
according to relative socioeconomic advantage and disadvantage. The indexes are based on
information from the five-yearly Census’ (Australian Bereau of Statisitics, 2013a). Then the
ranking are grouped into five categories: most disadvantaged, below average disadvantaged,
average disadvantaged, above average disadvantage and least disadvantage (Australian
Bereau of Statisitics, 2013a).
Determination of direct cost. Across Australia, the Australian Refined Diagnosis Related
Group (AR-DRG) is used to calculate the cost of each patient episode on the basis of actual
data about the treatment process. AR-DRG ‘is an Australian admitted patient classification
system which provides a clinically meaningful way of relating the number and type of patients
treated in a hospital (that is, its casemix) to the resources required by the hospital’. Each AR-
DRG represents ‘a class of patients with similar clinical conditions requiring similar hospital
services’ (Australian Institute of Health and Welfare, 2013b). The categorisation classifies
‘acute admitted patient episodes of care into groups with similar conditions and similar usage
of hospital resources, using information in the hospital morbidity record such as the diagnoses,
procedures and demographic characteristics of the patient’ (Australian Institute of Health and
Welfare, 2013b). It is considered that Australia is a model example of a mature costing
system and has the most sophisticated approach according to cost guidelines which include
the actual amount of resources used in the treatment of a particular patient (Raulinajtys-
Grzybek, 2014). Therefore, AR-DRG version 5.1 was used to calculate the direct cost (the
Australian dollar value used according to the year of admission).
Chapter Four
62
Indirect Cost. Based on a previous study, indirect costs were predicted at approximately 1.5
times the direct cost (Drummond, Sculpher, O'Brain, Stoddart, & Torrance, 1997). Indirect
costs include the following: patient and parents’/guardians’ absence from school or work
due to pain and discomfort or having to accompany the child; cost of transportation and
accommodation and societal losses of productivity.
4.3. Projection Methods
Age and residential area for each child were analysed. Future predictions for dental caries
embedded and impacted teeth, and pulp and periapical conditions, which accounted for 75%
of all hospitalised conditions during the study period, were also analysed.
All projections used in (Chapter 8) were based on age specific and Age Adjusted Rates (AAR)
which were calculated using the Health Statistics Calculator, a software package developed
by the Health Department of Western Australia. In the context of projections, two separate
methods were used to project future cases. Both methods accounted for the projected
increase in both the population and the incidence of these conditions, with time using a ten
years of data. The first method, the linear method, used the historical data to estimate a line
of best fit for each 5-year age group, using the method of least squares. Based on the
estimated AAR, the future number of cases was determined. The second method, the
Exponentially Weighted Moving Average (EWMA) also uses historical trends to model future
points equally, this method places greater weight on more recent data. Applying the two
methods separately, resulted in very similar trends, therefore only the results of the linear
method were presented. There is a general consensus among statisticians that a relatively
simple linear model of age-specific rates provides a good fit to the data while giving
Chapter Four
63
reasonably accurate predictions over a short to medium time span (Australian Bereau of
Statisitics, 2014a). The accepted approach among statisticians preparing projections of this
nature is to assume a linear model for increasing rates to prevent projecting admission rates
below zero. Further, there is a fundamental presumption in this approach that the factors
that affect oral related admissions, such as, risk indicators, change in an approximately linear
way with time for each age group (Australian Bereau of Statisitics, 2014a). This presumption
holds on condition that there are no major quantitative changes in any underlying factors,
such as the introduction of an intervention program.
Cost Projections. The DRG cost were categorised into (Low cost ($0-$4000), Middle ($4001-
$10,000), high ($10,001-$20,000) and extremely high ($20,001 and over)). The low cost
category was most representative of the overall cost distribution which was normally
distributed. Therefore, low cost was deemed appropriate to use in future cost projection.
4.4. Developing Framework Maps
To identify the possible gaps in primary dental service provision to children, data from
Western Australia was used. WA occupies the western third of the Australian continent,
comprising a land area of about 2.5 million square kilometers with a population of about half
a million children aged younger than 15 years (Fig. 4.1; Australian Bereau of Statisitics,
2014b). Of those, 19% live in the city of Perth, the capital of WA (Australian Bereau of
Statisitics, 2011). The Perth metropolitan area was used for this study as most (73%) of all
hospital admissions for children under age 15 occurred in the metro area. The existing SDS
in WA is a universal coverage model, providing free primary dental care to all school
registered children who choose to enroll in the service. Despite being a universally applied
Chapter Four
64
system however, it reaches a little less than 30 percent of all children (Government of
Western Australia, 2008a). Some parents who choose to not enroll their children can access
private dental services, but this is not an affordable or accessible option for many. Since
2000, SDS coverage has been declining rapidly, and more children are hospitalised for
preventable oral related conditions (Spencer, 2012). Against this backdrop it is important
that reliable methods are used to determine the distribution of demand for SDS clinics, in
order to enable policy development and service planning. To date there has been no attempt
to determine the distribution of demand for primary service (in this case SDS clinics), in
order to enable policy development and service planning.
Primary places of residency at the time of hospitalisation were analysed using Statistical
Local Area (SLA) which is ‘an Australian Standard Geographical Classification (ASGC) defined
area’ developed by the Australian Bureau of Statistics (Australian Bereau of Statisitics,
2011). SLAs cover the whole of Australia without gaps or overlaps, and there are a total of
37 SLA’s in WA (Australian Bereau of Statisitics, 2011). Boundary files for each SLA were
obtained from the Australian Bureau of Statistics (ABS) website (2012b). Age Adjusted Rates
(AAR) of child hospital admissions per SLA were calculated using the Health Statistics
Calculator of every child aged between 0–14 years old at the time of hospitalisation. In rate
calculations, population data (denominators) was obtained from estimations by the Health
Department of Western Australia, which is based on Australian Bureau of Statistics census
data.
Based on these admission rates per SLA, the entire child population was categorised into five
quintiles of even size, this was done separately for each age group.
Chapter Four
65
Figure 4.1.
Map of Western Australia (Government of Western Australia, 2015)
Census Collection District (CD). Admission data for each child was available on SLA level, but
for higher accuracy and precision analysis, smaller area-based analysis was needed, and
therefore census Collection Districts (CD’s) were used. A CD is much smaller than an SLA,
and is a quasi-measure of density of residents (based on an area that a single census officer
can collect data from). Each SLA contains a number of CD’s. The Perth metropolitan area
covers 2840 CDs, representing 65% of the Western Australia CDs, with a total child
population aged 14 years and younger of more than 270,000 children. Census collection
districts and the geographic boundaries of each CD were obtained from the ABS webpage
Chapter Four
66
(2013). Each CD was linked geographically to its SLA. Hospitalisation data across each of the
37 SLAs was distributed by age groups (0–4 years, 5–9 years and 10–14 years), the rates of
child hospitalisations was calculated for each SLA, and this rate was applied to each of the
CD’s within that specific SLA. This resulted in a hospitalisation rate for each age category, for
each CD.
Population data. Number of children aged under 15 years for each CD were obtained from
the ABS (2006) census data (Australian Bereau of Statisitics, 2013b).
Socioeconomic status. Each CD in Australia has a SEIFA score [Socio-Economic Indexes of
Area (SEIFA 2006)] score assigned to it by the ABS, based on certain socioeconomic
indicators of the population within that CD (Australian Bereau of Statisitics, 2013a). SEIFA is
a nationally accepted coding system developed by the ABS which ‘ranks areas in Australia
according to relative socioeconomic advantage and disadvantage based on information from
the 5-yearly Census’ (Australian Bereau of Statisitics, 2013a). These rankings were
dichotomised into most disadvantaged areas (Poorest, SEIFA deciles 1 to 5) and least
disadvantaged areas (Wealthiest, SEIFA deciles 6 to 10).
School Dental Service locations. The addresses of all fixed SDS clinics were obtained from the
Department of Health website (Australian Bereau of Statisitics, 2011) and geocoded, i.e.
changed into map coordinates, and each located on a map. The SDS clinics were identified as
points of provision of primary dental services and the populations of children who lived
within 2km of a SDS clinic were identified.
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67
Geographic information systems (GIS) in this study was used as a technique for integrating
hospitalisation data related to dental disease with known risk indicators (e.g.
socioeconomics), in order to identify and prioritise geographic areas of high need for a dental
service. The approach using GIS was tested on one city but is designed to be universally
applicable.
The numbers of child hospital admissions, numbers of children under age 15 years, and the
SEIFA score of each CD were geocoded. Fixed service (School Dental Service) locations were
geocoded. The resultant maps indicated where SDS clinics were located, as well as the
following attributes of the child population both within and outside of a 2km zone around it:
population density, age-specific hospital admission rates and an indication of area
socioeconomic disadvantage.
4.5. Statistical Analysis
Age-adjusted rates (AAR) were calculated using the Health Statistics Calculator, a software
package developed by the Health Department of Western Australia. It should be noted that
the data for this study span the years 1999/00–2008/09. In rate calculations, population
data (denominators) were obtained from estimations by the Health Department of Western
Australia Bureau of Statistics. These estimations were based on population data as obtained
by Australian Bureau of Statistics of 2006 Census Surveys. Age specific rates can only be
calculated for age, gender, Indigenous status, rurality and SLA. Significant differences
between rates were based on non-overlapping 95% confidence intervals (P <0.05).
All statistical analyses were conducted using the SPSS 21 for Windows (Statistical package
for the Social Sciences; SPSS, Chicago, IL USA) software, unless stated otherwise.
Chapter Four
68
Comparisons between variables were carried out using univariate, bivariate and
multivariate analyses to determine which primary determinant had a significant impact on
the outcome variable. Chi-square (χ²) tests were used to establish any statistical significant
differences between nominal (categorical) variables. In all statistical tests, significance levels
were set at 95% with P < 0.05 deemed to be significant. However, to determine significant
differences between continuous variable and nominal (categorical) variables, Kruskal-Wallis
tests were used when appropriate. Significant levels were set at 95% with a p value less than
0.05 considered to be statistically significant.
All mapping and geocoding of data used QGIS v.2.6 (Boston, USA), analyses used SPSS 21 for
Windows and data were tabulated in Excel 2007.
69
Chapter Five
5. Dental Hospitalisation Trends in Western
Australian Children under the Age of 15 Years: A
Decade of Population-based Study.
This chapter was published in the following article:
Alsharif, Alla, Kruger, Estie & Tennant, Marc. (2014). Dental hospitalization trends in
Western Australian children under the age of 15 years: a decade of population-based
study. International Journal Paediatric Dentistry. 25(1), 35-42. (Appendix B)
Chapter Five
70
5.1. Abstract
Objective: This study analysed a decade of dental admission patterns in Western
Australian children under the age of 15 years, examining associations with
sociodemographic characteristics and with particular focus on dental decay and
Indigenous children.
Material and Methods: This retrospective study analysed the data obtained for 43,937
child patients under the age of 15 years hospitalised for an oral-health related condition,
as determined by principal diagnosis (ICD-10AM). Primary place of residency, age,
gender, insurance status and Indigenous status were also analysed.
Results: ‘Dental caries’ and ‘embedded and impacted teeth’ were the most common
reasons for hospitalisation among children under the age of 15 years. ‘Dental caries’ were
most common in non-Indigenous patients, with ‘pulp and periapical’ most prevalent in
Indigenous patients. The age-adjusted rate (AAR) of hospitalisation for Indigenous
children in the last decade increased to reach that of non-Indigenous children in 2009.
Total DRG costs of hospitalisation, both public and private, were in excess of AUS $92
million over 10 years.
Recommendations and Conclusions: This study indicates the burden of oral-health-
related conditions on Western Australian children and the hospital system, in terms of
health and economical impact.
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71
5.2. Introduction
In Australia, dental conditions are one of the highest causes of acute preventable hospital
admissions (The Steering Committee for the Review of Government Service Provision,
2010). In 2003–2004, over 26,000 children under the age of 15 years old had to undergo
general anesthesia in hospitals in Australia for dental extraction and/or restorations
(Australian Institute of Health and Welfare, 2008a; 2011b). In 1995, Western Australia
recorded 3,754 cases (4,395 bed days) of children under the age of 18 years-old admitted to
hospital for oral conditions (Tennant et al., 2000). Unfortunately, subsequent studies
indicated that the rate of hospitalisations for oral conditions has increased over time. Kruger
et al. (2006) conducted a study and found that from 1999 to 2003, a total of 26,497 hospital
admissions (31,432 bed-days) in WA were attributed to oral health conditions among
children under the age of 18 (Kruger Dyson, & Tennant, 2006).
Some studies have found that the rates of hospitalisation due to oral conditions in children
varied between the age groups, with the highest rates for high school aged children, followed
by pre-primary, and the lowest rate is the primary school-aged group (Rogers, 2011). This is
not unsurprising as the preschool children mostly do not, on the whole have access to the
safety nets of School Dental Services (SA Dental Service, 2013), while the teenage levels are
most likely related to the removal of impacted teeth (mostly third molars) (Australian
Institute of Health and Welfare, 2011c).
In Australia, Aboriginal and Torres Strait Islander people are the first people of the land.
They, like many Indigenous people have faced very significant marginalisation since
European settlement and continue to this day to face extreme issues of poor health
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72
(Australian Institute of Health and Welfare, 2011d). According to recent studies, Indigenous
children have, on average, twice the incidence of dental caries as their non–Indigenous
counterparts (Government Northern Territory, 2011; Christian et al., 2012), but in all child
age groups, except infants, the hospitalisation rates for all oral health conditions were
significantly higher among non-Indigenous children (Rogers, 2011).
The aim of this study is to analyse a decade of dental admission patterns in Western
Australian children under the age of 15 years, examining associations with
sociodemographic characteristics and with particular focus on dental decay and Indigenous
children. The null hypothesis of this study is that the hospital admissions for dental reasons
(in children) are not associated with sociodemographic characteristics.
5.3. Material and Methods
5.3.1. Data Source
This research involved a de-identified detailed analysis of the data obtained from the WA
Hospital Morbidity Dataset for ten financial years from 1999/00 to 2008/09 under ethics
approval from The University of Western Australia. Principal diagnosis, classified by the
International Classification of Diseases (ICD-10AM) system, was obtained for every child
under the age of 15 years diagnosed and accordingly admitted for an oral health condition
in Western Australia for the study period. All principal diagnoses of oral health conditions
(ICD-10AM) were included in the analysis. The ICD–10–AM ‘is the Australian Modification of
the 10th revision of the International Classification of Diseases (ICD–10). It is the standard
classification scheme now used for reporting diagnoses in all hospital statistical collections,
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73
including the National Minimum Data Set and the Hospital Casemix Protocol’ (Commonwealth
Department of Health and Aged care, 1998). Age, gender and Indigenous status, insurance
status, length of stay, hospital area and type of each child were analysed. Remoteness was
determined using the Accessibility/Remoteness Index of Australia (ARIA) classification,
which measures ‘remoteness in terms of access along the road network from populated
localities to each of five categories of Service Centre. Localities that are more remote have less
access to service centres; those that are less remote have greater access to service centres’
(Australian Population and Migration Research Centre, 2013). Socioeconomic status was
analysed using Socio-Economic Indexes of Area (SEIFA) classification which is a ‘product
developed by the Australian Bureau of Statistics that ranks areas in Australia according to
relative socioeconomic advantage and disadvantage. The indexes were based on information
from the five-yearly Census’ (Australian Bereau of Statisitics, 2013a).
5.3.2. Statistical Analysis
Age-adjusted rates (AARs) were calculated using the Health Statistics Calculator, a software
package developed by the Health Department of Western Australia. It should be noted that
the data for this study span the years 1999/00-2008/09. In rate calculations, population data
(denominators) were obtained from estimations by the Health Department of Western
Australia Bureau of Statistics. These estimations were based on population data as obtained
by Australian Bureau of Statistics Census Surveys. Significant differences between rates were
based on non-overlapping 95% confidence intervals (P <0.05).
Chapter Five
74
To determine significant differences between nominal (categorical) variables, chi-square
(χ²) tests were used. Significance levels were set at 95% with ρ value < 0.05 deemed to be
significant.
SPSS 21 for Windows (Statistical package for the social sciences; SPSS, Chicago, IL USA)
software is used for analysis.
5.4. Results
5.4.1. Overall Data Summary
Between 2000 and 2009, a total of 43,937 children (0–14 years) were hospitalised due to
oral conditions. Of these, 94 % (n=41,475) accounted for seven major categories of oral
conditions with half (50%) of those hospitalisations for ‘dental caries’, followed by,
‘embedded and impacted teeth’ (14%), ‘pulp and periapical’ tissue conditions (11%),
‘developmental and birth defects’ (5%), ‘dental fractures’ (5%) and ‘dentofacial anomalies’
4%. Overall 5% (n = 2119) of admissions were for Indigenous children.
5.4.2. All Children
Time trends. The AAR of hospitalisations for oral conditions increased from 926 in 2000 to
1085 cases per 100,000 person-years in 2009. Approximately 73% of the admissions were
among children younger than 9 years old. In 2003, children aged < 5 years had 1.3 and 1.7
times the admission rate of 5- to 9- and 10- to 14-year-olds children, respectively. Since then,
Chapter Five
75
the admission rates for 5- to 9-year-olds increased and in 2009 were 1.2 and 1.5 times the
admission rates of 0- to 4-year-olds and 10- to 14-year-olds, respectively (Figure 5.1).
Sociodemographics association. Figure 5.2 represents the trends of the most common
conditions over time. Overall, 546 per 100,000 children per annum were admitted for ‘dental
caries’ and 144 per 100,000 had ‘embedded or impacted teeth’. A non-Indigenous child was
29 times more likely than an Indigenous child to be admitted for ‘embedded or impacted
teeth’. Non-Indigenous children were more likely to be admitted than Indigenous children
except for ‘pulp and periapical’ conditions. (Table 5.1) Children aged < 5 were more likely to
be admitted due to ‘dental fracture’ or ‘birth defects’ conditions. In contrast, higher rates of
children aged between 5 and 9 years were hospitalised due to ‘developmental defects’ or
‘dental caries’. ‘Dento-facial anomalies’ and ‘embedded and/or impacted teeth’, however,
mainly accounted for the oldest age group admissions. Children younger than 9 years were
more likely to be admitted due to ‘pulp and periapical’ conditions (Table 5.1).
Gender. Males were most likely to be hospitalised for ‘dental caries’ (AAR 560, 95% CI 550.1-
570.4) than females (AAR 530, 95% CI 520.1-540.4) (Table 5.1).
Socioeconomic association. Across all common conditions, higher percentages of children
hospitalised lived in the least and above average disadvantaged areas, except for children
with ‘pulp and periapical’ conditions (25%), where most were living in the most
disadvantaged areas, followed by 23% in below average disadvantaged areas (P <0.001)
(Table 5.1).
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76
Remoteness of residency. Across all conditions, children living in accessible areas are more
likely to be admitted than children living in remote or very remote areas. Rural residence
was significantly associated with less dental admissions, than metropolitan-living children
across all conditions (P <0.001; Table 5.1).
Length of stay. The length of stay in hospital (LOS) was calculated and found 92% of
separations from hospital happened on the same day (P <0.001; Table 5.1).
Conditions. Children admitted to public hospitals were more likely to have ‘dental fractures’,
‘birth defects’ or ‘pulp and periapical’ conditions. ‘Developmental defects’, ‘embedded and
impacted teeth’, ‘dental caries’ or ‘dentofacial anomalies’ were more likely to be admitted in
private hospitals (Table 5.1)
Most hospitalisations for ‘birth defects’ were for ankyloglossia, followed by cleft lip and
palate, while the highest percentages of ‘developmental defects’ admissions were for
supernumerary teeth and disturbances in tooth formation or eruption conditions.
Cost. The total DRG (diagnosis-related group) cost of this care was approximately AUS $92
million. Private insurance was the primary source of reimbursement for 55% of non-
Indigenous children, while Indigenous child admissions were much more likely to be
publicly funded (96%) (P <0.001; Table 5.1).
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77
Figure 5.1 Hospitalisation rates by age, over time
Figure 5.2 Age-adjusted hospitalisation rates of WA children by condition, over time
0.00
200.00
400.00
600.00
800.00
1,000.00
1,200.00
1,400.00
1,600.00
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
AA
R p
er 1
00,
000
per
son
-yea
r
0 to 4
5 to 9
10 to 14
ASR per 100,000
0
100
200
300
400
500
600
700
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
AA
R P
er
10
0,0
00
pe
rso
n-y
ear
years
Embedded & Impacted teeth
Fracture & dislocated tooth
pulp & periapical
Developmental defects
Birth defects
Dental caries
Chapter Five
78
Table 5.1 Hospitalisation of WA children for most common oral conditions across different variables
Variables Dental
fracture
Birth
defect
Development
al defects
Embedded
&
impaction
Dental
caries
Pulp &
periapical
Dento-
facial
anomalies
All children (AAR) 49.1 56.4 56.6 144.4 545.6 116.8 44.8
Age
(AAR)
0–4 111 136.7 29.7 1.9 746.3 165.3 2.6
5–9 28.2 22.3 83.6 35.4 754.4 165.7 25.8
10–14 11.1 14.4 55.2 388.8 146.8 22.1 103.9
Indigenous
status
(AAR)
Indigenous 49.2 24.8 6.7 5.0 415.1 152.3 2.5
Non-Indigenous 44.3 53.1 54.4 142.9 497.8 99.9 44.1
Gender
(AAR)
Male 55.8 70.4 57.2 115.5 560.2 126.2 37.3
Female 42.0 41.7 56.0 175.2 530.2 106.9 52.8
SEIFA*
(%)
Most disadvantage 19.4 17.8 10.8 9.0 17.2 25.0 10.0
Below average
disadvantage
20.7 19.6 14.4 14.9 19.3 23.2 14.0
Average disadvantage 18.4 20.0 18.5 20.3 18.4 17.1 17.9
Above average
disadvantage
18.3 21.2 21.5 23.6 19.9 17.5 21.8
Least disadvantage 22.5 21.3 34.6 32.2 25.2 17.2 36.0
ARIA*
(%)
Highly accessible 18.4 18.9 16.8 25.6 19.2 20.5 18.9
Accessible 67.7 63.2 66.1 56.8 58.7 60.0 62.9
Moderately accessible 6.5 9.6 8.6 12.0 11.4 9.6 11.6
Remote 2.6 3.9 4.5 4.1 5.1 4.0 3.9
Very remote 4.7 4.5 3.8 1.5 5.6 5.8 2.6
Same day
separation*
(%)
Yes 78.5 70.1 97.5 94.4 97.6 87.0 92.8
No 21.5 29.9 2.5 5.6 2.4 13.0 7.2
Insurance
status* (%)
Insured 34.3 42.9 69.9 71.5 52.5 25.7 74.8
Uninsured 65.7 57.1 30.1 28.5 47.5 74.3 25.2
Hospital
type*
(%)
Public 88.2 56.8 18.2 9.0 35.5 79.3 21.0
Private 11.8 43.2 81.7 91.0 64.4 20.6 79.0
Commonwealth 0 0 0.1 0.1 0.1 0.1 0
Hospital
area(AAR)
Rural 14.5 20 15.8 83.8 301 53.3 27.8
Metropolitan 55.1 62.4 64 152.1 560.3 123.8 46.3
AAR (Age adjusted rate per 100,000)
P < 0.001, Pearson chi-square
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79
5.4.3. Aboriginal and Torres Strait Islander Children
Rural-living non-Indigenous children had 1.2 times the admission rate of rural-living
Indigenous children. In contrast, Indigenous children living in major cities or regional areas
had 2.6 times the admission rate of their Indigenous counterparts in rural or remote areas.
Sixty-three percent of all separations recorded for patients identified as non-Indigenous
occurred in metropolitan private hospitals.
Time trends. Figure 5.3 shows that the AAR of hospitalisation for Indigenous children in the
last decade increased to reach that of non-Indigenous children in 2009. From 2000 to 2008,
the difference between Indigenous and non-Indigenous was statistically significant over this
period. Admission AARs for non-Indigenous children were 1.3 times more than that of
Indigenous children, with non-Indigenous females significantly, more likely to be admitted
than Indigenous females. In contrast, there is no statistical difference in the admission rates
between Indigenous males and females. Furthermore, the highest AAR of hospitalisation was
observed among Indigenous children under the age of 5 years (1337) (Table 5.2).
Length of stay. Indigenous children were more likely to have longer admissions than non-
Indigenous children (P <0.001; Table 5.3).
Insurance. Nearly 97% of Indigenous hospitalised children were uninsured with public
hospitals mostly the primary place of admission (P <0.001).
Socioeconomic associations. It was more likely for non-Indigenous children, across all ages,
from higher socioeconomic areas to be admitted compared to Indigenous children. Fifty-nine
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80
percent of all Indigenous children hospitalised were in the lowest socioeconomic group (P
<0.001; Table 5.3).
Remoteness of residency. According to ARIA, 60% of non-Indigenous children hospitalised in
WA lived in areas classified as accessible. Conversely, highest percentage (33%) of
Indigenous children lived primarily in very remote areas (ρ<0.001; Table 5.3).
Figure 5.3 Hospitalisation age-adjusted rates of WA children by Indigenous status, over time.
0
500
1000
1500
2000
2500
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
AA
R P
er
10
0,0
00
Pe
rso
n-y
ear
Indigenous
Non-Indigenous
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81
Table 5.2 Age-adjusted rates of hospitalisation for oral health conditions across age groups, gender and geographical location.
Indigenous Non-Indigenous Total
AAR* Cl§ AAR* Cl§ AAR* Cl§
All ages 813.3 778.7-848.0 1,090.4 1,079.9-1,100.8 1,073.6 1,063.5-1,083.6
Age group 0–4 1,328.7 1,251.2-1,406.2 1,244.7 1,224.9-1,264.4 1,250.2 1,231-1,269.3
5–9 901.3 838.6-964.0 1,182.4 1,163.6-1,201.3 1,164.3 1,146.1-1.182.4
10–14 229.4 197.3-261.5 853 837.4-868.6 816.8 802.1-831.6
Gender Male 853.1 803.5-902.6 1,095.6 1,080.9-1,110.2 1,080.6 1,066.6-1,094.7
Female 771.9 723.6-820.3 1,085.2 1,070.2-1,100.2 1,066 1,052.2-1,080.9
Location Rural 511.3 476.6-546.0 626.4 610.1-642.6 609.8 595.0-624.6
Urban 1,312.6 1,240-1,384.3 1,235.0 1,222.2-1,247.7 1,238.1 1,225.6-1,250.7
*Age adjusted rate per 100,000 person-years. § Cl represents the 95% confidence interval for AAR
Table 5.3 Percentages of child hospitalisations for oral health conditions across hospital type, SEIFA, ARIA and same day of separation.
Percentage (%)* Indigenous Non-
Indigenous
Hospital type Public 96.0 36.5
Private 4.0 63.4
SEIFA
Most disadvantage 58.9 14.3
Below average disadvantage 20.9 18.5
Average disadvantage 9.4 19.0
Below average disadvantage 7.1 21.0
Least disadvantage 3.8 27.2
ARIA
Highly Accessible 12.2 20.3
Accessible 30.8 61.3
Moderately Accessible 14.4 10.6
Remote 9.4 4.4
Very remote 33.2 3.3
Same day
separation
Yes 75.7 93
No 24.3 7
Insurance status Yes 3.5 55.1
No 96.5 44.9
P < 0.001, Pearson chi-square
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82
5.5. Discussion
In this study, the most common reasons for hospital admissions were ‘dental caries’ and
‘embedded and impacted teeth’. Over time, the hospitalisation rates of ‘dental caries’
increased. This is consistent with findings of a previous study (Kruger Dyson, & Tennant,
2006). Males exhibited a significantly higher rate of hospitalisation due to ‘dental caries’,
than females. The reason for the higher caries experience in males is unclear, although it has
been claimed that male children who have the same genotype of Streptococcus mutans as
their mother have up to 13 times greater risk of caries development than female children
that acquire the same strain of bacteria from their mother (Li & Caufield, 1995).
Hospitalisations for ‘embedded and impacted teeth’ were mainly among the oldest age group
with very significant differences between non-Indigenous and Indigenous children. This
confirm the finding of the previous surveys (Kruger Dyson, & Tennant, 2006; George et al.,
2011a). Hospitalisation at this age group, however, is unlikely to be due to third molar
impaction. Maxillary canine is one of the most frequently impacted teeth in children aged 11–
14 years, with the prevalence ranging from 0.8 to 5.2% (Ranjit et al.; Litsas & Acar, 2011).
‘Embedded and impacted teeth’ are predominantly undertaken in the private sector, which
is not managed through policy directives (George et al., 2011a). Non-Indigenous children are
more likely to have private health cover, which plays an important role in dental health-care
delivery in Australia. In 2010–11, 58% of dental expenditure in Australia was funded by out-
of-pocket expenses and 14% by health insurance (Australian Institute of Health and Welfare,
2012).
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83
Hospitalisations for ‘pulp and periapical’ conditions were mainly due to periapical abscess
without sinus formation. It is not surprising that uninsured, Australian Indigenous male
children aged < 9 years, and living in the most disadvantaged areas were more likely to be
admitted for this condition. This can indicate that they only access dental care when
conditions reached an advanced stage.
Although preschool children have difficulties accessing the existing dental health service, the
rates of hospitalisation among this age group have been declining since 2003. In 2005– 2009,
however, the hospitalisation rates of 5- to 9-year-olds started to increase and exceeded the
rates of 0- to 4-year-olds. The changing rates of procedures over time might be a result of
changing trends in clinician beliefs, as well as changing health insurance levels in the
community; no specific reason for change is evident. Currently, most publicly delivered
children dental program in Australia is SDS, which includes only emergency or basic
treatment, and covers only limited care for school children particularly those within low-
income families (An Advocacy Kit for Community and Welfare, 2010). The
comprehensiveness of these programmes differs significantly among state and territories in
terms of the types of services covered, age restrictions, and limits on the frequency of dental
visits. In Western Australia, the SDS is primarily a public dental health program, with
emphasis on prevention and education, and it provides free limited general dental care to
school children ranging from pre-primary through to year 11 and to year 12 in remote
locations. This care is provided by dental therapists from fixed and mobile clinics located at
schools throughout the state. Thus, treatment outside the scope of the SDS is referred to
other providers, and any costs are the responsibility of the parent or guardian. Furthermore,
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84
not all students are enrolled in SDS, and long intervals between visits might delay
interventions and early prevention.
Although the health of Indigenous children in Australia is lower than that of non-Indigenous
children for most indicators (Australian Institute of Health and Welfare, 2007b; 2012),
admission rates were higher among non-Indigenous children, as reported previously for
Western Australian children (Tennant et al., 2000; Kruger Dyson, & Tennant, 2006). The
differences observed are thought to be attributed to a number of factors, such as variation in
service access as a significant proportion of Indigenous children live in rural and remote
locations (Steele et al., 2000), socioeconomic or environmental factors(Munoz, Powers,
Nienhuys, & Mathews, 1992).
The Indigenous population in Western Australia constitutes just 3.2% of the total population
of the state and predominantly lives in rural and remote areas and in areas of higher
socioeconomic disadvantage (Australian Bereau of Statisitics, 2006). The hospitalisation
rates were higher among children living in metropolitan areas than in the rural children. This
can be attributable to the fact that Western Australia is experiencing a dental workforce
shortage in rural and remote areas, especially in terms of dental therapists and dental
specialists (Steele et al., 2000). Furthermore, geographical access to health services was
considered as the reason for this unequal distribution; it is evident by the fact that
Indigenous children in metropolitan areas are also more likely to be admitted than
Indigenous children in rural areas. They are also less likely to have private health cover,
which plays an important role in the private-driven dental health-care delivery in Australia
and hence fail to have adequate dental treatment. There is an obvious association between
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85
insurance status, and hospital types (private or public), and the admission of Indigenous
children, which might reflect the socioeconomic barriers to dental service utilisation.
Moreover, the public sector largely services medical and surgical emergencies and other
complex conditions and procedures. Indigenous children were more likely to have longer
stays in hospital than non-Indigenous children, and might be attributed to the severity of the
condition.
This study focused on the trends over a 10-year time period and to highlight those groups
within the child population more likely to be admitted. The same dataset is also being used
for further analysis to determine risk indicators and will involve more detailed statistical
analysis.
5.6. Recommendations and Conclusion
Most oral conditions, and especially dental caries, are preventable. These findings of this
study indicate rejection of the null hypothesis and it identified groups within the child
population more likely to be admitted to hospital for treatment of oral health-related
conditions, as well as associated characteristics. This information should be utilised and
applied to prevent costly in-patient treatment by early detection, prevention, and
intervention. At a time, when public health resources are limited, strategies need to be
developed to focus on these high-risk groups and best practice principles of care and demand
management to better utilise limited health resources. It is also important to address the
need for the redistribution of resources on the basis of regional need and the development
of community-based preventive programmes and treatment programmes, which will
significantly reduce the incidence of dental diseases in Australian children.
86
Chapter Six
6. Disparities in Dental Insurance Coverage among
Hospitalised Western Australian Children.
This chapter was published in the following article:
Alsharif, Alla, Kruger, Estie & Tennant, Marc. (2014). Disparities in dental insurance
coverage among hospitalised Western Australian children. International Dental
Journal. 64(5), 252-259. (Appendix C)
Chapter Six
87
6.1. Abstract
Objective: We sought to understand disparities in dental insurance coverage among
hospitalised Western Australian children and associated factors.
Material and Methods: This study analysed the data obtained for 43,937 child patients
under the age of 15 years hospitalised for an oral-health related condition, as determined
by principal diagnosis (ICD-10AM). Primary place of residency, age, gender, Indigenous
status and socioeconomic status were also analysed.
Results: Of our sample, 47.3% reported lack of dental insurance coverage. Non-
Indigenous children were more likely to have dental insurance than Indigenous children.
When insurance status was considered, Indigenous children were less likely to be
hospitalised for dental treatment. Rural children were more likely to be uninsured than
urban children. Lack of health insurance coverage was strongly associated with children
living in very remote areas. These disparities were exacerbated among rural indigenous
children. Disparities in dental insurance coverage and dental care are also evident by
socioeconomic status.
Recommendations and Conclusions: Better understanding of disparities in access to
care among children, socioeconomic divide in oral health insurance coverage and
subsequent development of intervention programmes, will be critical to improving
Australian children’s oral health.
Key words: Disparities, hospitalisation, dental, Australia.
Chapter Six
88
6.2. Introduction
One of the fundamental objectives of health-care systems across the globe is to ensure that
individuals have access to care on the basis of need, rather than ability to pay. However, this
objective in a free-market economy is often warped by the economic goals of society. In
Australia, dental services are predominately provided in the private sector setting and
therefore prices and wealth wraps around access. Historically, because dental care has not
been considered integral to health care, it is not subject to the tenets of the Australian Health
Act (AHA): that is, publicly administered, universal, portable, accessible and comprehensive
(Haas & Anderson, 2005). In contrast to physician- and hospital-based services that are
mainly publicly funded, Australians are largely responsible for financing their own dental
care. Australians pay for dental care in four different ways: through third-party insurance
(employment-related health insurance coverage); through private dental insurance; by
paying directly out-of-pocket; or through government-subsidised programmes (e.g. School
Dental Services for children or community and public hospital clinics for adults) (Haas &
Anderson, 2005).
At present, most publicly delivered child dental programmes in Australia are via School
Dental Services, which includes only emergency and basic treatment, and cover only limited
care for school children, particularly those with in low-income families (An Advocacy Kit for
Community & Welfare, 2010). However, most major in-hospital dental services are provided
by the private sector offering non-subsidised care. In addition, private health insurance
covers a proportion of costs but consumers have always faced relatively high out-of-pocket
costs for these services. In 2005, 43.8% of Australian children aged from 5–11 years had
private dental insurance (predominately personal) and 22.3% had cardholder status
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(eligible for publicly provided services) (Ellershaw & Spencer, 2009). The groups most
marginalised by the current dental care system are the lowest income families, Indigenous
people and children living in remote areas; this has a great impact on these suffering high
disease burdens such as the children of Australia’s first people the Aboriginal and Torres
Strait Islander people (An Advocacy Kit for Community & Welfare, 2010). These population
groups have the least access to dental care and carry the greatest burden of untreated
disease (An Advocacy Kit for Community & Welfare, 2010). People from wealthier groups
have better oral health and make use of more complex and expensive services, while waiting
lists for public dental care have grown by 20% per year (Haas & Anderson, 2005). Over time,
this has resulted in increased inequity in access to care.
This study examines the disparities in dental insurance coverage among Western Australian
children hospitalised because of oral health-related conditions and associated factors to
address the inequalities that currently exist. The null hypothesis of this study is that
childrens’ hospital admissions for dental conditions are not associated with the presence of
private health insurance.
6.3. Material and Methods
6.3.1. Data Source
This primary research data set was de-identified detailed data obtained from the Western
Australia Hospital Morbidity Dataset for 10 financial years from 1999–2000 to 2008–2009.
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Ethics. This research was conducted in full accordance with the World Medical Association
Declaration of Helsinki and ethical approval was granted by the Ethics Committee of The
University of Western Australia. Children were not directly involved in the study, as this was
only an analysis of de-identified hospitalisation data, as provided by the Health Department
of Western Australia.
Principal diagnosis. Principal diagnosis, classified by the International Classification of
Diseases (ICD-10AM) system, was obtained for every child under the age of 15 years
diagnosed and admitted for an oral health condition in Western Australia for the study
period. All principal diagnoses of oral health conditions (ICD-10AM) were included in the
analysis. The ICD–10–AM ’is the Australian Modification of the 10th revision of the
International Classification of Diseases (ICD–10). It is the standard classification scheme now
used for reporting diagnoses in all hospital statistical collections, including the National
Minimum Data Set and the Hospital Casemix Protocol’ (Commonwealth Department of Health
and Aged Care, 1998). For each child, age, gender and Indigenous status, insurance status,
hospital area and hospital type were also analysed.
Residential location. Remoteness was classified using the Accessibility/Remoteness Index of
Australia (ARIA) which measures ‘remoteness in terms of access along the road network from
populated localities to each of five categories of Service Centre. Localities that are more remote
have less access to service centres; those that are less remote have greater access to service
centres’ (Australian Population and Migration Research Centre, 2013).
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Socioeconomic status. Socioeconomic status was analysed using the Socio-Economic Indexes
of Area (SEIFA) classification which is a ‘product developed by the Australian Bureau of
Statistics that ranks areas in Australia according to relative socioeconomic advantage and
disadvantage. The indexes are based on information from the five-yearly Census’ (Australian
Bereau of Statisitics, 2013a).
6.3.2. Statistical Analysis
All data were analysed using SPSS 21 (Statistical package for the social sciences; SPSS,
Chicago, IL USA) for Windows software. Statistical significance was set at 95% (P < 0.05) and
was calculated using Pearson chi-square tests (χ²), to determine significant differences
between nominal (categorical) variables.
6.4. Results
From 2000 to 2009, a total of 43,937 children (0–14 years) were hospitalised because of oral
health-related conditions. Overall 5% (n = 2119) of admissions were for Indigenous children.
6.4.1. Dental Insurance (All children)
Almost one in every two children hospitalised was uninsured (47.3%; Table 6.1).
Age in years on admission. Children aged between 10 years and 14 years reported a
significantly higher level of dental insurance coverage than children younger than 9 years
old (P < 0.01; Table 6.1).
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Gender. More females (54%) were insured than males (51.4%) (Table 6.1).
Hospital type. Children with private health insurance were more likely to be admitted to
private hospitals than uninsured children (P < 0.01; Table 6.1).
Location. Children admitted to metropolitan hospitals were 1.6 times more likely to be
insured than children admitted to rural hospitals. Children from the oldest age group were
more likely to be insured than younger age groups. The observed variations were
statistically significant (P < 0.01; Table 6.1).
Socioeconomic status. Children with the lowest socioeconomic status (SES) were significantly
less likely to have dental insurance. In contrast, 76% of children hospitalised from least
disadvantaged areas were insured. Hospitalised children from high SES backgrounds were
three times more likely to be insured than children from most disadvantaged areas. (P < 0.01;
Table 6.1)
Remoteness/ accessibility. Statistically significant variations were observed across ARIA
classification (P < 0.01). Lack of health insurance coverage was strongly associated with
children living in very remote areas. Children living in accessible areas were twice as likely
to be insured as children living in very remote areas (Table 6.1).
Length of stay. Sixty-six percent of children admitted for more than a day were uninsured. Of
those admitted for more than a day, 78% of the 5-9 year olds and 74% of the < 5 year olds
were uninsured (P < 0.01; Table 6.1).
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Insurance status over time. In 2000, children admitted to hospital for oral health-related
conditions were more likely to be uninsured. Since then, insurance levels have increased to
reach 63% of all children younger than 15 years old hospitalised because of oral conditions
in 2009 (P < 0.01, Figure 6.1a). Statistically significant higher levels of dental insurance
coverage were observed among children aged between 10 and 14 years over time, followed
by the 5- to 9-year-old group (P < 0.01; Figure 6.1b). However, over last decade, the
percentage of uninsured children younger than 4 years old has decreased by 22% (P < 0.01;
Figure 6.1c).
Table 6.1
The percentages of hospitalisation of Western Australia children based on insurance status
compared with different variables
Insured Uninsured
Age (years) 0–4 5–9 10–14 Total 0–4 5–9 10–14 Total
All children 42.1 52.2 68.0 52.7 57.9 47.8 32.0 47.3
Gender Male 42.1 52.4 66.5 51.4 57.9 46.6 33.5 48.6
Female 42.1 52.0 69.1 54.0 57.9 48.0 30.9 46.0
Hospital
type*
Public 12.9 12.6 18.2 13.6 87.1 87.4 81.8 86.4
Private 71.9 80.3 81.6 78.2 28.1 19.7 18.4 21.8
Location* Urban 45 55.9 70.3 55.7 55 44.1 29.7 44.3
Rural 26.3 30.4 54.5 35.2 73.7 69.6 45.5 64.8
SEIFA* Most disadvantage 17.3 23.2 39.7 24.4 82.7 76.8 60.3 76.6
Below average
disadvantage
31 38.2 55.1 38.8 69 61.8 44.9 61.2
Average disadvantage 42.2 49.3 64.8 50.8 57.8 50.7 35.2 49.2
Above average
disadvantage
54.6 60.4 71.1 61.4 45.4 39.7 28.9 38.6
Least disadvantage 68 74.5 83.6 75.7 32 25.5 16.4 24.3
ARIA* Highly Accessible 39.5 51.5 67.3 51.6 60.5 48.5 32.7 48.4
Accessible 47.3 57.8 73.1 58.2 52.7 42.2 26.9 41.8
Moderately Accessible 31.0 36.9 50.5 38.5 69 63.1 49.5 61.5
Remote 34.8 43.2 59.2 43.4 65.2 56.8 40.8 56.6
Very remote 27.2 25.5 40.7 28.3 72.8 74.5 59.3 71.7
Same-day
separation*
Yes 43.8 54 69 54.2 56.2 46 31 45.8
No 26.5 22.2 57.4 34.2 73.5 77.8 42.6 65.8
SEIFA, Socio-Economic Indexes of Area; ARIA, Accessibility/Remoteness Index of Australia. *P < 0.001, Pearson chi-square, and refer to differences between variable categories, not between insured and uninsured.
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Figure 6.1a The percentages of hospitalisation among WA children based on insurance status.
Figure 6.1b
The percentages of insured hospitalised WA children over time based on age
0
20
40
60
80
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pe
rce
nta
ges
of
ho
spit
alie
d c
hild
ren
Insured
Uninsured
0
20
40
60
80
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pe
rce
nta
ges
un
insu
red
ho
spit
alis
ed
ch
ildre
n
0 to 4
5 to 9
10 to 14
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Figure 6.1c
The percentages of uninsured hospitalised WA children over time based on age
6.4.2. Dental Insurance (Indigenous Status)
The disparities were exacerbated among Indigenous children. Non-Indigenous Western
Australian children aged less than 15 years and hospitalised because of oral conditions over
the last decade were 16 times more likely to be insured compared with their Indigenous
counterparts.
Age. Across all ages, the majority of Indigenous children were uninsured. The percentage of
insured Indigenous children aged 5–9 years were higher (1.2%) than the percentages in
other Indigenous age groups (P < 0.01; Table 6.2).
0
20
40
60
80
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pe
rce
nta
ges
un
insu
red
ho
spit
alis
ed
ch
ildre
n
0 to 4
5 to 9
10 to 14
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Gender. Slightly more (3.9%) male Indigenous children were insured compared with female
Indigenous children (3.1%). In contrast, 57% of non-Indigenous females were insured
compared with their male counterparts (54%) (P < 0.01; Table 6. 2).
Location. Indigenous children living in urban areas were five times more likely to be insured
compared with their rural counterparts. Interestingly, non-Indigenous children living in
rural areas were 37 times more likely to be insured than Indigenous children living in rural
areas (P < 0.01; Table 6.2).
Hospital type. Both insured Indigenous and non-Indigenous children were significantly more
likely to be admitted in private hospitals (P < 0.01; Table 6.2).
Length of stay. Only (0.9%) of Indigenous children hospitalised for more than a day were
insured (P < 0.01).
Common oral conditions. There was a distinct contrast in the percentages of children with
health insurance among Indigenous and non-Indigenous group (P < 0.01; Table 6.2).
Socioeconomic status. Ninety-eight percent of Indigenous children hospitalised and living in
the most disadvantaged areas were uninsured. Significant differences in insurance status
between Indigenous and non-Indigenous children were observed based on socioeconomic
status, using the SEIFA scale (Table 6.2). Non-Indigenous children living in the most
disadvantaged areas were 19 times more likely to be insured than Indigenous children living
in the same areas. Statistically significant variations were observed across socioeconomic
distribution (P < 0.01).
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Remoteness/accessibility. For both Indigenous and non-Indigenous children the proportion
with health insurance decreased with increasing geographic remoteness, with insurance
levels of only 4% and 1.3% of the Indigenous child population residing in remote or very
remote areas, respectively. However, non-Indigenous children living in very remote areas
were 32 times more likely to be insured than their Indigenous counterparts (P < 0.01; Table
6.2).
Changes over time. Constant and high percentages of hospitalised Indigenous children have
been uninsured over the last decade (P < 0.01). The percentages of those with health
insurance among Indigenous hospitalised children were very low and constant over the
study period, with a slight increase (13%) in 2009 (Figure 6.2). In contrast, since 2005,
insurance among hospitalised non-Indigenous children has increased (P < 0.01; Figure 6.3).
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Table 6.2 The percentages of insurance coverage among hospitalised WA children based on Indigenous status and different variables.
Indigenous Non-Indigenous
Insured Uninsured Insured uninsured
All children* 3.5 96.5 55.1 44.9
Age*
(years)
0–4 3.1 96.9 45 55
5–9 4.3 95.7 54.7 45.3
10–14 3.1 96.9 69.1 30.9
Gender* Male 3.9 96.1 53.9 46.1
Female 3.1 96.9 56.5 43.5
Location* Urban 5.1 94.9 57.5 42.5
Rural 1.1 98.9 40.2 59.8
Hospital
type*
Public 1.1 98.9 15.2 84.8
Private 61.9 38.1 78.2 21.8
Same day
separation*
Yes 4.5 95.5 56.2 43.8
No 0.9 99.1 40.7 59.3
Conditions* Dental fracture 2.2 97.8 36.6 63.4
Birth defects 2.8 97.1 44.2 55.8
Developmental Defects 21.1 78.9 70.4 29.6
Embedded & Impacted teeth 7.1 92.9 71.6 28.4
Dental Caries 4.7 95.3 55.1 44.9
Pulp & periapical 1.3 98.7 28.8 71.2
Dento-facial anomalies 0 100 75.1 24.9
SEIFA* Most disadvantage 1.5 98.5 28 72.0
Below average disadvantage 3.4 96.6 40.9 59.1
Average disadvantage 5.1 94.9 51.9 48.1
Above average disadvantage 11.3 88.7 62.3 37.7
Least disadvantage 15 85 76.1 23.9
ARIA* Highly Accessible 6.6 93.4 53 47.0
Accessible 5.4 94.4 59.5 40.5
Moderately Accessible 2 98 41 59.0
Remote 4 96 47.6 52.4
Very remote 1.3 98.7 41.8 58.2
P < 0.001, Pearson chi-Square
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Figure 6.2
The percentages of hospitalisation among WA Indigenous children based on insurance
status.
Figure 6.3
The percentages of hospitalisation among WA non-Indigenous children based on insurance
status.
0
20
40
60
80
100
120
Pe
rce
nta
ges
of
ho
spit
alie
d in
dig
en
ou
s ch
ildre
n
Insured
Uninsured
0
20
40
60
80
Pe
rce
nta
ges
of
ho
spit
alie
d in
dig
en
ou
s ch
ildre
n
Insured
Uninsured
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6.5. Discussion
Health insurance coverage has previously been found to be a good predictor of preventive
care service use (Kenney, McFeeters, & Yee, 2005; Harford & Luzzi, 2010). Health insurance
in Australia does not automatically include dental insurance, but Australians can obtain
dental insurance by purchasing either private patient hospital cover combined with an
‘extras’ option that includes dental services, or the ‘extras only’ option. There are two levels
of dental services provided by this insurance: general dental coverage and major dental
coverage. General dental coverage typically includes services such as cleaning, removal of
plaque, radiographs and small restorations. Major dental coverage includes these services
plus additional services such as orthodontics, third molar removal, crowns, bridges and
dentures.
Dental health-care coverage is an indicator that reflects the extent to which people in need
actually receive essential dental health interventions (Kenney et al., 2005; Harford & Luzzi,
2010). The primary explanation cited in the literature for delayed dental health care seeking
is financial barriers (Harford & Luzzi, 2010). In this study, we found statistically significant
disparities in dental insurance coverage among hospitalised children associated with
Indigenous status, socioeconomic status and remoteness and accessibility of residential area.
The impacts of this disparity go beyond just the greater prevalence of the dental and oral
disease, and include greater morbidity and mortality.
In this study, those children who did have dental health insurance were more likely to come
from urban, accessible and least disadvantaged areas. This confirms findings of previous
surveys and may be an indication that insurance enabled access to dental care and led to
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greater demand for care once access had been obtained (Bagramian, Garcia-Godoy, & Volp,
2009). Although private dental insurance does not necessarily increase receipt of preventive
service or decrease perceived unmet need in all cases, it is evident that insured children are
more likely to be hospitalised for less invasive treatment than their uninsured counterparts
(who were probably more likely to receive extractions in dental clinics as outpatients and
would have difficulty paying a $100 dental bill). Kaspe et al. (2000) found that the uninsured
individuals were more likely to have difficulty obtaining health care once they lost coverage
(Kasper, Giovanni, & Hoffman, 2000). However, those uninsured individuals that did gain
private health cover had increased access to health services compared with those that
remained uninsured (Kasper et al., 2000). In terms of health status, it is suggested that
individuals losing coverage might experience adverse health outcomes compared with those
that remained insured. The previous article elucidates that having private health insurance
increases access to care and possibly improves health status. It is evident that Australian
children who were covered by private dental health insurance were less likely to report fair
or poor oral health than uninsured children (Harford & Luzzi, 2010).
A much smaller percentage of Indigenous children with health insurance compared with
non-Indigenous children could contribute to the poorer oral health status of Indigenous
children and inequality in access to oral health-care (Australian Institute of Health and
Welfare, 2007). As a result of inadequate health insurance coverage, with nearly 97% of
hospitalised Indigenous children being uninsured, numerous concerns about dental service
utilisation are raised. In dental markets where well-insured or private-pay patients are
common, public dental care coverage in children alone will be insufficient to remove
disparities in dental utilisation. The lack of affordable dental care and insurance coverage
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leads to postponing dental treatment, often for years. These untreated symptoms inevitably
get more severe, resulting in children requiring admission for more invasive treatment at a
much greater public expense than if they had been provided dental treatment when the
symptoms first occurred.
Furthermore, over the past 20 years, health care has become more expensive and more
individuals are unable to afford health insurance. It is important to note that the vast
majority of dental specialists are in private practice; consequently, most hospitalisations for
oral problems in children, and requiring general anesthesia, take place in specialised private
hospitals (Kruger Dyson, & Tennant, 2006; Australian Institute of Health and Welfare, 2010).
Accordingly, parents are forced to pay directly out of pocket or indirectly through private
health insurance for the hospitalisation process. In 2013, in Australia, Harford et al.’s
reported that almost 30% of children avoided or delayed seeking oral health care, did not
have recommended treatment, or their parents experienced a large financial burden because
of the cost of dental care (Harford & Luzzi, 2010). Children from low SES were seven times
more likely to avoid or delay visits because of cost compared with high SES counterparts,
and six times more likely to not have had recommended treatment because of costs (Harford
& Luzzi, 2010). Therefore, private dental insurance is an important factor modifying access
to dental care. These affordability and accessibility inequalities between groups might
indicate a substantial variation within Australian children, as seen in previous studies
(Kruger Dyson, & Tennant ., 2006; Williams et al., 2011).
The literature is replete with evidence that remote Indigenous children experience worse
oral health than their urban counterparts (Australian Institute of Health and Welfare, 2007;
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Smith et al., 2007), but this is not reflected in the higher rates of hospitalisation among
metropolitan Indigenous children (Williams et al., 2011; Tennant et al., 2000; Australian
Indigenous HealthInfoNet, 2013; Australian Institute of Health and Welfare, 2012 & MacRae
et al., 2012). This can be partly explained by the greater availability of service (even SDS)
and the higher proportion of insured urban-living Indigenous children than insured rural
and remote dwellers. In the rural environment, dental health-care services may be sparse
and located at great distances from the patient. In an urban environment, health-care
services may be located closer but, in addition to financial issues, transportation (such as
buses, trains) may be a barrier to getting to the needed care on time.
The Indigenous population is disadvantaged across a range of socioeconomic conditions, and
these affect child health outcomes. Research over the past decade has continued to show that
Indigenous children suffer disproportionately from many diseases, including dental
diseases, and a delayed access to the health-care system will increase their risk for other
complications and mortality from these illnesses. Most dental diseases are preventable and
unnecessary suffering and disability can be avoided by decreasing delays in diagnosis and
treatment. In addition, lack of access to ambulatory health care can lead to unnecessary
hospitalisations and more expensive forms and utilisation of health care. Therefore, having
dental insurance is seen, at least partly, as a way of overcoming financial barriers when in
need of dental care.
Over time the level of health insurance for Indigenous and non-Indigenous children can thus
be seen to reflect the inequality in health systems (including dental health) among the
Australian child population. Throughout Western Australia the SDS primarily focuses on
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prevention and education, and it provides free limited basic dental care by dental therapists
to school children ranging from pre-primary up to Year 12 in remote locations. The
Australian government provided a ‘safety-net’ system (SDS) as a way to provide free or
reduced fee dental care to uninsured children. However, these sources of care are not always
accessed and, as the numbers of poor and uninsured increase, the ‘safety-net’ health system
will be unable to bear the burden of providing dental health care to all of the uninsured. In
addition, any further invasive treatment is referred to other providers and any costs are the
responsibility of the parent.
The public health community needs to know more about the restrictions to seeking dental
health care within the Australian child population to enable better resource allocation, policy
and planning. Therefore, understanding and developing a plan to combat the disparities in
dental health among these groups should be a national priority.
6.6. Recommendations and Conclusion
Dental health insurance is a major component of obtaining and accessing child dental health
care. Our study adds new information regarding the demand for dental care among children
aged between 0 and 14 years, who account for 18.9% of the Australian population, leading
to an increasing awareness of the substantial heterogeneity within the populations.
Therefore, better understanding of disparities in access to care among children and the
socioeconomic divide in oral health insurance coverage, and subsequent development of
intervention programmes, will be critical to improving Australian children’s oral health.
Eliminating socioeconomic and geographical disparities in dental insurance and dental care
requires additional efforts in removing both financial and non-financial barriers to dental
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utilisation. Furthermore, improving dental insurance coverage for Indigenous and rural-
living children will ultimately help save health costs and improve overall health for the next
generation.
106
Chapter Seven
7. A Population-based Cost Description Study of
Oral Treatment of Hospitalised Western
Australian Children Aged Younger than 15 Years.
This chapter was published in the following article:
Alsharif, A. T., Kruger, E. & Tennant, M. (2015). A population-based cost description study of
oral treatment of hospitalized Western Australian children aged younger than 15
years. Journal of Public Health Dentistry. 75(3), 202-209. (Appendix D)
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7.1. Abstract
Objective: We sought to analyse the economic cost of a decade of dental hospital
admissions in Western Australian children under the age of 15 years and to identify socio-
demographic characteristics associated with these costs.
Material and Methods: This study analysed the cost of 43,937 child patients under the
age of 15 years hospitalised for an oral health–related condition, as determined by
principal diagnosis International Classification of Diseases (ICD-10AM). The Australian
Refine Diagnosis Related Group version 5.1 was used to calculate the direct cost. An
analysis of costs was broken down by socioeconomic status, primary place of residency,
age, gender, insurance status, and Indigenous status.
Results: The total DRG cost of these admissions was approximately AUS$92 million over
10 years. Most of these funds went toward treating “Dental caries” and “Embedded and
impaction” conditions of children under the age of 15 years. Approximately 95 percent of
the total cost of hospitalisation for oral conditions, over the last decade, accounted for
non-Indigenous children. Since 2000, the direct cost of child hospitalisation for oral
health-related conditions has increased to reach $13 million AUD in 2009.
Recommendations and Conclusions: This study identified the substantial economic
burden of child oral health-related hospitalisations that emphasises the importance of
preventing costly inpatient treatments.
Key words: cost, children, dental hospitalisation, Western Australian.
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7.2. Introduction
Dental conditions, specifically caries, are affecting the majority of children who live in
Western Australia (WA). It is important to note that the Australian Government provides
funds for running various public health programmes, such as School Dental Services (SDS),
addressing children with poor oral health (Merrick et al., 2012). Yet, many children still end
up in hospitals for dental treatment. The public health burden of hospital admissions due to
oral conditions is quite substantial. Recent research indicates that the rate of hospitalisation
due to oral conditions among WA children is 1,074 per 100,000 populations annually
(Alsharif, Kruger, & Tennant, 2014a). Yet, little is known about the economic effects of in-
hospital treatment of such conditions in Australia. It has also been noted that dental
admissions are the largest category of acute preventable hospital admissions and that oral
health problems are the second-most expensive disease group in Australia, with direct
treatment costs of over $6 billion annually and additional care costs exceeding a further $1
billion (Rogers, 2011).
The provision of health-care services to children affected by oral health issues in WA has
been a very costly obligation. Tennant et.al affirms how expensive oral health-care for
Western Australian children is, by stating that in 1995 approximately $111 million were
spent on the hospitalisation of children under 18 years of age (Tennant et al., 2000). Existing
data suggest that in the period between 1999 and 2003, the cost of hospitalisation for
children under the age of 18 years was $40 million (Kruger Dyson, & Tennant, 2006).
However, current estimates of treatment costs are unknown, and prior estimates are likely
to be obsolete in light of newer therapeutic modalities, inflation and changing patterns of
hospitalisation and surgery. The precise estimation of the costs of oral health services is
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critical to prevent undesired consequences affecting the quality of oral health-care.
Therefore, an updated estimate of the treatment costs of oral diseases in WA is necessary, as
this is an expensive service of providing treatments for (mostly) preventable conditions, and
our objective was to document all costs associated with the treatment of dental conditions
in the child population.
The aim of this study is to analyse the economic cost of a decade of dental hospital admissions
in Western Australian children under the age of 15 years and to identify sociodemographic
characteristics associated with these costs. The null hypothesis of this study is that hospital
admissions for dental reasons (in children) are not associated with an increased economic
burden on Australian dental health expenditure.
7.3. Material and Methods
7.3.1. Data Source
This research involved a de-identified detailed analysis of the data obtained from the WA
Hospital Morbidity Data System for ten fiscal years from 1999/00 to 2008/09. This research
has been conducted in full accordance with the World Medical Association Declaration of
Helsinki, and ethics approval was granted by the Ethics Committee of the University of
Western Australia. Children were not directly involved in the study, as this was only an
analysis of de-identified hospitalisation data, as provided by the Health Department of
Western Australia. These admissions included all children hospitalised for oral treatment at
WA including the day surgery for the study period. Demographics including age-adjusted
rates and percentages of variables were previously published (Alsharif et al., 2014a).
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7.3.2. Principle Diagnosis
Principal diagnosis, classified by the International Classification of Diseases (ICD-10AM)
system, was obtained for every child under the age of 15 years diagnosed and accordingly
admitted for an oral health condition in Western Australia for the study period. All principal
diagnoses of oral health conditions (ICD-10AM) were included in the analysis. The ICD–10–
AM ’is the Australian Modification of the revision 10 of the International Classification of
Diseases (ICD–10). It is the ‘standard classification scheme now used for reporting diagnoses in
all hospital statistical collections, including the National Minimum Data Set and the Hospital
Casemix Protocol’ (Commonwealth Department of Health and Aged Care, 2000).
7.3.3. Determination of Direct Cost
Across Australia, the Australian Refine Diagnosis Related Group (AR-DRG) is used to
calculate the cost of each patient episode on the basis of actual data about the treatment
process. It is considered that Australia is a model example of a mature costing system and
has the most sophisticated approach according to cost guidelines that include the actual
amount of resources used in the treatment of a particular patient (Raulinajtys-Grzybek,
2014). Therefore, AR-DRG version 5.1 was used to calculate the direct cost (the Australian
dollar value used according to the year of admission). AR-DRG ‘is an Australian admitted
patient classification system which provides a clinically meaningful way of relating the number
and type of patients treated in a hospital (that is, it’s casemix) to the resources required by the
hospital’. Each AR-DRG represents ‘a class of patients with similar clinical conditions requiring
similar hospital services’ (Australian Institute of Health and Welfare, 2013b). The
categorisation classifies ‘acute admitted patient episodes of care into groups with similar
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conditions and similar usage of hospital resources, using information in the hospital morbidity
record such as the diagnoses, procedures and demographic characteristics of the patient’
(Australian Institute of Health and Welfare, 2013b). AR-DRG cost based on age, gender and
Indigenous status, insurance status, hospital area and hospital type of each child were
analysed.
Remoteness/accessibility. Direct cost based on remoteness was determined using the
Accessibility/Remoteness Index of Australia (ARIA) classification, which measures
‘remoteness in terms of access along the road network from populated localities to each of five
categories of Service Centre. Localities that are more remote have less access to service centres;
those that are less remote have greater access to service centres’ (Australian Population and
Migration Research Centre, 2013).
Socioeconomic status. DRG based on socioeconomic status was analysed using Socio-
Economic Indexes of Area (SEIFA) classification. SEIFA is a nationally accepted coding
developed by the Australian Bureau of Satatistics, which ‘ranks areas in Australia according
to relative socioeconomic advantage and disadvantage based on information from the five-
yearly Census’ (Australian Bereau of Statisitics, 2013a).
7.3.4. Indirect Cost
Based on previous study, indirect costs were predicted at approximately 1.5 times the direct
cost (Drummond et al., 1997), and because DRG is a direct cost, this method has been used
to calculate the indirect costs. Indirect costs include the following: patient and
parents/guardians’ absence from school or work due to pain and discomfort or having to
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112
accompany the child; cost of transportation and accommodation and societal losses of
productivity.
7.3.5. Statistical Analysis
To determine significant differences between continuous variables and nominal
(categorical) variables, Kruskal-Wallis test was used when appropriate. Significant levels
were set at 95% with P value less than 0.05 deemed to be significant.
SPSS 21 for Windows (Statistical Package for the Social Sciences; SPSS, Chicago, IL USA)
software and Excel 2007 (Microsoft, Redmond, WA, USA) are used for analysis.
7.4. Results
From 2000 to 2009, a total of 43,937 children (0–14 years) were admitted to hospital for oral
health-related conditions. Of these, 5% (n=2119) were Indigenous children.
7.4.1. Direct cost (All children)
The total DRG cost of these admissions was approximately AUD $92 million with an
estimation of additional AUD $138 million indirect cost (Table 7.1).
Age in years on admission. Costs were higher for children younger than 9 years (DRG 68
million) compared with 10- to 14-year-old children (DRG 25 million) (P < 0.01; Table 7.1).
Gender. The cost did not vary substantially by gender (Table 7.1).
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113
Indigenous status. Approximately 95% of the total cost of hospitalisation for oral conditions,
over the last decade, was accounted for non-Indigenous children. The difference between the
DRG cost of hospitalisation among Indigenous children and non-Indigenous children was
statistically significant, χ2(1) = 68.3 (P < 0.01), with a mean rank DRG cost of 24,185 for
Indigenous and 21,857 for non-Indigenous (Table 7.1).
Hospital type. Fifty-nine and 41% of the hospitalisation costs were incurred in private and
public hospitals, respectively. The difference between the DRG cost of hospitalisation among
private and public hospital was statistically significant, χ2(1) = 43 (P < 0.01), with a mean
rank DRG cost of 21,457 for private hospitals and 22,267 for public hospitals (Table 7.1).
Location. Children living in metropolitan areas accounted for the highest proportion (86
percent) of oral hospitalisation costs. The DRG cost among children living in urban areas was
significantly higher than rural living children, χ2(1) = 172.5 (P < 0.01), with a mean rank DRG
cost of 22,300 for urban areas and 20,072 for rural areas (Table 7.1).
Socioeconomic status. The oral condition-associated costs of hospitalisation were much less
for the most disadvantaged children (17 percent of the total cost) when compared with the
other socioeconomic groups (Table 7.1).
Remoteness/accessibility. The proportion of admissions decreased with increasing
geographic remoteness. Therefore, total disease-attributable costs of oral hospitalisation
varied significantly by ARIA, χ2(1) = 67 (P < 0.01), with a mean rank DRG cost represented
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114
in table 7.1. The direct DRG cost of hospitalisation of children living in accessible areas was
12 times higher than children living in very remote areas.
Insurance status. The cost of hospitalisation of insured children was higher than their
uninsured counterparts by approximately $5million AUD. (Table 7.1)
Cost per condition over time. In 2000, the direct cost of child (younger than 14 years old)
hospitalisation for oral related conditions reached about $6 million AUD. Since then the cost
had more than doubled to $13 million AUD in 2009 (Figure 7.1). The variations over time
were statistically significant (P < 0.01).
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115
Table 7.1 The Australian Refine Diagnosis Related Group cost of hospitalisation of Western Australian children based on different variables
Variable Subcategory Mean
Rank
N Cost (DRG)
in million**
Indirect Cost
in million**
Total
All children 19,975 43,937 92 138 230
Age (years) 0–4 20,631 16,367 34 52 86
5–9 23,183 15,862 33 49 82
10–14 22,195 11,708 25 37 62
Gender Male 21,667 22,728 48 71 119
Female 22,292 21209 44 67 111
Indigenous * Indigenous 24,185 2,119 5 7 12
Non-Indigenous 21,857 41,818 87 131 218
Hospital type* Public 21,473 17,303 38 57 95
Private 22,283 26,591 54 81 135
Commonwealth 27,254 43 0.089 0.133 0.222
Hospital area* Urban 22,300 37,412 79 119 198
Rural 20,072 6,525 13 19 32
SEIFA Most disadvantage 21,525 7202 15 23 38
Below average disadvantage 21,130 8133 17 25 42
Average disadvantage 21,630 8128 17 26 43
Above average disadvantage 22,315 8918 19 28 47
Least disadvantage 22,560 11422 24 36 60
ARIA* Highly Accessible 22,506 8690 19 28 47
Accessible 21,786 26162 55 82 137
Moderately Accessible 20,923 4720 10 15 24
Remote 21,120 2043 4 6 11
Very remote 22,808 2092 4 7 11
Insurance
status*
Insured 22,569 23134 48 73 121
Un-insured 21,302 20803 44 65 109
P < 0.001, Kruskal-Wallis test
** AUD $ = Australian Dollar
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116
Figure 7.1 The Australian Refine Diagnosis Related Group cost of dental hospitalisation of Western
Australian children over time in million.
*AUD $ = Australian Dollar. Amount expressed in constant dollars to account for inflation
7.4.2. Direct cost (based on the most common oral conditions)
Of all admitted cases 94% (n=41,475) accounted for seven major categories of oral
conditions with half (50%) of those hospitalisations for ‘dental caries’, which cost
approximately $45 million AUD. This was followed by, ‘embedded and impacted teeth’
(14%= $12 million AUD), ‘pulp and periapical’ tissue conditions (11%= $10 million AUD),
‘developmental and birth defects’ (5%= $4.5 million AUD), and ‘dental fractures’ (5%) and
‘dentofacial anomalies’ 4%, which costs around $4 million AUD each (Table 7.2).
Age in years on admission. Oral health-related hospitalisation costs did differ by age group.
The highest costs were significantly accounted for 5- to 9-year-old children who were
0
2
4
6
8
10
12
14
dir
ect
co
st in
AU
D $
*(i
n M
illio
ns)
DRG cost
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117
hospitalised for ‘dental caries’, pulp and periapical’ or ‘developmental defects’ (P < 0.01).
‘Embedded and impacted teeth’ significantly incurred the highest costs among 10- to 14-
year-old (P < 0.01). However, in the younger than 5-year-old group, the highest
hospitalisation costs were incurred by the conditions classified as ‘dental fracture’ or ‘birth
defects’ (Table 7.2).
Indigenous status. Non-Indigenous child hospitalisation costs were significantly higher than
those of Indigenous children across the condition categories of ‘birth defect’, ‘developmental
defects’, ‘dental caries’ and ‘pulp and periapical conditions’ (P < 0.01; Table 7.2).
Gender. It has been observed that hospitalisation costs for ‘embedded and impacted teeth’
conditions were significantly higher among females than males (P < 0.01; Table 7.2).
Socioeconomic status. Significantly higher costs were observed among children living in least
disadvantage areas admitted for ‘dental caries’ conditions (P < 0.01). However, of children
admitted with ‘pulp and periapical’ conditions, the admissions costs of children living in the
most disadvantaged areas were 1.5 times higher than the admission cost of those living in
the least disadvantaged areas (P < 0.01; Table 7.2).
Remoteness/ accessibility. Across all conditions, the majority of hospitalisation costs were
driven by children living in accessible areas (Table 7.2). These variations were significantly
higher among children hospitalised for ‘developmental defects’, ‘dental caries’ or ‘pulp and
periapical’ conditions (P < 0.01).
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118
Insurance status. The cost of insured children admitted due to ‘dental caries’, ‘embedded and
impacted teeth’ or ‘developmental defects’ conditions were more likely to be higher than
those without insurance admitted with the similar conditions. However, the cost of insured
children hospitalised as a result of ‘pulp and periapical’, ‘birth defects’ or ‘dental fracture’
conditions were lower than those without dental insurance hospitalised with parallel
conditions (Table 7.2).
Hospital type. The highest admission costs of ‘dental caries’, ‘embedded and impacted teeth’
or ‘developmental defects’ were significantly incurred in the private sector (P < 0.01). For
‘dental fracture’, ‘birth defects’ and ‘pulp & periapical’ conditions, the greatest children
hospitalisation costs, were incurred in public hospitals (P < 0.01; Table 7.2).
Location. The admission costs for all common conditions (except ‘dental caries’ and
‘embedded and impacted teeth’) were significantly higher among children living in rural
areas, when compared with their urban living counterparts (P < 0.01). Conversely, the cost
of hospitalisation of children with ‘dental caries’ or ‘embedded and impacted teeth’
conditions living in metropolitan areas were 5.5, and 5.2 times higher than their rural living
counterparts, respectively (Table 7.2). However, the admissions cost of rural living children
(admitted for birth defects, pulp and periapical or dentofacial anomalies condition) were
significantly higher among urban living counterparts (P < 0.01).
Cost per condition over time. Figure 7.2 shows that the costs of hospitalisation for common
oral conditions except ‘dental caries’ were nearly doubled in 2009 (P < 0.01). However, the
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119
admission cost of ‘dental caries’ in 2009 was almost threefold higher than the admission cost
of children in 2000 (P < 0.01).
Table 7.2
The Australian Refine Diagnosis Related Group cost (in $ millions) of hospitalisation of Western
Australian children based most common oral conditions and different variables
AR-DRG cost based on Variables
(AUD)*
Dental
fracture
Birth defect Developmental
defects
Embedded &
impaction
Dental
caries
Pulp &
periapical
Dentofacial
anomalies
All children 4.1 6.5 4.5 11.9 44.8 9.5 3.8
Age
0–4 3 5.1 0.7 0.04 19.7 4.2 0.08
5–9 0.7 0.8 2.2 0.9 21 4.6 0.7
10–14 0.3 0.6 1.6 10.9 4.1 0.7 3
Indigenous
status
Indigenous 0.3 0.3 0.04 0.03 2.4 1.1 0.01
Non-Indigenous 3.8 6.2 4.46 11.86 42.4 8.4 3.8
Gender
Male 2.4 3.7 2.4 4.9 23.6 5.3 1.6
Female 1.7 2.8 2.2 7 21.2 4.2 2.2
SEIFA
Most disadvantage 0.8 1.2 0.5 1 7.7 2.4 0.4
Below average disadvantage 0.83 1.3 0.6 1.8 4.1 2.2 0.5
Average disadvantage 0.82 1.3 0.8 2.4 8.1 1.6 0.7
Above average disadvantage 0.73 1.3 1 2.8 8.9 1.7 0.8
Least disadvantage 0.9 1.4 1.6 3.9 16 1.6 1.4
ARIA
Highly accessible 0.8 1.2 0.8 3 8.6 2 0.7
Accessible 2.7 4.1 3 6.7 25.4 5.6 2.4
Moderately accessible 0.3 0.7 0.4 1.4 5 0.9 0.4
Remote 0.1 0.2 0.2 0.5 2.2 0.4 0.2
Very remote 0.2 0.3 0.1 0.2 3.6 0.6 0.1
Insurance status Insured 1.5 2.8 3.2 8.5 23.7 2.5 2.8
Uninsured 2.6 3.7 1.3 3.4 21.1 7 1
Hospital
type
Public 3. 4.4 0.8 1.1 15.8 7.5 0.9
Private 0.5 2.1 3.7 10.8 28.9 2 2.9
Commonwealth 0 0 0.004 0.008 0.07 0.009 0.002
Hospital
area
Rural 3.7 6.1 4.1 1.9 6.9 8.2 3.2
Metropolitan 0.4 0.4 0.4 10 37.9 1.3 0.6
*AUD $ = Australian Dollar
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120
Figure 7.2 The Australian Refine Diagnosis Related Group cost of Western Australian children by condition, over time.
*AUD $ = Australian Dollar. Amount expressed in constant dollars to account for inflation.
7.5. Discussion
This study indicates that, over time, the hospital admissions for dental reasons (in children)
were associated with an increasing economic burden on Australian dental health
expenditure. A steady but significant rise can be seen in the oral health-related admission
rates of children over the period (Alsharif et al., 2014a). As the average cost per admission
has increased, this inevitably led to an increase in total costs. Most of these funds went
towards treating ‘dental caries’ and ‘embedded and impacted teeth’ conditions. This is
consistent with previous studies (Tennant et al., 2000; Kruger Dyson, & Tennant, 2006).
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Co
st in
AU
D$
*(i
n M
illio
ns)
years
Embedded & Impacted teeth
Fracture & dislocated tooth
pulp & periapical
Developmental defects
Birth defects
Dental caries
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121
Significant cost differences were found based on age, with children younger than 5 years old,
incurred the highest admission costs as a result of traumatic dental fracture or birth defects
(mainly cleft lip and palate). On the other hand, among children aged between 5- and 9-
years-old, the highest admission costs of dental caries or pulp and periapical conditions
might be attributed to the fact that children at this age generally have deciduous teeth that
were exposed to cariogenic factors for a longer time. This explanation is supported by finding
low costs of dental caries admissions for children in the oldest age group, as new healthy
permanent dentition is present. In addition, older children are able to cope better with dental
treatment under local anesthesia than younger children (Nsour & Almoherat, 2013).
However, the greater cost related to treatment for embedded and impacted teeth at this age
group was mainly attributable to the impaction of maxillary permanent canine that is
common oral pathological finding reported after 12 years of age, especially among those
seeking orthodontic treatment. Moreover, it has been evident that an impacted canine is
twice more likely to be common in females than males (Litsas & Acar, 2011).
The Indigenous population is disadvantaged across a range of socioeconomic conditions that
sequentially affect child health outcomes. The literature is replete with evidence that
Indigenous children experience worse oral health than their non-Indigenous counterparts
(Australian Institute of Health and Welfare, 2007; Smith et al., 2007), but this is not reflected
in the costs of hospitalisation among Indigenous children. These challenges in accessing
dental care are fundamentally linked to issues of affordability, lack of health-care service
(even SDS), and the proportion of insured Indigenous children. In addition, most Indigenous
children live in rural areas where dental health-care services may be sparse and located at
great distances from the patient.
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122
The structure of the dental system in Australia is largely private, consequently most
hospitalisations concerning oral problems for children take place in private hospitals with
both providers and services concentrated in major cities (Kruger Dyson, & Tennant, 2006;
Australian Institute of Health and Welfare, 2010). In an urban environment, health-care
services may be located closer in distance; therefore the availability of the service increases
the utilisation and consequently increases the cost. On the other hand, it might be obvious
that the greater costs of admissions in public hospitals were incurred by emergency oral
conditions, whereas the highest costs of admissions in private hospitals were incurred by
dental caries treatment and impacted teeth removals. Dental health insurance coverage is
known to be the dominant predictors of the private sectors utilisation of and access to dental
care. This is because of their ability to mitigate the costs of care (Alsharif, Kruger, & Tennant,
2014b).
Researches over the past decade have continued to show that low socioeconomic status
children suffer disproportionately from many dental diseases and a delayed access to the
health-care system that will increase their risk for other complications (Marshall & Spencer,
2006). However, our study indicates that hospitalisation costs of the most disadvantaged
group are low, except for ‘pulp and periapical’ conditions. This may be attributed to the fact
that children only access dental health care when conditions reached an advanced stage that
requires admission for more invasive treatment, and accordingly a much greater public
expense, than if they had been provided dental treatment or prevention in early stages.
Furthermore, for children living in remote regions of the state where access to dental care is
difficult, resulting in long delays in the provision of treatment and, most likely, significant
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123
morbidity associated with dental pain and oral infection. Additionally, travelling to distant
centres for treatment under general anesthesia by specialist pediatric dentists has become
the usual method by that treatment is provided to the majority of affected children. In this
context, the costs which accounted primarily for this significant difference were travel and
treatment costs associated with hospitalisation and the administration of general anesthesia
(Milnes, Rubin, Karpa, & Tate, 1993). Many parents, especially rural-based or Indigenous,
cannot afford such high hospitalisation and treatment costs. Accordingly, a procedure such
as extraction of decayed teeth, which is relatively cheaper, is more preferable option.
However, when affordability and accessibility issues are overcome, the remote band groups
had significantly higher costs than groups that were located closer to treatment centres.
Over the last decade, there has been a substantial growth in hospitalisation costs for all
conditions particularly dental caries. This might be explained by the increase in child
population over the study period; however, hospitalisation rates also shows increases
(Alsharif et al., 2014a). It has also been anecdotally reported that in light of the recent global
economic crisis, overall dental treatment prices in Australia have increased well beyond
inflation, and the shift toward demanding more expensive private services has occurred.
Furthermore, it can be argued that a decline in the robustness of the current school dental
service approach has an impact on child dental hospitalisations, resulting in elevated costs
in WA. Figures of increasing cost over time would have implications for the future, indicating
a significant burden on the Australian health-care system.
In Australia dental care is not subjected to the tenets of the Australian Health Act, hence the
funding structure in the dental system is different to the rest of the health system in that
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124
individuals pay for the majority of their care. Although government funding is significant, the
subsidies available are far less than those provided in the general health system. The amount
of funding available to the public system is dwarfed by consumer expenditure in the private
system. However, historically, the United Kingdom included dental care in their National
Health Service system. Therefore, economic analyses in the United Kingdom and other
European nations are not generally applicable to Australia, given that different patterns of
dental care utilisation and payment systems between countries result in marked variations
in dental health-care expenditures.
7.6. Recommendations and Conclusion
In brief, our study concludes that it is important to prevent costly inpatient treatment by
early detection, prevention, and intervention as findings indicate a substantial economic
burden of child hospitalisation (for dental reasons) (Donly & Brown, 2005; Pienihakkinen,
Jokela, & Alanen, 2005; Splieth, Nourallah, & Konig, 2004; Davies, 2003). Therefore, with
limited public health resources, strategies are needed to focus on best practice principles of
care and demand management for better utilisation of available health resources. In our
view, tremendous monetary benefits are expected when primary prevention of dental caries,
especially in children, through SDS is implemented. The high economic burden of children
dental hospitalisation implies the need for health resources redistribution based on
a regional need in conjugation with the development of community-based preventive
programmes and treatment programmes.
125
Chapter Eight
8. Future Projections of Child Oral Health-related
Hospital Admission Rates in Western Australia.
This chapter was published in the following article:
Alsharif, Alla, Kruger, Estie & Tennant, Marc. (2016). Future projections of child oral health-
related hospital admission rates in Western Australia. Australian Journal of Primary
Health. http://dx.doi.org/10.1071/PY15132. (Appendix E)
Chapter Eight
126
8.1. Abstract
Objective: This study aimed to project the hospital admission rates of Western Australian
children for oral conditions, with a particular focus on dental caries, embedded and
impacted teeth, and pulp and periapical conditions through to the year 2026.
Material and Methods: Two methods (the linear method and the exponentially weighted
moving average) were used to generate projection data through to the year 2026, using
the Western Australian Hospital Morbidity Dataset for the period 1999–2000 to 2008–
2009.
Results: The projected admission rate increase in those children aged 14 years and
younger from 2000 to 2026 was 43%. The admission rates are expected to more than
double over time (7317 cases in 2026 compared to only 3008 cases in 2000) for those
children living in metropolitan areas. Dental caries, embedded and impacted teeth, and
pulp and periapical conditions will remain the top (mostly) preventable causes of
admission throughout this time.
Recommendations and Conclusion: Anticipating the future burden of oral health-
related hospital admissions in children, in terms of expected numbers of cases, is vital for
optimising the resource allocation for early diagnosis, prevention and treatment. A
concerted effort will be required by policymakers and oral health-care communities to
effect substantial change for the future.
Key words: dental care for children, hospitalised child, oral health.
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127
8.2. Introduction
Over the past 30 years, there have been significant improvements in the oral health of
Western Australian children, partly associated with the development of a comprehensive
school dental service (SDS) and public health measures, such as widely accessible fluoridated
water supplies (Kruger Dyson, & Tennant, 2006). As a result, the prevalence of dental disease
in children has diminished (Blinkhorn & Davies, 1996). However, dental caries are still a
major public health concern in most developed countries, affecting 60–90% of school-age
children, and their incidence is expected to increase significantly over time in many
developing countries (World Health Organisation, 2015). Oral health conditions are
responsible for the highest number of acute preventable hospital admissions and significant
cost to Australia (The Steering Committee for the Review of Government Service Provision,
2010), and cause considerable social concern within the community.
In Western Australia (WA) during 1999–2000 and 2008–09, dental conditions accounted for
933 and 1081 hospital admissions per 100 000 person-year (PY), respectively; these
numbers could be reduced by providing early access to appropriate services (Alsharif et al.,
2014a). The majority of cases were for dental caries and extractions. Dental conditions cost
the state more than $92 million over the last decade (Alsharif, Kruger, & Tennant, 2014c).
Overall, 546 cases per 100 000 children per annum were admitted for ‘dental caries’ and 144
admissions per 100 000 had ‘embedded or impacted teeth’ (Alsharif et al., 2014c). In
addition, a previous study has shown a clear urban–rural divide in child hospital admissions;
the estimated age-adjusted hospitalisation rates (AARs) of urban-dwelling children were
twice that of their rural-dwelling counterparts (Alsharif et al., 2014a).
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128
By 2040, the WA population is projected to double, with metropolitan areas remaining the
dominant population centres in the state (Australian Bereau of Statisitics, 2014a). Hence, an
increase in oral health-related conditions in children is expected to have a significant impact
on the demands for oral health services over the next 20 years. This is likely to be
exacerbated by limited resources and workforce shortages. Projections of oral health-related
admission rates and their associated costs need to be performed to inform policy, planning
and resource allocation. Previously, projections have led to better planning and resource
allocation (Madge, 2000; Goss, 2008; Australian Government Department of Health, 2009;
Australian Institute of Health and Welfare, 2014c; Health Workforce Australia 2014).
To date, there are no data available on future child oral-health hospitalisation demands in
Western Australia. An understanding of the projected incidence of children’s oral conditions
is a fundamental obligation to enable rational planning for monitoring and treatment of oral
conditions. Against this backdrop, the aim of this study was to analyse projected oral-health-
related admission rates of Western Australian children, with a particular focus on dental
caries, embedded and impacted teeth, and pulp and periapical conditions through to 2026,
based on 10 years of past hospitalisation data for robustness.
8.3. Material and Methods
8.3.1. Data Source
This study involved a de-identified detailed analysis of the data obtained from the Western
Australian Hospital Morbidity Dataset for the period 1999–2000 to 2008–2009 under ethics
approval from The University of Western Australia. A principal diagnosis was obtained for
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129
every child under the age of 15 years admitted for an oral health condition (in both private
and public hospitals) in WA for the study period, using the International Classification of
Diseases Tenth Revision Australian Modification (ICD-10-AM) system. All principal
diagnoses of oral health conditions (ICD-10-AM) were included in the analysis. The ICD-10-
AM ‘is the standard classification scheme now used for reporting diagnoses in all hospital
statistical collections, including the National Minimum Data Set and the Hospital Casemix
Protocol’ (Commonwealth Department of Health and Aged Care, 1998). Age and residential
area for each child were analysed. Future predictions for dental caries, embedded and
impacted teeth, and pulp and periapical conditions, which accounted for 75% of all
hospitalised conditions during the study period, were also analysed.
8.3.2. Data Analysis
All projections were based on Age-Adjusted hospitalisation rates (AARs), which were
calculated using the Health Statistics Calculator, a software package developed by the Health
Department of WA. Population data (denominators) for hospital admission rates were
obtained from estimations by the Health Department of WA. These estimations were based
on population data obtained by Australian Bureau of Statistics census surveys. Two separate
methods were used to project future cases (Gill, Codde, & Vasudaven, 1997). Both methods
accounted for the projected increase in both the population and the incidence of these
conditions, using ten years of data. The first method, the linear method, used historical data
to estimate a line of best fit for each 5-year age group, using the method of least squares.
Based on the estimated AARs, the future number of cases was determined. The second
method, the exponentially weighted moving average (EWMA), used historical trends to
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130
model future points equally. This method places greater weight on more recent data.
Applying the two methods separately resulted in very similar trends; therefore, only the
results of the linear method are presented. There is a general consensus among statisticians
that a relatively simple linear model of age-specific rates provides a good fit to the data while
giving reasonably accurate predictions over a short to medium time span (Australian Bereau
of Statisitics, 2014a). The accepted approach among statisticians preparing projections of
this nature is to assume a linear model for increasing rates to prevent projecting admission
rates below zero. Further, there is a fundamental presumption in this approach that the
factors that affect oral health-related admissions, such as risk indicators, change in an
approximately linear way with time for each age group (Australian Bereau of Statisitics,
2014a). This presumption holds on condition that there are no major quantitative changes
in any underlying factors, such as the introduction of an intervention program.
8.3.3. Cost Projections
Based on a previous study, Australian refined diagnosis-related groups (AR-DRGs) were
used to calculate the direct cost of each patient episode on the basis of actual data about the
treatment process (Alsharif, Kruger, & Tennant, 2015). Each AR-DRG represents ‘a class of
patients with similar clinical conditions requiring similar hospital services’ (Australian
Institute of Health and Welfare, 2013b). The DRG cost was divided into categories: low (0–
4000); middle (4001–10 000); high (10 001–20 000); and extremely high (20 001 and over).
The low-cost category was most representative of the overall cost distribution, which was
normally distributed. Therefore, low-cost was deemed appropriate to use in future cost
projections.
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131
Other data analyses were performed using SPSS 21 for Windows (IBM Statistical Package for
the Social Sciences, Chicago, IL, USA) and Excel 2007 (Microsoft, Redmont, WA USA).
8.4. Results
A total of 43 937 children (0–14 years) were admitted to hospital for oral-health-related
conditions over the study period. Of these, 15% (n = 6525) were rural-dwelling children.
8.4.1. Projections of all Oral Health-related Hospitalisations
Rates
Population projections through 2026 for WA indicated a significant increase (66%) in the
total population. The actual projected oral health-related admission rates increase in those
aged 14 years and younger from 2000 to 2026 is 43% (Figure 8.1). Of the total projected oral
health-related admissions, a 171% increase in hospitalisation rates of children aged 5–9
years is projected to occur in 2026. However, in 2026, a 23% decrease in hospitalisation
rates among children younger than 5 years is projected (Figure 8.1).
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132
Figure 8.1
Projection of children’s Age Adjusted hospitalisation Rates due to oral conditions over time
and based on age.
It is anticipated that the AARs will more than double (7317 cases in 2026 compared to only
3008 cases in 2000) for those children living in metropolitan areas (Figure 8.2). In contrast,
a slight reduction is projected in the AARs among rural-dwelling children (Figure 8.2).
0.00
500.00
1,000.00
1,500.00
2,000.00
2,500.00
AA
R p
er 1
00
,00
0 p
erso
n-y
ear
0-4
5-9
10-14
All ages
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133
Figure 8.2
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children based on
location.
The overall direct costs of all oral health-related child hospitalisations are estimated to
increase from $10 million in 2009 to $16 million in 2026, an increase of 61% (Figure 8.3).
From 2016 to 2026, oral hospital admissions will cost the state a minimum of AU$147 million
(Figure 8.3).
0
200
400
600
800
1000
1200
1400
1600
1800A
AR
PER
10
0,0
00
PER
SON
-YEA
R
Rural
Metropolitan
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134
Figure 8.3
The projected diagnosis-related group cost of dental hospitalisation of Western Australian
children through to 2026 in millions of dollars.
8.4.2. Projections of Dental Caries Hospitalisation Rates
Hospitalisation due to oral conditions among children is highly influenced by dental caries,
as this condition accounts for ~50% of all cases. Assuming hospitalisation rates will follow a
similar trend in future, it is projected that the overall AARs of dental caries will more than
double from 406 to ~937 cases per 100 000 PY between 2000 and 2026. With the
anticipated increases in the population, this equates to ~3742 new cases expected to be
hospitalised in 2026 (Figure 8.4). In addition, the overall AARs of hospitalisation in children
living in metropolitan areas is projected to rise from 417 to ~1190 cases per 100 000 PY
between 2000 and 2026, which equates to ~3982 new cases expected to be admitted in 2026
(Figure 8.5). A significant gap is predicted to occur in the future between the hospitalisation
rates of children living in rural areas compared to those living in metropolitan areas (Figure
8.5).
0
2
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2000 2005 2009 2016 2020 2026
DR
G C
ost
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Cost AUD
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Figure 8.4
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to caries
conditions based on age.
Figure 8.5
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to dental
caries based on location.
0
200
400
600
800
1000
1200
1400
1600
1800
2000
AA
R P
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8.4.3. Projections of Hospitalisation Rates for Embedded and
Impacted Teeth
The admission rates of children with embedded and impacted teeth are projected to stabilise
over the next decade, with children aged 10–14 years still accounting for the highest
admission rates (Figure 8.6). Although hospitalisation rates of children living in
metropolitan areas will decrease slightly over time, remarkable variations in admission rates
will continue to occur between rural- and urban-dwelling children (Figure 8.7).
Figure 8.6
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to
impacted or embedded tooth removal based on age.
0
50
100
150
200
250
300
350
400
450
500
AA
R P
ER 1
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All ages
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Figure 8.7
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to
impacted or embedded dental removal based on location.
8.4.4. Projections of Hospitalisation Rates for Pulp and
Periapical Treatment
The admission rates of children for pulp and periapical treatment are projected to stabilise
over the next decade and are expected to reach ~244 cases per 100 000 PY in 2026, an
increase of almost 66% from 2000 (Figure 8.8). The significant split in admission rates
between rural- and urban-dwelling children will continue through the next 10 years, with
children living in urban areas 2.4 times more likely to be admitted to hospital as a result of
pulpal and periapical conditions than their rural-dwelling counterparts (Figure 8.9).
0
20
40
60
80
100
120
140
160
180
200A
AR
PER
10
0,0
00
PY
Rural
Metropolien
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138
Figure 8.8
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to pulp
and periapical conditions based on age.
Figure 8.9
Age-adjusted hospitalisation rates projection to 2026 of hospitalised children due to pulp
and periapical dental conditions based on location.
0
50
100
150
200
250
300
AA
R P
ER 1
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,00
0 P
Y
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10-14
All ages
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180
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00
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AA
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Rural
Metropolitain
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8.5. Discussion
Although there has been a significant reduction in dental caries in children over the last
generations in Australia (as in other developed countries), the rates of oral health-related
hospital admissions among children have increased substantially over the past decade. The
annual rates of admissions in WA are predicted to increase significantly over the next 20
years. It is important to note that projections are not intended to function as exact forecasts,
but to indicate what might be expected if the stated assumptions were to apply over the
projected time frame. More recently, our team has revealed that the AARs of hospitalisations
for oral conditions increased from 926 in 2000 to 1085 cases per 100 000 PY in 2009
(Alsharif et al., 2014c). By 2026, the rates of avoidable hospitalisation and associated costs
are projected to increase. It is reasonable to predict that the number of children with oral
conditions will increase by an even greater percentage, as only school-registered children
are clinically diagnosed and treated within the limited SDS scope. An increase in age-
adjusted dental caries admission rates has been observed over the past 10 years and this
trend is likely to continue, resulting in an estimated 52% increase in the annual number of
admissions due to dental caries by 2020. If these trends continue, an estimated 83% increase
in dental caries admissions can be expected by 2026. The dramatic increase in the
anticipated number of dental caries in school-age children should be alarming to all those
concerned with planning and providing dental services to children in WA.
The projected rates of hospitalisation for embedded and impacted teeth removal/treatment
are expected to remain stable or decrease slightly. This might be attributed to the changing
rates of procedures as a result of changing trends in clinician beliefs, as well as changing
health insurance levels in the community. However, the authors believe that this trend is not
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expected to continue indefinitely and there will be an increase in the projected number of
cases admitted to hospital for the removal of embedded and impacted teeth among
disadvantaged children once they have access to appropriate services. This assumption is
based on the fact that disadvantaged children are at higher risk of systemic and metabolic
disorders, genetic disorders and deciduous teeth injuries, which are all causes of delay in
tooth eruption or impaction (Almonailiene, Balciuniene, & Tutkuviene, 2010).
It is predicted that there will be an increase in admission rates for pulpal and periapical
conditions in children aged 5–9 years old over the next 20 years as a result of population
growth and poor dental health service access. Long intervals between SDS visits might delay
interventions and early prevention; consequently, children only access care when dental
conditions have reached advanced stages. In addition, the lack of affordable dental care and
insurance coverage lead to the postponement of dental treatment, often for years. These
untreated symptoms inevitably become more severe, resulting in children requiring
admission for more invasive treatment at a much greater public expense than if they had
been provided dental treatment when the symptoms first occurred.
The health of rural- and remote-dwelling children in Australia is poorer than that of urban-
dwelling children for most indicators, including marked inequalities in oral health and oral
health services (Australian Institute of Health and Welfare, 2008b). Geographical access to
health services is clearly the reason for these inequalities in health. In metropolitan areas,
clinics are located mainly in community health centres, or on school or hospital grounds.
However, in some rural communities, mobile dental clinics provide limited oral health
services for children. This inequality is evident in the fact that children living in metropolitan
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areas are more likely to be admitted to a hospital for dental procedures than children living
in rural areas (Alsharif et al., 2014c). Children in rural and remote regions are also less likely
to have private health cover (Alsharif et al., 2014b), which plays an important role in the
private-driven oral health-care delivery system in Australia. Further contributing to
inequalities is the fact that WA is experiencing a dental workforce shortage in rural and
remote areas, especially in dental therapists and specialists (Steele et al., 2000).
Over the last decade, there has been substantial growth in hospitalisation costs for all oral
conditions, particularly dental caries (Alsharif et al., 2015). This cost-pressure scenario is
only expected to increase in the near future. As a result of the recent global economic crisis,
dental treatment prices in Australia are expected to increase well beyond inflation rates and
a demand for more expensive private services has occurred. In addition, a decline in the
robustness of the current SDS approach has had an impact on child dental admissions,
resulting in elevated costs in WA. The projected increasing costs will have implications for
the future, indicating a significant burden on the Australian health-care system.
Increases in the AARs of children admitted for oral conditions may be explained by several
factors. For example, demographic shifts in the Australian population will have a major
influence on the projected number of oral-condition cases in the future. Although evidence
indicates that some minority populations have higher oral-condition rates that are not
reflected by lower admission rates, additional increases in the projected admission rates are
expected once these groups gain access to the service. In addition to an actual increase in the
incidence of oral diseases, population growth (primarily in urban areas), workforce
shortages and misdistribution, changes in diagnostic and treatment practices, and limited
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resources for specific conditions, are likely to affect the future burden of these diseases.
These shifts will create a significant socioeconomic burden on the Australian dental health
system, since dental services are not covered by the principle of universal access. Clearly,
opportunities to target early intervention towards those at higher risk of the need for
admission, and to target primary and preventive services towards areas of need, are key
research and policy directions that come from this research.
8.6. Recommendations and Conclusion
Projections indicate increasing rates of oral health-related admissions among Western
Australian children, especially for dental caries, and pulp and periapical conditions. Oral
diseases among children have a considerable impact on the Western Australian community.
The rates of oral health-related admissions occurring in Western Australian hospitals each
year is an important measure of the burden of oral conditions in Australia and has
implications for resource allocation and planning. Investment decisions on the prevention of
oral conditions and treatment facilities, workforce planning and evaluation of oral health
policy rely not only on knowing how many cases were hospitalised in a given year, but on
how many can be expected to be admitted in the future. Therefore, a universal strategy is
needed to set the platform for oral health actions in WA into the next decade. Anticipating
the future burden of oral health-related admissions in children in terms of expected numbers
of cases is vital in optimising the allocation of resources to enable children to have timely
access to preventively focused dental care that meets the minimum standard benchmarks
for oral health service provision.
143
Chapter Nine
9. Identifying and Prioritising Areas of Child Dental
Service Need: A GIS-based Approach.
This chapter was published in the following article:
Alsharif, Alla, Kruger, Estie & Tennant, Marc. (2016). Identifying and prioritising areas of
child dental service need: A GIS-based approach. Community Dental Health. 33(1),
33-38. (Appendix F)
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9.1. Abstract
Objective: To identify and prioritise areas of high need for dental services among the
child population in metropolitan Western Australia.
Material and Methods: All children hospitalised due to an oral-condition from 2000 to
2009, at metropolitan areas of Perth were included in the analysis of a 10-year data set.
QGIS tools mapped the residential location of each child and socioeconomic data in
relation to existing services (School Dental Service clinics).
Results: The tables and maps provide a clear indication of specific geographical areas,
where no services are located, but where high hospital-admission rates are occurring,
especially among school-age children. The least-disadvantaged areas and areas of high
rates of school-age child hospital-admissions were more likely to be within 2km of the
clinics than not. More of high risk-areas (socio-economically deprived areas combined
with high oral health-related hospital admissions rates), were found within 2km of the
clinics than elsewhere.
Recommendation and Conclusion: The application of GIS methodology has identified a
community’s current service access needs, and assisted evidence based decision making
for planning and implementing changes to increase access based on risk.
Key words: Geographic Information System, hospital admissions, child oral health,
Australia.
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9.2. Introduction
With the substantial reduction in dental decay prevalence in child populations there is an
ongoing need for the systems that underpin care for this group to evolve in order to meet
changing oral health profiles. Consistent with the greater exposure of many societies to
fluoride, dental decay in children has diminished dramatically. In most developed countries
caries prevalence hovers around 50% of the population, and severity as measured by the
DMFT at age 12 years, is below two (Petersen, 2003). Caries experience in Australia is
consistent with these global measures (Mejia et al., 2012). Several countries have, for many
years, operated School Dental Services (SDS), which is (in various forms) a universal service
model to provide primary dental care to the child population. These services started their
existence in environments of high burdens of dental disease, and have adapted to falling
burden of dental disease by, for example, means testing, integration with adult services and,
in rare cases, cessation or outsourcing to private dental providers. With the majority of the
disease burden now resting with a small minority of children, the concept of targeting of
dental services to those in greatest need becomes a key to effective services. Results of our
previous studies indicated that Indigenous status, absence of private insurance, low
socioeconomic status and rural living are the most common risk indicators of decreased
receipt of preventive service or increased perceived unmet need (Alsharif et al., 2014a;b;
2015). In addition, it is well known that previous history of dental caries is the best indicator
of higher future risk. In this study, we used geographic information systems (GIS) method to
identify areas of need for primary dental services for children. GIS is a computational
approach to health planning is not new (Aronoff, 1989), and GIS technology has a distinct
component of geography or location that captures and represents features known as geo-
referenced or spatial data (Fun-Mun, Poh-Chin, & Ka-Win, 2008). Within the framework of
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health information management, GIS are able to answer health questions regarding ‘where
is what’ (Graves, 2008), and has come into use in health to describe and understand the
changing spatial organisation of the health care system, examining its relation to health
outcomes and access, and exploring how to improve health care delivery (McLafferty, 2003).
The aim of this study was to identify and prioritise areas of high need for dental services
among the child population in metropolitan Western Australia using the oral health related
hospitalisation data of all children over a ten year period.
9.3. Materials and Methods
Ethics approval to conduct the study was granted by the Ethics Committee of The University
of Western Australia RA/4/1/5502.
To identify the possible gaps in primary dental service provision to children, data from
metropolitan Western Australia (WA) were used. WA occupies the Western third of the
Australian continent; comprising an area of about 2.5 million sq.km with a population of
about half a million aged under 15 years (Australian Bereau of Statisitics, 2014b). Of those,
19% live in the capital city of Perth region (Australian Bereau of Statisitics, 2015). Perth was
used for this study as 73% of all hospital admissions for children under age 15 occurred in
the metropolitan area, and existing SDS clinics are located predominantly in that area. The
existing SDS in WA is a universal coverage model, providing free primary dental care to all
school registered children who choose to enrol in the service. Despite being a universally
applied system however, it reaches a under 30% of children (GWA DHS, 2008c). Some
parents who choose to not enrol their children can access private dental services, but this is
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not an affordable or accessible option for many. Since 2000, SDS coverage has been declining
rapidly, and more children are hospitalised for preventable oral related conditions (Spencer,
2012). Against this backdrop it is important that reliable methods are used to determine the
distribution of demand for SDS clinics, to inform policy development and service planning.
9.3.1. Hospitalisation Data:
Hospitalisation data were analysed for every 0- to14-year-olds, diagnosed and accordingly
admitted to hospital in WA for an oral health condition, as classified by the International
Classification of Disease –Tenth Australian Modification (ICD-10AM) (CDHAC, 1998). These
data were obtained from the WA Hospital Morbidity Dataset (HMDS) for 10 financial years,
from 1999/00 to 2008/09. Primary place of residence at the time of hospitalisation were
also analysed, using Statistical Local Areas (SLAs). A total of 37 SLAs cover WA without gaps
or overlaps, and their boundary files were obtained from the (ABS) website (Australian
Bereau of Statisitics, 2012a; b). Age adjusted Rates (AAR) of child hospital admissions per
SLA were calculated using the Health Statistics Calculator developed by the Health
Department of Western Australia and population data based on ABS census data. Based on
these admission rates per SLA, the entire child population was categorised into five quintiles,
separately for each age group.
9.3.2. Census Collection District (CD):
Admission data for each child was available at SLA level, but for higher accuracy and
precision analysis, a smaller area-based analysis was needed, and therefore census
Collection Districts (CDs) were used. A CD is much smaller than an SLA, and is a quasi-
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measure of density of residents (based on an area that a single census officer can collect data
from). Census collection districts and the geographic boundaries of each CD were obtained
from the ABS webpage (2011). The Perth metropolitan area covers 2,840 CDs, 65% of the
WA’s CDs, with more than 270,000 under 14-year-olds. Hospitalisation data across each of
the 37 WA SLAs were distributed by age groups (0–4, 5–9 and 10–14 years). For each age
group, the rates of child hospitalisations was calculated for each SLA then this SLA rate was
applied to each of the SLA’s CDs.
9.3.3. Population Data
The numbers of under 15-year-olds for each CD were obtained from the ABS (2006) census
data (Australian Bereau of Statisitics, 2013b).
9.3.4. Socioeconomic Status Data
Each CD has a Socio-Economic Indexes of Area score (SEIFA 2006) assigned by the ABS,
based on socioeconomic indicators of the CD’s population (Australian Bereau of Statisitics,
2013a). SEIFA is a nationally accepted coding system ranking areas in Australia according to
relative socioeconomic advantage based on five-yearly census data (Australian Bereau of
Statisitics, 2013a). These rankings were dichotomised into most disadvantaged areas
(Poorest, SEIFA deciles 1 to 5) and least disadvantaged areas (Wealthiest, SEIFA deciles 6 to
10).
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9.3.5. School Dental Service Locations:
The addresses of all fixed SDS clinics were obtained from the Department of Health
(Australian Bereau of Statisitics, 2011) and geocoded, i.e. changed into map coordinates and
located on a map. The populations of children who lived within 2km of each SDS clinic were
identified.
9.3.6. Geographic Information Systems (GIS)
GIS in this study were used as a technique for integrating hospitalisation data related to
dental disease with known risk indicators (e.g. socioeconomics), to identify and prioritise
geographic areas of high need for a dental service. The approach while tested on this one city
was designed to be universally applicable. The resultant maps indicated where SDS clinics
were located, as well as the following attributes of the child population both within and
outside of a 2km zone around it: population density, age-specific hospital admission rates
and an indication of area socioeconomic disadvantage.
All mapping and geocoding of data used QGIS v.2.6 (Boston, USA), analyses used SPSS 21 for
Windows and data were tabulated in Excel 2007.
9.4. Results
From 2000 to 2009, 31,910 metropolitan Perth children aged from 0–14 years were hospital
admissions for oral health-related conditions. All (77 fixed SDS clinics were included, with a
ratio of 2,414 school aged child population per clinic.
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The distributions of hospital admissions rates by both socioeconomic status and location
inside or outside 2km of a clinic are presented in Tables 9.1, 9.2 and 9.3. More children (68%)
lived within 2km of existing SDS clinics than further away. Of all children living within 2km
of a clinic, 18% of 0–4 year olds come from areas with higher (i.e. high or very high)
admission rates and low socioeconomic scores (poorest urban areas) (Table 9.1). In addition,
11% and 5% of 5–9 and 10–14 year-olds, respectively, were living in the poorest areas with
higher admission rates (Table 9.2 and 9.3).
Table 9.1
Zero to four years old child population distribution by hospital admission rates and
socioeconomic status inside/outside the 2km Zone of existing SDS clinics.
Admission
rates1
Inside the 2km zones Outside the 2km zones
Poorest areas Wealthiest areas Total Poorest areas Wealthiest areas Total
Very low 3,964 (7%) 7,791 (13%) 11,758 (20%) 1,153 (4%) 5,349 (20%) 6,502 (24%)
Low 4,656 (8%) 6,181 (10%) 10,837 (18%) 1,340 (5%) 4,525 (17%) 5,871 (22%)
Moderate 6,355 (11%) 6,947 (12%) 13,302 (23%) 967 (4%) 3,525 (13%) 4,492 (17%)
High 5,000 (8%) 7,170 (12%) 12,170 (20%) 1,077 (4%) 3,073 (11%) 4,150 (15%)
Very High 5,431 (9%) 5,528 (9%) 10,962 (18%) 1,950 (7%) 4,103 (15%) 6,080 (22%)
Total 25,406 (43%) 33,617 (57%) 59,029 (100%) 6,487 (24%) 20,575 (76%) 27,097 (100%)
1All admission rates per 100 000 population. (Very Low = 0-1141, Low = 1142-1183, Moderate=1184-1209,
High=1210-1299, Very High≥1300)
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Table 9.2:
Five to nine years old child population distribution by hospital admission rates and
socioeconomic status inside/outside the 2km Zone of existing SDS clinics.
Admission
rates1
Inside the 2km zones Outside the 2km zones
Poorest areas Wealthiest areas Total Poorest areas Wealthiest areas Total
Very low 8,046 (13%) 5,606 (9%) 13,652 (22%) 2,904 (10%) 3,059 (11%) 59,729 (21%)
Low 5,356 (9%) 7,161 (12%) 12,520 (21%) 1,229 (4%) 3,203 (11%) 4,438 (15%)
Moderate 5,287 (9%) 7,255 (12%) 12,545 (21%) 1,301 (5%) 3,226 (11%) 4,546 (16%)
High 4,567 (7%) 6,499 (11%) 11,066 (19%) 1,058 (4%) 5,240 (18%) 6,298 (22%)
Very High 1,884 (3%) 9,256 (15%) 11,140 (18%) 18 (0.1%) 7,115 (25%) 7,133 (25%)
Total 25,140 (41%) 35,777 (59%) 60,923 (100%) 6,510 (100%) 21,843 (100%) 28,387 (100%)
1All admission rates per 100 000 population. (Very Low = 0-1041, Low = 1042-1139, Moderate=1140-1209,
High=1210-1391, Very High≥1392)
Table 9.3
Ten to fourteen years old child population distribution based on hospital admission rates
and socioeconomic status inside/outside the 2km Zone of existing SDS clinics.
Admission
rates1
Inside the 2km zones Outside the 2km zones
Poorest areas Wealthiest areas Total Poorest areas Wealthiest areas Total
Very low 8,691 (13%) 5,356 (8%) 14,053 (21%) 2,186 (7%) 1,793 (6%) 3985 (13%)
Low 6,362 (10%) 9,564 (14%) 15,929 (24%) 1,605 (5%) 4,124 (13%) 5806 (18%)
Moderate 7,964 (12%) 9,103 (14%) 17,067 (26%) 1,708 (5%) 2,813 (9%) 4534 (14%)
High 2,346 (4%) 7,263 (11%) 9,609 (15%) 1,117 (4%) 8,130 (26%) 9247 (30%)
Very High 580 (1%) 8,042 (12%) 8,686 (13%) 43 (0.1%) 7,647 (24%) 7690 (24%)
Total 25,943 (40%) 39,328 (60%) 65,344 (100%) 6,659 (21%) 24,507 (78%) 31262 (100%)
1All admission rates per 100 000 population. (Very Low = 0-652, Low = 653-773, Moderate=774-817,
High=818-980, Very High≥981)
About a third of children live outside the 2km zones, 6% of them come from the poorest and
higher admission rates urban areas. Meanwhile, 41% of all the children are from the
wealthiest areas with higher hospitalisation rates and lived predominantly more than 2km
from a clinic (Tables 9.1– 9.3).
In this analysis, the term ‘highest risk areas’ refers to CDs with the poorest areas and having
high oral related hospital admissions rates; ‘lowest risk areas’ being the wealthiest with the
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lowest admission rates. Note that admissions were based on children’s addresses at the time
of admission. The locations of clinics were considered as a potential barrier to children’s
hospital admissions through access to early diagnosis and treatment.
Large geographical variations of high risk areas in relation to age, either outside of, or inside
the 2km zone of existing SDS clinics, were observed (Figures 9.1 and 9.2). More high risk
areas were observed among preschool aged children, regardless of their location in relation
to the clinics. High risk areas for children aged under 5 years were more likely to be within,
rather than outside of a 2km radius of a clinic. There were also more high risk areas within,
rather than outside 2km of clinics (Figures 9.1 and 9.2) for children older than 5 years. Most
high risk areas were in the peripheral areas of this particular metropolitan region.
Figures 9.3 and 9.4 compared the high oral related admission rates of children living in the
wealthiest areas, outside and inside the 2km zone of existing SDS clinics and reveal large
geographical variation. For the wealthiest areas, those with high admission rates of school-
age children were more likely to be within a 2 km of a clinic than further away. However,
many areas at risk of high (school-age children) hospitalisation rates were found more than
2km from a clinic, where no SDS service is available. Most wealthier areas with high
preschool child hospital admission rates, were concentrated in peripheral areas of this
metropolitan region.
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Figure 9.1
High age-adjusted oral related admission rates of children living in low socioeconomic areas
(SEIFA<6) inside 2km zones of existing School Dental Service clinics in Perth.
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Figure 9.2
High age-adjusted oral related admission rates of children living in low socioeconomic areas
(SEIFA<6) outside 2km zones of existing School Dental Service clinics in Perth.
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Figure 9.3
High age-adjusted oral related admission rates of children living in high socioeconomic areas
(SEIFA>5) inside 2km zones of existing School Dental Service clinics in Perth.
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Figure 9.4
High age-adjusted oral related admission rates of children living in high socioeconomic areas
(SEIFA>5) outside 2km zones of existing School Dental Service clinics in Perth.
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When comparing children of different age groups, from poorest/wealthiest areas, where
high risk of hospitalisations occur, differences were observed (Figures 9.1–9.4). Most areas
with high risk preschool admission rates, were from the poorest areas. In contract, most of
high risk school-age hospital admissions areas, were from the wealthiest areas, with a
significant number being in areas with worse SDS coverage.
9.5. Discussion
While there has been a significant reduction in tooth decay levels in children over the last
generation in Australia as in other developed economies, marked inequalities in oral health
still exist. Results of our earlier work on the incidence of oral related hospitalisations among
the child population of Western Australia were previously published (Alsharif et al., 2014a).
It has been determined that the total Diagnosis Related group (DRG) cost of these admissions
was AUD$92 million, with an estimated additional $138 million as indirect cost (Alsharif et
al., 2015). While hospitals are a vital component of any health system, the Australian dental
health care system is searching for ways to increase SDS coverage and reduce costs of
hospitalisations. One clear strategy is to increase the access to and utilisation of those
universal primary care and preventive services.
In the present study, integrated data from hospital admissions, socioeconomic population-
based indicators, and service locations, were used to form a cohesive risk-based geographic
output to support the spatial configuration of future service planning. The study
demonstrates an application of GIS to population-based oral health planning.
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The findings reflect the oral health profile disparities of a metropolitan population.
Preventable oral hospitalisations have been proposed as a key marker of poor health plan
performance (Australian Institute of Health and Welfare, 2014b). Currently, SDSs are the
main public child dental program in Australia, providing dental check-ups, emergency and
basic treatment, but cover only limited care for enrolled school children, particularly those
within disadvantaged families (NSW Oral Health Alliance, 2010). Treatment outside the
scope of the SDS is referred to other providers and any costs are the responsibility of the
parent or guardian (Government of Western Australian. Department of Health, 2008a). Many
studies confirmed that lower use of preventive health services, delay seeking primary care
and higher levels of oral diseases are observed among children living in low socioeconomic
areas, these untreated symptoms get more severe and admission for complex treatment may
be inevitable (Australian Bereau of Statisitics, 2010). However, admission rates do not reflect
the actual burden of the disease among disadvantaged groups possibly due to economic
constraints and reduced mobility.
On the other hand, a different admission pattern was evident among children from high SES
areas. These children were more likely to be admitted for oral conditions than those living
in more deprived areas. Based on our previous study using the same data set, 76% of
children in wealthy areas have private dental health insurance (compared to only 24% of
those in poor areas) which might indicate that insurance enabled improved access to dental
care and led to greater demand for hospital-based care once access had been obtained
(Alsharif et al., 2014b; Bagramian et al., 2009).
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This can be confirmed by the findings in Figures 9.3 and 9.4, where children from wealthy
areas are more likely to be admitted for oral related conditions than children living in poor
areas. Nevertheless, it is obvious from our previous analysis that insured, wealthy children
are more likely to be admitted for less invasive treatment than their most deprived
counterparts (who were probably more likely to receive invasive treatment), (Alsharif et al.,
2014a;b) despite individuals from poor backgrounds carrying a higher burden of oral
disease (Australian Institute of Health and Welfare, 2011a). In general, it is evident that
people from the most deprived areas were less likely to have taken preventive health actions
such as dental screening, or having their teeth cleaned (Australian Bereau of Statisitics,
1999). Our study findings suggested that variations in SES may lead to variations in utilising
complex health service based on need. This may contribute to widening oral health
inequalities among Australians, with more low-SES children requiring admission for more
invasive treatment which has a much greater public expense than if they had been provided
dental treatment when the symptoms first occurred.
The results and maps provide a clear indication of specific geographical areas (in this city)
where no local service is provided, but where high hospital admission rates occur especially
among school-age children.
Therefore, our findings provide valuable insights to the extent of child oral health admissions
in relation to access to existing services and deprivation mapped in detail across the city.
These findings provide a methodological approach that can be applied, not just locally, but
elsewhere to assist in planning resource allocation, prioritising services and targeting of
interventions.
Chapter Nine
160
9.6. Recommendations and Conclusion
This study has applied GIS methodology to identify a community’s current service access
needs, and informed evidence based decision making for planning and implementing
changes to increase access based on risk. The methods developed in this framework can be
adopted by other communities to identify a set of target areas with vulnerable populations
and subsequently to monitor the effectiveness of remedial interventions. This model may be
particularly well suited for planning and prioritising future health services in other urban
communities, based on population projections and disease models of the current population.
161
Chapter Ten
10. Discussion and Conclusion
Chapter Ten
162
10.1. Introduction
The Australian health care system’s fundamental goal is to ensure individual accessibility to
care based on need rather than ability to pay. Since the Australian Health Act does not
consider dental care as part of general health care, this goal has not been entirely met in
relation to oral or dental services. This compartmentalisation needs to be reconsidered as
oral health affects general health by causing considerable pain and suffering and by changing
their diet, speech and quality of life.
Australian child national surveys have found that there is an overall decrease in the average
number of decayed teeth over the past 30 years, however, since the late 1990s a gradual
increase has been noticed (Australian Institute of Health and Welfare, 2015). Australians’
oral health care is delivered through private practice or government-subsidised
programmes such as SDS, or through public hospital clinics for adults (Haas & Anderson,
2005). The existing SDS remains the only universal coverage model which is limited to school
registered children. In general, since 2000, SDS coverage has been declining, and at the same
time we have seen more children hospitalised for preventable oral related conditions
(Spencer, 2012). We now find that dental diseases has become the third most common cause
for having general anaesthetics in pre-school age Western Australian children (Sims et al.,
2005).
Previous research has reported a gradual increase in oral hospital admissions trend among
Western Australian children since the late 1990s (Tennant et al., 2000; Kruger Dyson, &
Tennant, 2006; Slack-Smith et al., 2009; Slack-Smith et al., 2013). Reports on those
Chapter Ten
163
admissions indicated that higher rates of hospitalisation were observed among children
living in rural areas, those of low SES and of Indigenous origin, and the highest admissions
were amongst pre-school aged children. Other study suggest that even adult hospitalisations for
oral-health-related conditions remain considerable, even though a large proportion might be
preventable (Kruger & Tennent, 2016). High hospital admission rates indicate an increase in
the prevalence of those conditions within the community, poor non-hospital care system
performance or, alternatively, an increasing use of the general anesthesia in the hospital
system for dental needs (Australian Institute of Health and Welfare, 2013a).
In terms of funding and access, the oral health care system does not operate in the same way
as the general health care system in Australia, and strategies to identify and address access
issues should be based on relevant and reliable information such as population based
studies. Little is known about the current trends in potentially preventable hospitalisations
over time in Western Australian children, as well as those groups in the population most at
risk, and the specific dental conditions leading to admissions. Against this backdrop it is
important to identify the recent trends of oral hospital admissions in children, as well as
identifying groups at higher risk for admission, in order to develop a reliable method to
determine the distribution of demand for SDS clinics which will enable precise policy
development and service planning.
10.2. Trend of Children Oral Health-related Hospitalisation
The study (Chapter 5) aims to analyse a decade of potentially avoidable children oral related
hospital admissions in Western Australian children under the age of 15 years, examining
associations with socio-demographic characteristics and with particular focus on dental
Chapter Ten
164
decay and Indigenous children. In contrast to the null hypothesis, the results identified
groups within the child population more likely to be admitted to hospital for treatment of
oral conditions. The results of Chapter Five showed that Kruger et al.’s (2006) population
had similar trends of school aged child dental hospital admission rates to our population.
However, differences were observed between the two studies when pre-school child
admission rates were compared; suggesting that there is somehow an increase access to oral
preventive services among this particular group or a changing rates of procedures over time
might be a result of changing trends in clinician beliefs, as well as changing health insurance
levels in the community; no specific reason for change is evident.
Although Indigenous status, poverty and rural/remote dwelling are all risk indicators for
admission to hospital for dental conditions, WA children admission rates were higher among
non-Indigenous children, and those living in least disadvantaged metropolitan areas. The
differences observed are thought to be attributed to several factors. One of those factors is
the fact that Western Australia is experiencing a dental workforce shortage in rural and
remote areas, especially in terms of dental therapist and dental specialists (Steele et al.,
2000). This unequal distribution can also be attributable to the variation in geographical
access to health services (Steele et al., 2000).
As health insurance coverage has previously been found to be a good predictor of preventive
care service use (Kenney et al., 2005; Harford & Luzzi, 2010), this thesis (Chapter 6) has
examine the disparities in dental insurance coverage among WA children admitted for oral
related conditions and associated factors to address the equalities that currently exist. It is
apparent that there are statistically significant disparities in dental insurance coverage
Chapter Ten
165
among hospitalised children associated with Indigenous status, socioeconomic status and
remoteness and accessibility of residential area, which might reflect the socio-demographic
and economic barriers to dental service utilisation. The results of this thesis confirm that as
a result of inadequate health insurance coverage in privately driven market, numerous
concerns about dental service utilisation are raised. Those children who did have dental
health insurance were more likely to come from urban, accessible and least disadvantaged
areas. This result is of a particular significance because it indicates that insurance enabled
access to dental care and led to greater demand for care once access had been obtained.
Although private dental insurance does not necessarily increase receipt of preventive service
or decrease perceived unmet need in all cases, it is evident that insured children are more
likely to be hospitalised for less invasive treatment than their uninsured counterparts
(Chapter Six). Kasper et al. (2000) found that the uninsured individuals were more likely to
have difficulty obtaining health care once they lost coverage. However, those uninsured
individuals that did gain private health cover had increased access to health services
compared with those that remained uninsured (Kasper et al., 2000). In terms of health status,
it is suggested that individuals losing coverage might experience adverse health outcomes
compared with those that remained insured (Kasper et al., 2000).
Therefore, there is now evidence (Chapter Six) that having private health insurance
increases access to dental care and possibly improves oral health status, and the disparities
observed in regards of dental insurance could attributed to subtle variations between the
different subsets of the population. The Australian government provided a ‘safety-net’
system (SDS) as a way to provide free or reduced fee dental care to uninsured children.
However, these sources of care are not always accessed and, as the numbers of poor and
Chapter Ten
166
uninsured increase, the ‘safety-net’ health system will be unable to bear the burden of
providing dental health care to all of the uninsured. In addition, any further invasive
treatment is referred to other providers and any costs are the responsibility of the parent.
As the United Kingdom included dental care in their National Health Service system,
economic analyses in the UK and other European nations are not generally applicable to
Australia, given that different patterns of dental care utilisation and payment systems
between countries result in marked variations in dental health care expenditures. Therefore,
(Chapter Seven) aims to analyse the economic cost of a decade of dental hospital admissions
in Western Australian children under the age of 15 years, and to identify socio-demographic
characteristics associated with these costs. When costs were estimated using DRG, a
substantial growth in hospitalisation costs for all conditions particularly dental caries were
observed. Admittedly, the child population increased over the study period, but not just did
this result in increasing absolute numbers of hospitalisations, but there was an increase in
rates of hospital admissions (Chapter Five). It has also been anecdotally reported that in light
of the recent global economic crisis, overall dental treatment prices in Australia have
increased well beyond inflation, and the shift toward demanding more expensive private
services has occurred. Furthermore, it can be argued that a decline in the robustness of the
current school dental service approach has an impact on child dental hospitalisations,
resulting in elevated costs in WA. Figures of increasing cost over time would have
implications for the future, indicating a significant burden on the Australian health care
system.
The literature is replete with evidence that the socioeconomic disadvantage experienced by
rural living Indigenous people places them at greater risk of exposure to behavioural and
Chapter Ten
167
environmental health risk indicators (Australian Institute of Health and Welfare, 2007a;
Smith et al., 2007), however, this is not reflected in the hospital admission rates and
associated costs (Chapter Five & Seven). Although the Government funding is significant, the
subsidies available are far less than those provided in the general health system. The amount
of funding available to the public system is dwarfed by consumer expenditure in the private
system. Therefore, these challenges in accessing dental care are fundamentally linked to
issues of affordability, lack of health care service (including SDS) and the proportion of
uninsured children. Therefore, an understanding of the projected incidence of children’s oral
conditions is a fundamental obligation to enable rational planning for monitoring and
treatment of oral conditions.
By 2040, the WA population is projected to double; with metropolitan areas remaining the
dominant population centre in WA (Australian Bereau of Statisitics, 2013b). Hence, an
increase in oral health-related conditions in children is expected to have an enormous impact
on the demands for oral health services over the next 20 years, particularly with limited
resources and workforce shortages. Unfortunately, there were no data available on future
child oral health hospitalisation demands in Western Australia. Against this backdrop
(Chapter Eight) aims to project future oral-health related admission rates of Western
Australian children through to the year 2026, based on 10 years of past hospitalisation data
for robustness. The rates of oral related hospital admissions among children have
substantially increased over the past decade (Chapter Five). Subsequent to this, the annual
rates of admissions in Western Australia are predicted to increase significantly over the next
20 years. It is also reasonable to predict that the number of children with oral conditions will
increase by an even greater percentage, as only school registered children are clinically
Chapter Ten
168
diagnosed and treated within the limited SDS scope. Increases in the AAR of children
admitted for oral conditions over time may be explained by a number of possible factors. For
example, the demographic shifts in the Australian population have a major influence on the
projected number of oral condition cases for the future. Although, evidence indicates that
some minority populations have higher oral condition rates which is not reflected by lower
admission rates, additional increases in the projected admission rates are expected once
they get access to the service. In addition to a true increase in the incidence of oral diseases,
population growth primarily in urban areas, workforce shortages and maldistribution,
changes in diagnostic and treatment practices, along with limited resources for specific
conditions impact the future burden of these diseases. Those increases will create a
significant socioeconomic burden on the Australian dental health system, since dental
services are not covered by the principle of universal access. This was in general agreement
with Kruger & Tennant (2015a,b) preliminary study which reported that projections
indicate that if current trends are set to continue, hospitalisations for oral health-related
conditions among Western Australians older than 65 years will place a considerable burden
on the health system.
10.3. Trends of Children Oral Health-related Hospitalisation for
Most Prevalent Conditions
An analysis of oral related hospital admissions indicated that most hospitalisation were for
‘dental caries’, ‘embedded and impacted teeth’ and ‘pulp and Periapical’ conditions. The
outcome is similar to other studies which have obtain reliable results indicating an increase
Chapter Ten
169
in the hospital admission rate of ‘dental caries’ over time. When establishing differences at
the population level, males, non-Indigenous, insured, living in least deprived urban areas
exhibited significantly higher rates of hospitalisation due to ‘dental caries’. Across all ages,
primary school age, followed by pre-school age groups experienced higher admission rates
due to ‘dental caries’. The admission cost of ‘dental caries’ in 2009, was almost three-folds
higher than the admission cost of children in 2000. Higher hospital admission costs were
observed among children aged younger than 9 years, non-Indigenous, living in accessible
metropolitan areas. Approximately, 95% Indigenous children, who were admitted for dental
caries treatment, were uninsured, in contrast to 45% of non-Indigenous children. Another
point of interest is that the projected overall AAR of dental caries is expected to more than
double by 2026. The dramatic increase in the anticipated number of dental caries in school
age children should be alarming to all those concerned with planning and providing dental
services to children in Western Australia. Additional analysis revealed a massive gap is
observed to occur in the future between the caries related hospital admission rates in
children living in rural areas when compared to their metropolitan counterparts.
The data obtained for Chapter Five, demonstrated there are significant differences in
hospitalisations for ‘embedded and impacted teeth’ between non-Indigenous and
Indigenous children. Non-Indigenous children were 29 times more likely to be admitted for
impacted teeth removal than Indigenous counterparts. This result is of a particular
significance because it demonstrates how private health cover plays an important role in
dental health-care delivery in Australia, as non-Indigenous children were more likely to be
covered than Indigenous children. However, hospitalisation among the older group is
unlikely to be due to third molar impaction, as maxillary canine is common oral pathological
Chapter Ten
170
finding reported in children aged 11-14 years, especially those seeking orthodontic
treatment (Manne et al., 2012; Litsas& Acar, 2011). Embedded and impacted teeth removal
was predominantly undertaken in the private sector which is not managed through policy
directives. ‘Embedded and impacted teeth’ significantly incurred the highest costs of
admissions among 10–14 year-olds, children living in least disadvantage and metropolitan
areas. The projected rates of hospitalisation for embedded and impacted teeth removal are
expected to remain stable or decrease slightly. This might be attributed to early detection of
permanent canine displacement, and early intervention by removal of the retained
deciduous canine which has been proven to improve the angulation and eruption of an
ectopic permanent canine (Ericson & Kurol, 1986a). However, the authors believe that this
constant trend is not expected to continue indefinitely and there will be an increase in the
projected number of cases admitted to hospital for embedded and impacted teeth removal
among disadvantaged children once they have access to appropriate services. Unless SDS
providers in WA incorporate canine’s eruption assessment into their routine examination of
the child’s dental development from the age of 8. Thus, when possible canine impaction is
suspected further diagnostic tests and extraction of the retained deciduous canine may be
required. Previous international comparison revealed significant differences in rates of
admission for impacted teeth, with England having rates approximately five times less than
France, and seven times less than Australia. Those results could be explained by the
implementation of guidelines in the United Kingdom, and the absence of similar guidelines
in France and Australia (Anjrini et al., 2014). On the other hand, although hospitalisation
rates of children living in metropolitan areas will slightly decrease over time, remarkable
variations in the admission rates will continue to be observed between rural and urban living
children.
Chapter Ten
171
Hospitalisations for ‘pulp and periapical’ conditions were mainly due to periapical abscess
without sinus formation. It is not surprising that uninsured, Australian Indigenous male
children aged less than 9 years, and living in the most disadvantaged areas were more likely
to be admitted for this condition. When determining the insurance status of children
admitted for pulp and periapical conditions, both Indigenous and non-Indigenous children
revealed inadequate health coverage. The highest costs of admission for pulp and periapical
were significantly accounted for 5–9 year old children. Additional analysis revealed that
hospitalisation costs of the most disadvantaged group are low for all oral conditions, except
for ‘Pulpal and periapical’ conditions. This may be attributed to the fact that children only
access dental health care when conditions reached an advanced stage which requires
admission for more invasive treatment, and accordingly a much greater public expense, than
if they had been provided dental treatment or prevention in early stages. Even assuming the
current hospitalisation rates, it is been projected that the admission rates of children for pulp
and periapical treatment will stabilise over the next decade, except for children aged 5–9
years old. This might be due to long intervals between SDS’s visits which might delay
interventions and early prevention, and children thus access care when conditions reached
advanced stages. In addition, lack of affordable dental care and insurance coverage lead to
postponing dental treatment, often for years. These untreated symptoms inevitably get more
severe, resulting in children requiring admission. The significant split of admission rates
between rural/urban living children will continue to exist through the next 10 years.
Most hospitalisations for ‘birth defects’ were for ankyloglossia, followed by cleft lip and
palate. Admissions for birth defect treatment were common among pre-school age children,
Chapter Ten
172
non-Indigenous, children living in least disadvantaged urban areas. Children admitted for
birth defect conditions were more likely to be uninsured, with a higher rate of admissions
encountered for public hospitals. On the other hand, the highest percentages of
‘Developmental defects’ admissions were for supernumerary teeth and disturbances in tooth
formation or eruption conditions, with children aged 5–9 years more likely to be admitted
for treatment of dental developmental defect conditions. Children living in least
disadvantaged urban areas and being insured were more likely to be admitted in private
hospitals for ‘Developmental defect’ conditions.
10.4. Framework Model
Without a doubt, potentially preventable oral hospitalisations have been proposed as a key
marker of poor health system performance (Australian Institute of Health and Welfare,
2014a). Therefore, the Australian dental health care system is searching for ways to increase
universal primary care and preventative services coverage. One clear strategy is to increase
the access to and utilisation of those primary oral health services (in this case SDS) and
reduce costs of hospitalisations.
Previously, no studies have been conducted which integrated data from hospital admissions,
socioeconomics and service locations to form a cohesive risk based geographic output. In
this preliminary study (Chapter Nine), the hospitalisation data set has been merged with the
population distribution data using a geographic modelling technique which support the
spatial configuration of future service planning. The study (Chapter Nine) demonstrates an
application of GIS to population-based oral health planning. In the agreement with the null
hypothesis, the findings reflect the oral health profile disparities of a population living in the
Chapter Ten
173
same area, indicating that variations in SES and primary service access (e.g. SDS), may lead
to variations in utilising complex health service based on need. These discrepancies may
contribute to stark inequalities in oral health among Australian children.
The models have provided a clear indication of specific geographical areas (in this particular
metropolitan region) where no services (SDS clinics) are located, but where high hospital
admission rates are occurring, especially among school-age children. Therefore, our
population-based framework method has with the example data provided valuable insight
to the extent of child oral health admissions in relation to access to existing services, within
a precise socioeconomic characteristic of a geographical area. These findings provide a
methodological approach that can be applied, not just locally, but elsewhere to assist in
planning resource allocation, service prioritising and implementing of targeting-
appropriate intervention.
10.5. Future Studies
Since it was revealed in this thesis that children oral health diseases are not evenly
distributed anymore and one universal approach (e.g. SDS) that fits all Australian children
dental health has to be modified to address WA’s sprawling geographic and demographic
spread. Therefore, additional in-depth analysis should include those areas which were
identified as high risk areas of oral hospitalisation, to guide the design and selection of SDS
interventions in those specific areas. An increase in efforts is necessary to curb escalating
government health expenditure by reducing avoidable and preventable oral health related
hospitalisations, and focusing efforts on an improved, accessible and equitable primary oral
health care system.
Chapter Ten
174
10.6. Recommendations and Conclusion
Most oral conditions, and especially dental caries, are preventable. Thus, this thesis
investigated the avoidable dental hospitalisations to identify groups within the population
at higher risk for hospitalisation, as well as identifying time trends in hospitalisation rates
against a background of rapidly changing demographics (Chapter Five). This information
should be utilised and applied to prevent costly in-patient treatment by early detection,
prevention, and intervention. At a time when public health resources are limited, strategies
need to be developed to focus on these high-risk groups and best practice principles of care
and demand management to better utilise limited health resources.
Dental health insurance is a major component of obtaining and accessing child dental health
care. Most recently, this study has determined the disparities in access to care among
children in relation to socioeconomic divide in oral health insurance coverage (Chapter Six).
New information has been added regarding the demand for dental care based on insurance
coverage among children aged between 0 and 14 years, leading to an increasing awareness
of the substantial heterogeneity within the populations. Eliminating socioeconomic and
geographical disparities in dental care requires additional efforts in removing both financial
and non-financial barriers to dental utilisation.
The high economic burden of children dental hospitalisation over the last decade implies the
need for health resources redistribution based on a regional need in conjugation with the
development of community-based preventive programmes and treatment programmes
(Chapter Seven). In our view, tremendous monetary benefits are expected when primary
prevention of dental caries, especially in children, through SDS is implemented. Investment
Chapter Ten
175
decisions in oral conditions prevention and treatment facilities, workforce planning and
evaluation of oral health policy rely not only on knowing how many cases of oral conditions
were hospitalised in a given year, but on how many can be expected to be admitted in the
future. Thus, anticipating the future burden of oral related admissions in children in terms
of expected numbers of cases is vital in optimising the resources allocation to enable children
to have timely access to preventively focused dental care that meets the minimum standard
benchmarks for oral health service provision (Chapter Eight).
This thesis was the first of its kind to model children oral health-related hospital admissions
rates and their socioeconomic position in relation to oral health service at a community level
(Chapter Nine), and to illustrate and predict a community’s current service access needs and
assist in evidence-based decision making for planning and implementing changes to increase
access to basic risk. This new geographical model may be particularly well suited for
planning and prioritising future health service in other urban communities, based on
population projections and disease models of the current population. This thesis developed a
framework that can be adopted by other communities to identify a set of target areas,
vulnerable populations and monitor the effectiveness of interventions designed to improve
their access to care. It also provides an understanding of the distribution of demand for oral
health services, to enable policy development and service planning.
Significant reduction on the incidence of dental diseases in Australian children can be
attained through development of community-based preventive programmes and treatment
programmes on the basis of regional need. In this thesis a number of new finding were made,
paving the way for a universal strategy reform in order to set the platform for oral health
actions in WA into the next decades.
176
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Appendices
198
Appendix A
Winthrop Professor Marc TennantPrimary, Aboriginal & Rural Health Care (School of)MBDP: M309
Dear Professor Tennant
HUMAN RESEARCH ETHICS OFFICE – AMENDMENT REQUEST APPROVED
Research Ethics and Biosafety OfficeResearch Services
Phone:Fax:email:MBDP:
+61 8 6488 1610+61 8 6488 [email protected] M459
Our Ref: RA/4/1/5502 16 August 2012
Hospitalisations for oral-health related reasons in Western Australia: A ten-year analysis of trends and future projections
Student(s): Alla Talal Y Alsharif
I confirm receipt of your correspondence requesting an amendment to the protocol for the above project.
Approval has been granted for the amendment as outlined in your correspondence and attachments (if any) subject to any conditions listed below.
Any conditions of ethics approval that have been imposed are listed hereunder:
1. Addition of graduate student Ala Alsharif (student number 20446892)
If you have any queries, please do not hesitate to contact Kate Kirk on (08) 6488 3703.
Please ensure that you quote the file reference RA/4/1/5502 and the associated project title in all future correspondence.
Yours sincerely
Peter JohnstoneManager
Appendix B
Dental hospitalization trends in Western Australian childrenunder the age of 15 years: a decade of population-basedstudy
ALLA T. ALSHARIF, ESTIE KRUGER & MARC TENNANTInternational Research Collaborative- Oral Health and Equity, The University of Western Australia, Nedlands, WA,
Australia
International Journal of Paediatric Dentistry 2014
Background and Aim. This study analyzed a dec-
ade of dental admission patterns in Western Aus-
tralian children under the age of 15 years,
examining associations with sociodemographic
characteristics and with particular focus on dental
decay and Indigenous children.
Methods. This retrospective study analyzed the
data obtained for 43,937 child patients under the
age of 15 years hospitalized for an oral-health-
related condition, as determined by principal
diagnosis (ICD-10AM). Primary place of residency,
age, gender, insurance status and Indigenous
status were also analyzed.
Results. ‘Dental caries’ and ‘embedded and
impacted teeth’ were the most common reasons
for hospitalization among children under the age
of 15 years. ‘Dental caries’ were most common in
non-Indigenous patients, with ‘pulp and periapi-
cal’ most prevalent in Indigenous patients. The
age-standardized rate (ASR) of hospitalization for
Indigenous children in the last decade increased
to reach that of non-Indigenous children in 2009.
Total DRG costs of hospitalization, both public and
private, were in excess of AUS $92 million over
10 years.
Conclusions. This study indicates the burden of
oral-health-related conditions on Western Austra-
lian children and the hospital system, in terms of
health and economical impact.
Introduction
In Australia, dental conditions are one of the
highest causes of acute preventable hospital
admissions1. In 2003–2004, over 26,000 chil-
dren under the age of 15 years old had to
undergo general anesthesia in hospitals in
Australia for dental extraction and/or restora-
tions2,3. In 1995, Western Australia (WA)
recorded 3754 cases (4395 bed-days) of chil-
dren under the age of 18 years old admitted
to hospital for oral conditions4. Unfortu-
nately, subsequent studies indicated that the
rate of hospitalizations for oral conditions has
increased over time. Kruger et al.5 conducted
a study and found that from 1999 to 2003, a
total of 26,497 hospital admissions (31,432
bed-days) in WA were attributed to oral
health conditions among children under the
age of 18.
Some studies have found that the rates of
hospitalization due to oral conditions in chil-
dren varied between the age groups, with the
highest rates for high school-aged children,
followed by pre-primary, and the lowest rate
is the primary school-aged group6. This is not
unsurprising as the preschool children mostly
do not, on the whole have access to the
safety nets of School Dental Services7, while
the teenage levels are most likely related to
the removal of impacted teeth (mostly third
molars)5.
In Australia, Aboriginal and Torres Strait
Islander people are the first people of the
land. They, like many indigenous people,
have faced very significant marginalization
since European settlement and continue to
this day to face extreme issues of poor
health8. According to recent studies, Indige-
nous children have, on average, twice the
incidence of dental caries as their non-Indige-
nous counterparts9,10, but in all child age
groups, except infants, the hospitalization
Correspondence to:
Estie Kruger, School of Anatomy, Physiology and Human
Biology, The University of Western Australia (M309), 35
Stirling Highway, Nedlands, WA 6009, Australia.
E-mail: [email protected]
© 2014 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd 1
DOI: 10.1111/ipd.12095
rates for all oral health conditions were signif-
icantly higher among non-Indigenous chil-
dren6.
The aim of this study is to analyze a decade
of dental admission patterns in Western Aus-
tralian children under the age of 15 years,
examining associations with sociodemograph-
ic characteristics and with particular focus on
dental decay and Indigenous children. The
null hypothesis of this study is that the hospi-
tal admissions for dental reasons (in children)
are not associated with sociodemographic
characteristics.
Materials and methods
Data source
This research involved a de-identified detailed
analysis of the data obtained from the WA
Hospital Morbidity Dataset for ten financial
years from 1999/00 to 2008/09 under ethics
approval from The University of Western
Australia. Principal diagnosis, classified by the
International Classification of Diseases (ICD-
10AM) system, was obtained for every child
under the age of 15 years diagnosed and
accordingly admitted for an oral health condi-
tion in Western Australia for the study per-
iod. All principal diagnoses of oral health
conditions (ICD-10AM) were included in the
analysis. The ICD–10–AM ‘is the Australian
Modification of the 10th revision of the Inter-
national Classification of Diseases (ICD–10). Itis the standard classification scheme now
used for reporting diagnoses in all hospital
statistical collections, including the National
Minimum Data Set and the Hospital Casemix
Protocol’11. Age, gender and Indigenous sta-
tus, insurance status, length of stay, hospital
area, and type of each child were analyzed.
Remoteness was determined using the Acces-
sibility/Remoteness Index of Australia (ARIA)
classification, which measures ‘remoteness in
terms of access along the road network from
populated localities to each of five categories
of service center. Localities that are more
remote have less access to service centers;
those that are less remote have greater access
to service centers’12. Socioeconomic status
was analyzed using Socio-Economic Indexes
of Area (SEIFA) classification, which is a
‘product developed by the ABS that ranks
areas in Australia according to relative socio-
economic advantage and disadvantage. The
indexes were based on information from the
5-yearly census’13.
Age-specific and age-standardized rates
(ASRs) were calculated using the Health Sta-
tistics Calculator, a software package devel-
oped by the Health Department of Western
Australia. It should be noted that the data for
this study span the years 1999/00-2008/09.
In rate calculations, population data (denomi-
nators) were obtained from estimations by
the Health Department of Western Australia
Bureau of Statistics. These estimations were
based on population data as obtained by Aus-
tralian Bureau of Statistics Census Surveys.
Significant differences between rates were
based on non-overlapping 95% confidence
intervals (P < 0.05).
To determine significant differences between
nominal (categorical) variables, chi-square (v²)tests were used. Significance levels were set at
95% with Ρ value < 0.05 deemed to be signifi-
cant. SPSS 21 for Windows (Statistical package
for the social sciences; SPSS, Chicago, IL, USA)
software is used for analysis.
Results
Overall data summary
Between 2000 and 2009, a total of 43,937 chil-
dren (0–14 years) were hospitalized due to
oral conditions. Of these, 94% (n = 41,475)
accounted for seven major categories of oral
conditions with half (50%) of those hospital-
izations for ‘dental caries’, followed by,
‘embedded and impacted teeth’ (14%), ‘pulp
and periapical’ tissue conditions (11%), ‘devel-
opmental and birth defects’ (5%), ‘dental frac-
tures’ (5%), and ‘dentofacial anomalies’ 4%.
Overall, 5% (n = 2119) of admissions were for
Indigenous children.
All children
Time trends. The ASR of hospitalizations for
oral conditions increased from 926 in 2000 to
2 A. T. Alsharif, E. Kruger & M. Tennant
© 2014 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
1085 cases per 100,000 person-years in 2009.
Approximately 73% of the admissions were
among children younger than 9 years old. In
2003, children aged < 5 years had 1.3 and 1.7
times the admission rate of 5- to 9- and 10-
to 14-year-old children, respectively. Since
then, the admission rates for 5- to 9-year-olds
increased and in 2009 were 1.2 and 1.5 times
the admission rates of 0- to 4-year-olds and
10- to 14-year-olds, respectively (Fig. 1).
Sociodemographic association. Figure 2 repre-
sents the trends of themost common conditions
overtime. Overall, 546 per 100,000 children per
annum were admitted for ‘dental caries’ and
144 per 100,000 had ‘embedded or impacted
teeth’. A non-Indigenous child was 29 times
more likely than an Indigenous child to be
admitted for ‘embedded or impacted teeth’.
Non-Indigenous children were more likely to
be admitted than Indigenous children except
for ‘pulp and periapical’ conditions. (Table 1)
Children aged < 5 were more likely to be
admitted due to ‘dental fracture’ or ‘birth
defects’ conditions. In contrast, higher rates of
children aged between 5 and 9 years were hos-
pitalized due to ‘developmental defects’ or
‘dental caries’. ‘Dentofacial anomalies’ and
‘embedded and/or impacted teeth’, however,
mainly accounted for the oldest age group
admissions. Children younger than 9 years
were more likely to be admitted due to ‘pulp
and periapical’ conditions.
Gender. Males are most likely to be hospital-
ized for ‘dental caries’ (ASR 560, 95% CI
550.1–570.4) than females (ASR 530, 95% CI
520.1–540.4).
Socioeconomic association. Across all common
conditions, higher percentages of children
hospitalized lived in the least and above aver-
age disadvantaged areas, except for children
with ‘pulp and periapical’ conditions (25%),
where most were living in the most disadvan-
taged areas, followed by 23% in below aver-
age disadvantaged areas (Ρ < 0.001).
Remoteness of residency. Across all conditions,
children living in accessible areas are more
likely to be admitted than children living in
remote or very remote areas. Rural residence
was significantly associated with less dental
admissions, than metropolitan-living children
across all conditions (Ρ < 0.001; Table 1).
Length of stay. The length of stay in hospital
(LOS) was calculated and found 92% of
0.00
200.00
400.00
600.00
800.00
1000.00
1200.00
1400.00
1600.00
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
ASR
per
10
0,0
00
per
son
-yea
r
0 to 4
5 to 9
10 to 14
ASR per 100,000
Fig. 1. Hospitalization rates by age, over time.
0
100
200
300
400
500
600
700
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
ASR
per
100
,000
per
son-
year
Years
Embedded & impacted teeth
Fracture & dislocated tooth
Pulp & periapical
Developmental defects
Birth defects
Dental caries
Fig. 2. Age-standardized hospitalization rates of WA children by condition, overtime.
Trend of dental admission in Western Australian children 3
© 2014 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
separations from hospital happened on the
same day (Ρ < 0.001; Table 1).
Conditions. Children admitted to public hospi-
tals were more likely to have ‘dental frac-
tures’, ‘birth defects’ or ‘pulp and periapical’
conditions. ‘Developmental defects’, ‘embed-
ded and impacted teeth’, ‘dental caries’ or
‘dentofacial anomalies’ were more likely to be
admitted in private hospitals.
Cost. The total DRG (diagnosis-related group)
cost of this care was approximately AUS
$92 million. Private insurance was the
primary source of reimbursement for 55% of
non-Indigenous children, while Indigenous
child admissions were much more likely to be
publicly funded (96%) (Ρ < 0.001).
Aboriginal and Torres Strait Islander children
Rural-living non-Indigenous children had 1.2
times the admission rate of rural-living Indige-
nous children. In contrast, Indigenous children
living in major cities or regional areas had 2.6
times the admission rate of their Indigenous
counterparts in rural or remote areas. Sixty-
three percent of all separations recorded for
Table 1. Hospitalization of WA children for most common oral conditions across different variables.
VariablesDentalfracture
Birthdefect
Developmentaldefects
Embedded andimpaction
Dentalcaries
Pulp andperiapical
Dentofacialanomalies
All children (ASR) 49.1 56.4 56.6 144.4 545.6 116.8 44.8Age (ASR)0–4 111 136.7 29.7 1.9 746.3 165.3 2.65–9 28.2 22.3 83.6 35.4 754.4 165.7 25.810–14 11.1 14.4 55.2 388.8 146.8 22.1 103.9
Indigenous status (ASR)Indigenous 49.2 24.8 6.7 5.0 415.1 152.3 2.5Non-Indigenous 44.3 53.1 54.4 142.9 497.8 99.9 44.1
Gender (ASR)Male 55.8 70.4 57.2 115.5 560.2 126.2 37.3Female 42.0 41.7 56.0 175.2 530.2 106.9 52.8
SEIFA* (%)Most disadvantage 19.4 17.8 10.8 9.0 17.2 25.0 10.0Below average disadvantage 20.7 19.6 14.4 14.9 19.3 23.2 14.0Average disadvantage 18.4 20.0 18.5 20.3 18.4 17.1 17.9Above average disadvantage 18.3 21.2 21.5 23.6 19.9 17.5 21.8Least disadvantage 22.5 21.3 34.6 32.2 25.2 17.2 36.0
ARIA* (%)Highly accessible 18.4 18.9 16.8 25.6 19.2 20.5 18.9Accessible 67.7 63.2 66.1 56.8 58.7 60.0 62.9Moderately accessible 6.5 9.6 8.6 12.0 11.4 9.6 11.6Remote 2.6 3.9 4.5 4.1 5.1 4.0 3.9Very remote 4.7 4.5 3.8 1.5 5.6 5.8 2.6
Same day separation* (%)Yes 78.5 70.1 97.5 94.4 97.6 87.0 92.8No 21.5 29.9 2.5 5.6 2.4 13.0 7.2
Insurance status* (%)Insured 34.3 42.9 69.9 71.5 52.5 25.7 74.8Uninsured 65.7 57.1 30.1 28.5 47.5 74.3 25.2
Hospital type* (%)Public 88.2 56.8 18.2 9.0 35.5 79.3 21.0Private 11.8 43.2 81.7 91.0 64.4 20.6 79.0Commonwealth 0 0 0.1 0.1 0.1 0.1 0
Hospital area (ASR)Rural 14.5 20 15.8 83.8 301 53.3 27.8Metropolitan 55.1 62.4 64 152.1 560.3 123.8 46.3
ASR (age-standardized rate per 100,000).*Ρ < 0.001, Pearson chi-square.
4 A. T. Alsharif, E. Kruger & M. Tennant
© 2014 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
patients identified as non-Indigenous occurred
in metropolitan private hospitals.
Time trends. Figure 3 shows that the ASR of
hospitalization for Indigenous children in the
last decade increased to reach that of non-
Indigenous children in 2009. From 2000 to
2008, the difference between Indigenous and
non-Indigenous was statistically significant
over this period. Admission ASRs for non-
Indigenous children were 1.3 times more
than that of Indigenous children, with non-
Indigenous females significantly, more likely
to be admitted than Indigenous females. In
contrast, there is no statistical difference in
the admission rates between Indigenous
males and females. Furthermore, the highest
ASR of hospitalization was observed among
Indigenous children under the age of 5 years
(1337) (Table 2).
Length of stay. Indigenous children were
more likely to have longer admissions than
non-Indigenous children (Ρ < 0.001)
(Table 3).
Insurance. Nearly 97% of Indigenous hospital-
ized children were uninsured with public
hospitals mostly the primary place of admis-
sion (Ρ < 0.001).
Socioeconomic associations. It was more likely
for non-Indigenous children, across all ages,
from higher socioeconomic areas to be
admitted compared with Indigenous children.
Fifty-nine percent of all Indigenous children
hospitalized were in the lowest socioeconomic
group (Ρ < 0.001; Table 3).
Remoteness of residency. According to ARIA,
60% of non-Indigenous children hospitalized
in WA lived in areas classified as accessible.
Conversely, highest percentage (33%) of
Indigenous children lived primarily in very
remote areas (Ρ < 0.001; Table 3).
Discussion
In this study, the most common reasons for
hospital admissions were ‘dental caries’ and
‘embedded and impacted teeth’. Over time,
Table 2. Age-specific and age-standardized rates of hospitalization for oral health conditions across age groups, gender, andgeographical location.
Indigenous Non-Indigenous Total
ASR* Cl† ASR* Cl† ASR* Cl†
All ages 813.3 778.7–848.0 1090.4 1079.9–1100.8 1073.6 1063.5–1083.6Age group0–4 1328.7 1251.2–1406.2 1244.7 1224.9–1264.4 1250.2 1231–1269.35–9 901.3 838.6–964.0 1182.4 1163.6–1201.3 1164.3 1146.1–1.182.410–14 229.4 197.3–261.5 853 837.4–868.6 816.8 802.1–831.6
GenderMale 853.1 803.5–902.6 1095.6 1080.9–1110.2 1080.6 1066.6–1094.7Female 771.9 723.6–820.3 1085.2 1070.2–1100.2 1066 1052.2–1080.9
LocationRural 511.3 476.6–546.0 626.4 610.1–642.6 609.8 595.0–624.6Urban 1312.6 1240–1384.3 1235.0 1222.2–1247.7 1238.1 1225.6–1250.7
*Age-standardized rate per 100,000 person-years.†Cl represents the 95% confidence interval for ASR.
0
500
1000
1500
2000
2500
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
ASR
per
10
0,0
00
per
son
-yea
r
Indigenous
Non-Indigenous
Fig. 3. Hospitalization ASR of WA children by Indigenous
status, over time.
Trend of dental admission in Western Australian children 5
© 2014 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
the hospitalization rates of ‘dental caries’
increased. This is consistent with findings of
a previous study5. Males exhibited a signifi-
cantly higher rate of hospitalization due to
‘dental caries’, than females. The reason for
the higher caries experience in males is
unclear, although it has been claimed that
male children who have the same genotype
of mutans streptococci as their mother have
up to 13 times greater risk of caries develop-
ment than female children that acquire the
same strain of bacteria from their mother14.
Hospitalizations for ‘embedded and impacted
teeth’ were mainly among the oldest age group
with very significant differences between non-
Indigenous and Indigenous children. This con-
firm the finding of the previous surveys5,15.
Hospitalization at this age group, however, is
unlikely to be due to third molar impaction.
Maxillary canine is one of the most frequently
impacted teeth in children aged 11–14 years,
with the prevalence ranging from 0.8 to
5.2%16,17. ‘Embedded and impacted teeth’ are
predominantly undertaken in the private sec-
tor, which is not managed through policy direc-
tives15. Non-Indigenous children are more
likely to have private health cover, which plays
an important role in dental healthcare delivery
in Australia. In 2010–2011, 58% of dental
expenditure in Australia was funded by
out-of-pocket expenses and 14% by health
insurance18.
Hospitalizations for ‘pulp and periapical’
conditions were mainly due to periapical
abscess without sinus formation. It is not sur-
prising that uninsured, Australian Indigenous
male children aged < 9 years, and living in
the most disadvantaged areas were more
likely to be admitted for this condition. This
can indicate that they only access dental care
when conditions reached an advanced stage.
Most hospitalizations for ‘birth defects’ were
for ankyloglossia, followed by cleft lip and
palate, while the highest percentages of
‘developmental defects’ admissions were for
supernumerary teeth and disturbances in
tooth formation or eruption conditions.
Although preschool children have difficulties
accessing the existing dental health service, the
rates of hospitalization among this age group
have been declining since 2003. In 2005–2009,however, the hospitalization rates of 5- to 9-
year-olds started to increase and exceeded the
rates of 0- to 4-year-olds. The changing rates of
procedures over time might be a result of
changing trends in clinician beliefs, as well as
changing health insurance levels in the com-
munity; no specific reason for change is evi-
dent. Currently, most publicly delivered
children dental program in Australia is SDS,
which includes only emergency or basic treat-
ment and covers only limited care for school
children particularly those within low-income
families19. The comprehensiveness of these
programs differs significantly among state and
territories in terms of the types of services cov-
ered, age restrictions, and limits on the fre-
quency of dental visits. In Western Australia,
the SDS is primarily a public dental health pro-
gram, with emphasis on prevention and educa-
tion, and it provides free limited general dental
care to school children ranging from pre-pri-
mary through to year 11 and to year 12 in
remote locations. This care is provided by dental
therapists from fixed and mobile clinics located
at schools throughout the state. Thus, treat-
ment outside the scope of the SDS is referred to
Table 3. Percentages of child hospitalizations for oralhealth conditions across hospital type, SEIFA, ARIA, andsame day of separation.
Percentage (%)* IndigenousNon-Indigenous
Hospital type Public 96.0 36.5Private 4.0 63.4
SEIFA Most disadvantage 58.9 14.3Below averagedisadvantage
20.9 18.5
Averagedisadvantage
9.4 19.0
Below averagedisadvantage
7.1 21.0
Least disadvantage 3.8 27.2ARIA Highly accessible 12.2 20.3
Accessible 30.8 61.3Moderatelyaccessible
14.4 10.6
Remote 9.4 4.4Very remote 33.2 3.3
Same dayseparation
Yes 75.7 93No 24.3 7
Insurance status Yes 3.5 55.1No 96.5 44.9
*Ρ < 0.001, Pearson chi-square.
6 A. T. Alsharif, E. Kruger & M. Tennant
© 2014 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
other providers, and any costs are the responsi-
bility of the parent or guardian. Furthermore,
not all students are enrolled in SDS, and long
intervals between visits might delay interven-
tions and early prevention.
Although the health of Indigenous children
in Australia is lower than that of non-
Indigenous children for most indicators20,21,
admission rates were higher among non-Indig-
enous children, as reported previously for Wes-
tern Australian children4,5. The differences
observed are thought to be attributed to a num-
ber of factors, such as variation in service access
as a significant proportion of Indigenous chil-
dren live in rural and remote locations22, socio-
economic or environmental factors23.
The Indigenous population in Western Aus-
tralia constitutes just 3.2% of the total popula-
tion of the state and predominantly lives in
rural and remote areas and in areas of higher
socioeconomic disadvantage24. The hospitaliza-
tion rates were higher among children living in
metropolitan areas than in the rural children.
This can be attributable to the fact that Western
Australia is experiencing a dental workforce
shortage in rural and remote areas, especially in
terms of dental therapist and dental special-
ists22. Furthermore, geographical access to
health services was considered as the reason for
this unequal distribution; it is evident by the
fact that Indigenous children in metropolitan
areas are also more likely to be admitted than
Indigenous children in rural areas. They are
also less likely to have private health cover,
which plays an important role in the private-
driven dental healthcare delivery in Australia
and hence fail to have adequate dental treat-
ment. There is an obvious association between
insurance status and hospital types (private or
public), and the admission of Indigenous chil-
dren, which might reflect the socioeconomic
barriers to dental service utilization. Moreover,
the public sector largely services medical and
surgical emergencies and other complex condi-
tions and procedures. Indigenous children were
more likely to have longer stays in hospital than
non-Indigenous children and might be attrib-
uted to the severity of the condition.
This study focused on the trends over a
10-year time period and to highlight those
groups within the child population more
likely to be admitted. The same dataset is
also being used for further analysis to deter-
mine risk indicators and will involve more
detailed statistical analysis.
Conclusion
Most oral conditions, and especially dental car-
ies, are preventable. These findings of this
study indicate rejection of the null hypothesis,
and it identified groups within the child popu-
lation more likely to be admitted to hospital for
treatment of oral-related conditions, as well as
associated characteristics. This information
should be utilized and applied to prevent costly
in-patient treatment by early detection, pre-
vention, and intervention. At a time, when
public health resources are limited, strategies
need to be developed to focus on these high-
risk groups and best practice principles of care
and demand management to better utilize lim-
ited health resources. It is also important to
address the need for the redistribution of
resources on the basis of regional need and the
development of community-based preventive
programs and treatment programs, which will
significantly reduce the incidence of dental dis-
eases in Australian children.
Bullet points to describe the importance of this
paper to paediatric dentists
● This paper identify groups in the child population at
risk for dental condition-related hospitalizations.
● Early intervention aimed at these high-risk groups
could prevent costly hospital-based procedures, as
most are preventable.
● Indigenous status, poverty and rural/remote dwelling
are all risk indicators for admission to hospital for
dental conditions.
Acknowledgement
The authors would like to thank Professor
John McGeachie OAM for his continuous
ongoing support of the whole team.
Conflict of interest
The authors declare no potential conflict of
interest.
Trend of dental admission in Western Australian children 7
© 2014 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
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2013. http://www.adelaide.edu.au/apmrc/research/
projects/category/about_aria.html (accessed October
10 2013).
13 Australian Bureau of Statistics. Socio-Economic
Indexes for Areas. Census for a Brighter Future. cat.
no. 2901.0. Canberra: ABS, 2013. http://www.abs.
gov.au/ausstats/[email protected]/mf/2033.0.55.001/ (accessed
October 10 2013).
14 Li Y, Caulfield PW. The fidelity of initial acquisition
of mutans streptococci by infants from their moth-
ers. J Dent Res 1995; 74: 681–685.15 George RP, Kruger E, Tennant M. Hospitalisation for
the surgical removal of impacted teeth: has Australia
followed the international trends?. AMJ 2011; 4:
425–430.16 Ranjit M, ChandraSekhar G, Shubhaker RJ, Hara-
nath RMR, Sampath A. Impacted canines: etiology,
diagnosis, and orthodontic management. J Pharm
Bioallied Sci 2012; 4: S234–S238.17 Litsas G, Acar A. A review of early displaced maxil-
lary canines: etiology, diagnosis and interceptive
treatment. Open Dent J 2011; 5: 39–47.18 Australian Institute of Health and Welfare. Health
Expenditure Australia 2010–11, in Health and Wel-
fare Expenditure. Series no. 47. Cat. no. HWE 56.
Canberra: AIHW, 2012. http://www.aihw.gov.au/
publication-detail/?id=107374230092012
(accessed October 19 2013).
19 An Advocacy Kit for Community & Welfare
Non-Government Organisations (NGOs). Issues in
Oral Health for Low Income and Disadvantaged
Groups in NSW, in NSW Oral Health Alliance
(OHA). Sydney: NSW, 2010.
20 Australian Bureau of Statistics and Australian insti-
tute of Health and Welfare. The Health and Welfare
of Australia’s Aboriginal and Torres Strait Islanser
People. Canberra: Australian Bureau of Statistics
and Australian institute of Health and Welfare,
2005. http://www.aihw.gov.au/publication-detail/?
id=10737418989 (accessed October 20 2013).
21 Australian Institute of Health and Welfare. Oral
Health of Aboriginal and Torres Strait Islander Chil-
dren. Canberra: Australian Institute of Health and
Welfare (AIHW) (Dental Statistics and Research Ser-
ies No. 35). cat. no. DEN 167, 2007. http://www.
aihw.gov.au/publication-detail/?id=6442468050 (accessed
November 2 2013).
22 Steele L, Pacza T, Tennant M. Rural and remote oral
health, problems and models for improvement: a
Western Australian perspective. Aust J Rural Health
2000; 8: 22–28.23 Munoz E, Powers JR, Nienhuys TG, Mathews JD.
Social and environmental factors in 10 aboriginal
communities in Northern territory: relationship to
hospital admissions of children. Med J Aust 1992;
156: 529–533.24 Australian Bureau of Statistics. Population Distribu-
tion, Aboriginal and Torres Strait Islander Australians,
cat. No. 4705.0. 2006. Canberra: ABS, 2013. http://
www.abs.gov.au/ausstats/[email protected]/Latestproducts/2011.
0.55.001Main%20Features262011?opendocument&tab
name=Summary&prodno=2011.0.55.001&issue=2011&
num&view (accessed November 2 2013).
8 A. T. Alsharif, E. Kruger & M. Tennant
© 2014 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
Appendix C
ORIG INAL ART ICLE
Disparities in dental insurance coverage among hospitalisedWestern Australian children
Alla Talal Alsharif, Estie Kruger and Marc Tennant
International Research Collaborative – Oral Health and Equity, Department of Anatomy, Physiology and Human Biology, The University ofWestern Australia, Nedlands, WA, Australia.
Objectives: We sought to understand disparities in dental insurance coverage among hospitalised Western Australianchildren and associated factors. Methods: This study analysed the data obtained for 43,937 child patients under the ageof 15 years hospitalised for an oral-health related condition, as determined by principal diagnosis (ICD-10AM). Primaryplace of residency, age, gender, Indigenous status and socioeconomic status were also analysed. Results: Of our sample,47.3% reported lack of dental insurance coverage. Non-Indigenous children were more likely to have dental insurancethan Indigenous children. When insurance status was considered, Indigenous children were less likely to be hospitalisedfor dental treatment. Rural children were more likely to be uninsured than urban children. Lack of health insurance cov-erage was strongly associated with children living in very remote areas. These disparities were exacerbated among ruralindigenous children. Disparities in dental insurance coverage and dental care are also evident by socioeconomic status.Conclusions: Better understanding of disparities in access to care among children, socioeconomic divide in oral healthinsurance coverage and subsequent development of intervention programmes, will be critical to improving Australianchildren’s oral health.
Key words: Disparities, hospitalisation, dental, Australia
INTRODUCTION
One of the fundamental objectives of health-care sys-tems across the globe is to ensure that individualshave access to care on the basis of need, rather thanability to pay. However, this objective in a free-market economy is often warped by the economicgoals of society. In Australia, dental services are pre-dominately provided in a private sector setting andtherefore prices and wealth wraps around access.Historically, because dental care has not been consid-ered integral to health care, it is not subject to thetenets of the Australian Health Act (AHA): that is,publicly administered, universal, portable, accessibleand comprehensive1. In contrast to physician- andhospital-based services that are mainly publiclyfunded, Australians are largely responsible for financ-ing their own dental care. Australians pay for dentalcare in four different ways: through third-partyinsurance (employment-related health insurance cov-erage); through private dental insurance; by payingdirectly out-of-pocket; or through government-subsi-dised programmes (e.g. School Dental Services for
children or community and public hospital clinics foradults)1.At present, most publicly delivered child dental pro-
grammes in Australia are via School Dental Services(SDS), which includes only emergency and basic treat-ment, and cover only limited care for school children,particularly those with in low-income families2. How-ever, most major in-hospital dental services are pro-vided by the private sector offering non-subsidisedcare. In addition, private health insurance covers aproportion of costs but consumers have always facedrelatively high out-of-pocket costs for these services.In 2005, 43.8% of Australian children aged from5–11 years had private dental insurance (predomi-nately personal) and 22.3% had cardholder status (eli-gible for publicly provided services)3. The groupsmost marginalised by the current dental care systemare the lowest income families, Indigenous people andchildren living in remote areas; this has a great impacton these suffering high disease burdens such as thechildren of Australia’s first people the Aboriginal andTorres Strait Islander people2. These populationgroups have the least access to dental care and carry
© 2014 FDI World Dental Federation 1
International Dental Journal
doi: 10.1111/idj.12116
the greatest burden of untreated disease2. People fromwealthier groups have better oral health and make useof more complex and expensive services, while wait-ing lists for public dental care have grown by 20%per year1. Over time, this has resulted in increasedinequity in access to care.This study examines the disparities in dental insur-
ance coverage among Western Australian childrenhospitalised because of oral-related conditions andassociated factors to address the inequalities that cur-rently exist. The null hypothesis of this study is thatchildrens’ hospital admissions for dental conditionsare not associated with the presence of private healthinsurance.
MATERIALS AND METHODS
Data source
This primary research data set was de-identifieddetailed data obtained from the Western AustraliaHospital Morbidity Dataset for 10 financial yearsfrom 1999–2000 to 2008–2009.
Ethics
This research was conducted in full accordance withthe World Medical Association Declaration of Helsinkiand ethical approval was granted by the Ethics Com-mittee of the University of Western Australia. Childrenwere not directly involved in the study, as this was onlyan analysis of de-identified hospitalisation data, as pro-vided by the Health Department of Western Australia.
Principal diagnosis
Principal diagnosis, classified by the InternationalClassification of Diseases (ICD-10AM) system, wasobtained for every child under the age of 15 yearsdiagnosed and admitted for an oral health conditionin Western Australia for the study period. All princi-pal diagnoses of oral health conditions (ICD-10AM)were included in the analysis. The ICD-10-AM is theAustralian Modification of the 10th revision of theInternational Classification of Diseases (ICD-10). It isthe standard classification scheme now used forreporting diagnoses in all hospital statistical collec-tions, including the National Minimum Data Set andthe Hospital Casemix Protocol’4. For each child, age,gender and Indigenous status, insurance status, hospi-tal area and hospital type were also analysed.
Residential location
Remoteness was classified using the Accessibility/Remoteness Index of Australia (ARIA) which measures
‘remoteness’ in terms of access along the road networkfrom populated localities to each of five categories ofservice centre. Localities that are more remote have lessaccess to service centres, whereas those that are lessremote have greater access to service centres5.
Socioeconomic status
Socioeconomic status was analysed using the Socio-Eco-nomic Indexes of Area (SEIFA) classification which is aproduct developed by the Australian Bureau of Statisticsthat ranks areas in Australia according to relative socio-economic advantage and disadvantage. The indexes arebased on information from the five-yearly Census6.All data were analysed using SPSS 21 (SPSS, Chi-
cago, IL USA) for Windows software. Statistical sig-nificance was set at 95% (P < 0.05) and wascalculated using Pearson chi-square (v²) tests, to deter-mine significant differences between nominal (categor-ical) variables.
RESULTS
From 2000 to 2009, a total of 43,937 children(0–14 years) were hospitalised because of oral-relatedconditions. Overall 5% (n = 2,119) of admissions werefor Indigenous children.
Dental insurance (All children)
Almost one in every two children hospitalised wasuninsured (47.3%; Table 1).
Age in years on admission
Children aged between 10 years and 14 yearsreported a significantly higher level of dental insur-ance coverage than children younger than 9 years old,(P < 0.01) (Table 1).
Gender
More females (54%) were insured than males(51.4%) (Table 1).
Hospital type
Children with private health insurance were morelikely to be admitted to private hospitals than unin-sured children (P < 0.01; Table 1).
Location
Children admitted to metropolitan hospitals were 1.6times more likely to be insured than children admittedto rural hospitals. Children from the oldest age group
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Alsharif et al.
were more likely to be insured than younger agegroups. The observed variations were statistically sig-nificant (P < 0.01; Table 1).
Socioeconomic status
Children with the lowest socioeconomic status (SES)were significantly less likely to have dental insurance.In contrast, 76% of children hospitalised from leastdisadvantaged areas were insured. Hospitalised chil-dren from high SES backgrounds were three timesmore likely to be insured than children from most dis-advantaged areas (P < 0.01; Table 1).
Remoteness/accessibility
Statistically significant variations were observed acrossthe ARIA classification (P < 0.01). Lack of healthinsurance coverage was strongly associated with chil-dren living in very remote areas. Children living inaccessible areas were twice as likely to be insured aschildren living in very remote areas (Table 1).
Length of stay
Sixty-six per cent of children admitted for more than aday were uninsured, from those 78% were childrenaged between 5–9 years, followed by 74% of childrenyounger than 5 years old (P < 0.01; Table 1).
Insurance status over time
In 2000, children admitted to hospital for oral-relatedconditions were more likely to be uninsured. Sincethen, insurance levels have increased to reach 63% ofall children younger than 15 years old hospitalisedbecause of oral conditions in 2009 (P < 0.01;Figure 1a). Statistically significant higher levels ofdental insurance coverage were observed among chil-dren aged between 10 and 14 years over time, fol-lowed by the 5- to 9-year-old group (P < 0.01;Figure 1b). However, over last decade, the percentageof uninsured children younger than 4 years old hasdecreased by 22% (P < 0.01; Figure 1c).
Dental insurance
The disparities were exacerbated among Indigenouschildren. Non-Indigenous Western Australian childrenaged less than 15 years and hospitalised because oforal conditions over the last decade were 16 timesmore likely to be insured compared with their Indige-nous counterparts.
Age
Across all ages, the majority of Indigenous childrenwere uninsured. The percentage of insured Indigenouschildren aged 5–9 years were higher (1.2%) than the
Table 1 Percentage of hospitalisation of Western Australian children based on insurance status compared withdifferent variables
Insured Uninsured
Age (years) 0–4 5–9 10–14 Total 0–4 5–9 10–14 Total
All children 42.1 52.2 68.0* 52.7 57.9 47.8 32.0 47.3GenderMale 42.1 52.4 66.5 51.4 57.9 46.6 33.5 48.6Female 42.1 52.0 69.1 54.0 57.9 48.0 30.9 46.0Hospital type*Public 12.9 12.6 18.2 3.6 87.1 87.4 81.8 86.4Private 71.9 80.3 81.6 78.2 28.1 19.7 18.4 21.8Location*Urban 45 55.9 70.3 55.7 55 44.1 29.7 44.3Rural 26.3 30.4 54.5 35.2 73.7 69.6 45.5 64.8SEIFA*Most disadvantaged 17.3 23.2 39.7 24.4 82.7 76.8 60.3 76.6Below average disadvantage 31 38.2 55.1 38.8 69 61.8 44.9 61.2Average disadvantage 42.2 49.3 64.8 50.8 57.8 50.7 35.2 49.2Below average disadvantage 54.6 60.4 71.1 61.4 45.4 39.7 28.9 38.6Least disadvantaged 68 74.5 83.6 75.7 32 25.5 16.4 24.3ARIA*Highly accessible 39.5 51.5 67.3 51.6 60.5 48.5 32.7 48.4Accessible 47.3 57.8 73.1 58.2 52.7 42.2 26.9 41.8Moderately accessible 31.0 36.9 50.5 38.5 69 63.1 49.5 61.5Remote 34.8 43.2 59.2 43.4 65.2 56.8 40.8 56.6Very remote 27.2 25.5 40.7 28.3 72.8 74.5 59.3 71.7Same-day separation*Yes 43.8 54 69 54.2 56.2 46 31 45.8No 26.5 22.2 57.4 34.2 73.5 77.8 42.6 65.8
SEIFA, Socio-Economic Indexes of Area; ARIA, Accessibility/Remoteness Index of Australia.*P < 0.001, Pearson chi-square, and refer to differences between variable categories, not between insured and uninsured groups.
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Insurance coverage among hospitalised children
percentages in other Indigenous age groups (P < 0.01;Table 2).
Gender
Slightly more (3.9%) male Indigenous children wereinsured compared with female Indigenous children(3.1%). In contrast, 57% of non-Indigenous femaleswere insured compared with their male counterparts(54%) (P < 0.01; Table 2).
Location
Indigenous children living in urban areas were fivetimes more likely to be insured compared with theirrural counterparts. Interestingly, non-Indigenous chil-dren living in rural areas were 37 times more likely to
be insured than Indigenous children living in ruralareas (P < 0.01; Table 2).
Hospital type
Both insured Indigenous and non-Indigenous childrenwere significantly more likely to be admitted in pri-vate hospitals (P < 0.01; Table 2).
Length of stay
Only (0.9%) of Indigenous children hospitalised formore than a day were insured (P < 0.01).
Common oral conditions
There was a distinct contrast in the percentages ofchildren with health insurance among Indigenous andnon-Indigenous group (P < 0.01; Table 2).
Socioeconomic status
Ninety-eight per cent of Indigenous children hospita-lised and living in the most disadvantaged areas wereuninsured. Significant differences in insurance statusbetween Indigenous and non-Indigenous children wereobserved based on socioeconomic status, using theSEIFA scale (Table 2). Non-Indigenous children livingin the most disadvantaged areas were 19 times morelikely to be insured than Indigenous children living inthe same areas. Statistically significant variations wereobserved across socioeconomic distribution (P < 0.01).
Remoteness/accessibility
For both Indigenous and non-Indigenous children theproportion with health insurance decreased withincreasing geographic remoteness, with insurance levelsof only 4% and 1.3% of the Indigenous child popula-tion residing in remote or very remote areas, respec-tively. However, Non-Indigenous children living in veryremote areas were 32 times more likely to be insuredthan their Indigenous counterparts (P < 0.01; Table 2).
Changes overtime
Constant and high percentages of hospitalised Indige-nous children have been uninsured over the last decade(P < 0.01). The percentages of those with health insur-ance among Indigenous hospitalised children were verylow and constant over the study period, with a slightincrease (13%) in 2009 (Figure 2), In contrast, since2005, insurance among hospitalised non-Indigenouschildren has increased (P < 0.01; Figure 3).
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Figure 1. (a) The percentages of hospitalisation among Western Austra-lian (WA) children based on insurance status. (b) The percentages ofinsured hospitalised WA children over time based on age. (c) The per-centages of uninsured hospitalised WA children over time based on age.
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DISCUSSION
Health insurance coverage has previously been foundto be a good predictor of preventive care serviceuse7,8. Health insurance in Australia does not auto-matically include dental insurance, but Australianscan obtain dental insurance by purchasing either pri-vate patient hospital cover combined with an ‘extras’option that includes dental services, or the ‘extrasonly’ option. There are two levels of dental servicesprovided by this insurance: general dental coverageand major dental coverage. General dental coveragetypically includes services such as cleaning, removal ofplaque, radiographs and small restorations. Majordental coverage includes these services plus additionalservices such as orthodontics, third molar removal,crowns, bridges and dentures.Dental health-care coverage is an indicator that
reflects the extent to which people in need actually
receive essential dental health interventions7,8. Theprimary explanation cited in the literature for delayeddental health care seeking is financial barriers8. In thisstudy, we found statistically significant disparities indental insurance coverage among hospitalised childrenassociated with Indigenous status, socioeconomic sta-tus and remoteness and accessibility of residentialarea. The impacts of this disparity go beyond just thegreater prevalence of the dental and oral disease, andinclude greater morbidity and mortality.In this study, those children who did have dental
health insurance were more likely to come fromurban, accessible and least disadvantaged areas. Thisconfirms findings of previous surveys and may be anindication that insurance enabled access to dental careand led to greater demand for care once access hadbeen obtained9. Although private dental insurancedoes not necessarily increase receipt of preventive ser-vice or decrease perceived unmet need in all cases, it
Table 2 Percentages of insurance coverage among hospitalised Western Australian children based on indigenousstatus and different variables
Indigenous Non-Indigenous
Insured Uninsured Insured Uninsured
All children* 3.5 96.5 55.1 44.9Age (years)*0–4 3.1 96.9 45 555–9 4.3 95.7 54.7 45.310–14 3.1 96.9 69.1 30.9Gender*Male 3.9 96.1 53.9 46.1Female 3.1 96.9 56.5 43.5Location*Urban 5.1 94.9 57.5 42.5Rural 1.1 98.9 40.2 59.8Hospital type*Public 1.1 98.9 15.2 84.8Private 61.9 38.1 78.2 21.8Same-day separation*Yes 4.5 95.5 56.2 43.8No 0.9 99.1 40.7 59.3Conditions*Dental fracture 2.2 97.8 36.6 63.4Birth defects 2.8 97.1 44.2 55.8Developmental defects 21.1 78.9 70.4 29.6Embedded and impacted teeth 7.1 92.9 71.6 28.4Dental caries 4.7 95.3 55.1 44.9Pulp and periapical 1.3 98.7 28.8 71.2Dento-facial anomalies 0 100 75.1 24.9SEIFA*Most disadvantaged 1.5 98.5 28 72.0Below average disadvantage 3.4 96.6 40.9 59.1Average disadvantage 5.1 94.9 51.9 48.1Below average disadvantage 11.3 88.7 62.3 37.7Least disadvantaged 15 85 76.1 23.9ARIA*Highly accessible 6.6 93.4 53 47.0Accessible 5.4 94.4 59.5 40.5Moderately accessible 2 98 41 59.0Remote 4 96 47.6 52.4Very remote 1.3 98.7 41.8 58.2
SEIFA, Socio-Economic Indexes of Area; ARIA, Accessibility/Remoteness Index of Australia.*q < 0.001, Pearson chi-square, and refer to differences between Indigenous and non-Indigenous groups within each category.
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Insurance coverage among hospitalised children
is evident that insured children are more likely to behospitalised for less invasive treatment than theiruninsured counterparts (who were probably morelikely to receive extractions in dental clinics asoutpatients and would have difficulty paying a $100dental bill). Kasper et al.10 found that the uninsuredindividuals were more likely to have difficulty obtain-ing health care once they lost coverage. However,those uninsured individuals that did gain privatehealth cover had increased access to health servicescompared with those that remained uninsured10. Interms of health status, it is suggested that individualslosing coverage might experience adverse health out-comes compared with those that remained insured.The previous article elucidates that having privatehealth insurance increases access to care and possiblyimproves health status10. It is evident that Australianchildren who were covered by private dental healthinsurance were less likely to report fair or poor oralhealth than uninsured children8.A much smaller percentage of Indigenous children
with health insurance compared with non-Indigenouschildren could contribute to the poorer oral health sta-tus of Indigenous children and inequality in access tooral health-care11. As a result of inadequate healthinsurance coverage, with nearly 97% of hospitalisedIndigenous children being uninsured, numerous con-cerns about dental service utilisation are raised. In den-
tal markets where well-insured or private-pay patientsare common, public dental care coverage in childrenalone will be insufficient to remove disparities in dentalutilisation. The lack of affordable dental care andinsurance coverage leads to postponing dental treat-ment, often for years. These untreated symptoms inevi-tably get more severe, resulting in children requiringadmission for more invasive treatment at a muchgreater public expense than if they had been provideddental treatment when the symptoms first occurred.Furthermore, over the past 20 years, health care has
become more expensive and more individuals areunable to afford health insurance. It is important tonote that the vast majority of dental specialists are inprivate practice; consequently, most hospitalisationsfor oral problems in children, and requiring generalanaesthesia, take place in specialised private hospi-tals12,13. Accordingly, parents are forced to pay directlyout of pocket or indirectly through private health insur-ance for the hospitalisation process. In 2013, in Austra-lia, Harford et al.8 reported that almost 30% ofchildren avoided or delayed seeking oral health care,did not have recommended treatment, or their parentsexperienced a large financial burden because of the costof dental care. Children from low SES were seven timesmore likely to avoid or delay visits because of cost com-pared with high SES counterparts, and six times morelikely to not have had recommended treatment becauseof cost8. Therefore, private dental insurance is animportant factor modifying access to dental care. Theseaffordability and accessibility inequalities betweengroups might indicate a substantial variation withinAustralian children, as seen in previous studies12,14.The literature is replete with evidence that remote
Indigenous children experience worse oral health thantheir urban counterparts11,15, but this is not reflectedin the higher rates of hospitalisation among metropol-itan Indigenous children14,16–20. This can be partlyexplained by the greater availability of service (evenSDS) and the higher proportion of insured urban-living Indigenous children than insured rural andremote dwellers. In the rural environment, dentalhealth-care services may be sparse and located greatdistances from the patient. In an urban environment,health-care services may be located closer but, inaddition to financial issues, transportation (such asbuses, trains) may be a barrier to getting to theneeded care on time.The Indigenous population is disadvantaged across
a range of socioeconomic conditions and these affectchild health outcomes. Research over the past decadehas continued to show that Indigenous children sufferdisproportionately from many diseases, including den-tal diseases, and a delayed access to the health-caresystem will increase their risk for other complicationsand mortality from these illnesses. Most dental dis-
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Figure 2. The percentages of hospitalisation among Western AustralianIndigenous children based on insurance status.
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Figure 3. The percentages of hospitalisation among Western Australiannon-indigenous children based on insurance status.
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eases are preventable and unnecessary suffering anddisability can be avoided by decreasing delays indiagnosis and treatment. In addition, lack of access toambulatory health care can lead to unnecessaryhospitalisations and more expensive forms and utilisa-tion of health care. Therefore, having dental insuranceis seen, at least partly, as a way of overcoming finan-cial barriers when in need of dental care.Over time the level of health insurance for Indige-
nous and non-Indigenous children can thus be seen toreflect the inequality in health systems (including den-tal health) among the Australian child population.Throughout Western Australia the SDS primarilyfocuses on prevention and education, and it providesfree limited basic dental care by dental therapists toschool children ranging from pre-primary up to Year11 and to Year 12 in remote locations. The Australiangovernment provided a ‘safety-net’ system (SDS) as away to provide free or reduced fee dental care touninsured children. However, these sources of careare not always accessed and, as the numbers of poorand uninsured increase, the ‘safety-net’ health systemwill be unable to bear the burden of providing dentalhealth care to all of the uninsured. In addition,any further invasive treatment is referred to otherproviders and any costs are the responsibility of theparent.The public health community needs to know more
about the restrictions to seeking dental health carewithin the Australian child population to enable betterresource allocation, policy and planning. Therefore,understanding and developing a plan to combat thedisparities in dental health among these groups shouldbe a national priority.
CONCLUSION
Dental health insurance is a major component ofobtaining and accessing child dental health care. Ourstudy adds new information regarding the demand fordental care among children aged between 0 and14 years, who account for 18.9% of the Australianpopulation, leading to an increasing awareness of thesubstantial heterogeneity within the populations.Therefore, better understanding of disparities in accessto care among children and the socioeconomic divide inoral health insurance coverage, and subsequent devel-opment of intervention programmes, will be critical toimproving Australian children’s oral health. Eliminat-ing socioeconomic and geographical disparities in den-tal insurance and dental care requires additional effortsin removing both financial and non-financial barriers todental utilisation. Furthermore, improving dental insur-ance coverage for Indigenous and rural-living childrenwill ultimately help save health costs and improve over-all health for the next generation.
Acknowledgement
The authors thank Prof. John McGeachie OAM forhis continuous ongoing support of the whole team.
Conflict of interest
None declared
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Insurance coverage among hospitalised children
14. Williams S, Jamieson L, MacRae A et al. Review of Indigenousoral health [internet], 2011. Available from http://www.healthinfonet.ecu.edu.au/oral_review. Accessed 2 December 2013.
15. Smth K, Dyson K, Kruger E et al. Oral health in rural and remoteWestern Australian Indigenous communities: a two-year retro-spective analysis of 999 people. Int Dent J 2007 57: 93–99.
16. Tennant M, Namjoshi D, Codde J et al. Oral health and hospi-talization in Western Australian children. Aust Dent J 2000 45:204–207.
17. Australian Indigenous HealthInfoNet. Summary of AustralianIndigenous health [internet], 2012. Perth: Editor 2013. Avail-able from http://www.healthinfonet.ecu.edu.au/health-facts/summary. Accessed 5 December 2013.
18. Australian Institute of Health and Welfare. Dental health ofIndigenous children in Northern Territory, in Bulletin no.102.Cat. no. AUS 154. Canberra: AIHW; 2012.
19. MacRae A, Thomson N, Anomie et al. Overview of AustralianIndigenous health status, 2012. Available from http://www.healthinfonet.ecu.edu.au/health-facts/overviews. Accessed 30November 2013.
20. Australian Institute of Health and Welfare. Dental health ofIndigenous children in the Northern Territory: progress of theClosing the Gap Child Oral Health Program [internet], inAIHW bulletin no. 102. Cat. no. AUS 154. Canberra: AIHW;2012. Available from: http://www.aihw.gov.au/publication-detail/?id=10737421499. Accessed 8 December 2013.
Correspondence to:Estie Kruger,
International Research Collaborative –Oral Health and Equity,
School of Anatomy, Physiology and Human Biology,The University of Western Australia (M309),
35 Stirling Highway, Nedlands,WA 6009, Australia.
Email: [email protected]
8 © 2014 FDI World Dental Federation
Alsharif et al.
Appendix D
A population-based cost description study of oral treatmentof hospitalized Western Australian children aged youngerthan 15 yearsAlla Talal Alsharif, BDS, MDPPH1; Estie Kruger, BChD, MChD1; Marc Tennant, BDSc, PhD2
1 International Research Collaborative – Oral Health and Equity, The University of Western Australia, Perth, Western Australia, Australia2 School of Anatomy, Physiology and Human Biology, The University of Western Australia (M309), Perth, Western Australia, Australia
Keywordscost; children; dental hospitalization; WesternAustralian.
CorrespondenceAssociate Professor Estie Kruger, InternationalResearch Collaborative- Oral Health and Equity,The University of Western Australia, 35 StirlingHighway, 6009 WA, Australia. Tel.:618-648-858; Fax: 618-648-858; e-mail:[email protected]. Alla Talal Alsharifis with the School of Anatomy, Physiology andHuman Biology, The University of WesternAustralia (M309). Estie Kruger and MarcTennant are with the International ResearchCollaborative – Oral Health and Equity, TheUniversity of Western Australia.
Received: 5/26/2014; accepted: 1/5/2015.
doi: 10.1111/jphd.12088
Journal of Public Health Dentistry •• (2015) ••–••
Abstract
Objectives: We sought to analyze the economic cost of a decade of dental hospitaladmissions in Western Australian children under the age of 15 years and to identifysocio-demographic characteristics associated with these costs.Methods: This study analyzed the cost of 43,937 child patients under the age of 15years hospitalized for an oral health–related condition, as determined by principaldiagnosis International Classification of Diseases (ICD-10AM). The AustralianRefine Diagnosis Related Group version 5.1 was used to calculate the direct cost. Ananalysis of costs was broken down by socioeconomic status, primary place of resi-dency, age, gender, insurance status, and Indigenous status.Results: The total DRG cost of these admissions was approximately AUS$92 millionmillion over 10 years. Most of these funds went toward treating “Dental caries” and“Embedded and impaction” conditions of children under the age of 15 years.Approximately 95 percent of the total cost of hospitalization for oral conditions,over the last decade, accounted for non-Indigenous children. Since 2000, the directcost of child hospitalization for oral-related conditions has increased to reach $13million AUD in 2009.Conclusions: This study identified the substantial economic burden of childoral-related hospitalizations that emphasizes the importance of preventing costlyinpatient treatments.
Introduction
Dental conditions, specifically caries, are affecting the major-ity of children who live in Western Australia (WA). It isimportant to note that the Australian Government providesfunds for running various public health programs, such asSchool Dental Services (SDS), addressing children with poororal health (1). Yet, many children still end up in hospitals fordental treatment. The public health burden of hospitaladmissions due to oral conditions is quite substantial. Recentresearch indicates that the rate of hospitalization due to oralconditions among WA children is 1,074 per 100,000 popula-tions annually (2). Yet, little is known about the economiceffects of in-hospital treatment of such conditions in Austra-lia. It has also been noted that dental admissions are thelargest category of acute preventable hospital admissions andthat oral health problems are the second-most expensivedisease group in Australia, with direct treatment costs of over
$6 billion annually and additional care costs exceeding afurther $1 billion (3).
The provision of healthcare services to children affected byoral health issues in WA has been a very costly obligation.Tennant et al. affirms how expensive oral healthcare forWestern Australian children is, by stating that in 1995approximately $111 million were spent on the hospitalizationof children under 18 years of age (4). Existing data suggestthat in the period between 1999 and 2003, the cost of hospi-talization for children under the age of 18 years was $40million (5). However, current estimates of treatment costs areunknown, and prior estimates are likely to be obsolete in lightof newer therapeutic modalities, inflation, and changing pat-terns of hospitalization and surgery. The precise estimation ofthe costs of oral health services is critical to prevent undesiredconsequences affecting the quality of oral health care. There-fore, an updated estimate of the treatment costs of oral dis-eases in WA is necessary, as this is an expensive service of
Journal of Public Health Dentistry . ISSN 0022-4006
1© 2015 American Association of Public Health Dentistry
providing treatments for (mostly) preventable conditions,and our objective was to document all costs associated withthe treatment of dental conditions in the child population.
The aim of this study is to analyze the economic cost of adecade of dental hospital admissions in Western Australianchildren under the age of 15 years and to identify socio-demographic characteristics associated with these costs. Thenull hypothesis of this study is that hospital admissions fordental reasons (in children) are not associated with anincreased economic burden on Australian dental healthexpenditure.
Materials and methods
Data source
This research involved a de-identified detailed analysis of thedata obtained from the WA Hospital Morbidity Data Systemfor ten fiscal years from 1999/00 to 2008/09. This research hasbeen conducted in full accordance with the World MedicalAssociation Declaration of Helsinki, and ethics approval wasgranted by the Ethics Committee of the University of WesternAustralia. Children were not directly involved in the study, asthis was only an analysis of de-identified hospitalization data,as provided by the Health Department of Western Australia.These admissions included all children hospitalized for oraltreatment at WA including the day surgery for the studyperiod. Demographics including age-adjusted rates and per-centages of variables were previously published (2).
Principal diagnosis
Principal diagnosis, classified by the International Classifica-tion of Diseases (ICD-10AM) system, was obtained for everychild under the age of 15 years diagnosed and accordinglyadmitted for an oral health condition in WA for the studyperiod. All principal diagnoses of oral health conditions(ICD-10AM) were included in the analysis. The ICD–10–AM“is the Australian Modification of the revision 10 of theInternational Classification of Diseases (ICD–10)”. It is the“standard classification scheme now used for reporting diag-noses in all Hospital statistical collections, including theNational Minimum Data Set and the Hospital CasemixProtocol” (6).
Determination of direct cost
Across Australia, the Australian Refine Diagnosis RelatedGroup (AR-DRG) is used to calculate the cost of each patientepisode on the basis of actual data about the treatmentprocess. It is considered that Australia is a model example of amature costing system and has the most sophisticatedapproach according to cost guidelines that include the actual
amount of resources used in the treatment of a particularpatient (7). Therefore, AR-DRG version 5.1 was used tocalculate the direct cost (the Australian dollar value usedaccording to the year of admission). AR-DRG “is an Austra-lian admitted patient classification system which provides aclinically meaningful way of relating the number and type ofpatients treated in a hospital (that is, it’s casemix) to theresources required by the hospital”. Each AR-DRG represents“a class of patients with similar clinical conditions requiringsimilar hospital services” (8). The categorization classifies“acute admitted patient episodes of care into groups withsimilar conditions and similar usage of hospital resources,using information in the hospital morbidity record such asthe diagnoses, procedures and demographic characteristics ofthe patient” (8). AR-DRG cost based on age, gender andIndigenous status, insurance status, hospital area, and type ofeach child were analyzed.
Remoteness/accessibility
Direct cost based on remoteness was determined using theAccessibility/Remoteness Index of Australia (ARIA) classifi-cation, which measures “remoteness in terms of access alongthe road network from populated localities to each of five cat-egories of Service Centre. Localities that are more remotehave less access to Service Centers; those that are less remotehave greater access to Service Centers” (9).
Socioeconomic status
DRG based on socioeconomic status was analyzed usingSocio-Economic Indexes of Area (SEIFA) classification.SEIFA is a nationally accepted coding developed by the Aus-tralian Bureau of Statistics (ABS), which ranks areas in Aus-tralia according to relative socioeconomic advantage anddisadvantage based on information from the five-yearlycensus (10).
Indirect cost
Based on previous study, indirect costs were predicted atapproximately 1.5 times the direct cost (11), and becauseDRG is a direct cost, this method has been used to calculatethe indirect costs. Indirect costs include the following: patientand parents/guardians’ absence from school or work due topain and discomfort or having to accompany the child; cost oftransportation and accommodation; and societal losses ofproductivity.
Statistical analysis
To determine significant differences between continuousvariables and nominal (categorical) variables, Kruskal–Wallis
Cost description study of oral treatment of Western Australian children A. Talal Alsharif et al.
2 © 2015 American Association of Public Health Dentistry
test was used when appropriate. Significant levels were setat 95 percent with P value less than 0.05 deemed to besignificant.
SPSS 21 for Windows (Statistical Package for the Social Sci-ences; SPSS, Chicago, IL, USA) software and Excel 2007(Microsoft, Redmond, WA, USA) are used for analysis.
Results
From 2000 to 2009, a total of 43,937 children (0-14 years)were admitted to hospital for oral health–related conditions.Of these, 5 percent (n = 2,119) were Indigenous children.
Dental cost (all children)
The total DRG cost of these admissions was approximatelyAUS $92 million with a mean DRG cost of $19,975, with anestimation of additional AUD $138 million indirect cost(Table 1).
Age in years on admission
Costs were higher for children younger than 9 years (DRG 68million) compared with 10- to 14-year-old children (DRG 25million) (P < 0.01) (Table 1).
Gender
The cost did not vary substantially by gender (Table 1).
Indigenous status
Approximately 95 percent of the total cost of hospitalizationfor oral conditions, over the last decade, was accounted fornon-Indigenous children. However, the mean DRG costamong Indigenous children ($24,185) actually was higherthan the non-Indigenous children ($21,857) (P < 0.01)(Table 1).
Hospital type
Fifty-nine and 41 percent of the hospitalization costs wereincurred in private and public hospitals, respectively.However, the mean DRG cost among children admitted toprivate hospitals ($22,283) was significantly higher than chil-dren admitted in public hospitals ($21,473) (P < 0.01)(Table 1).
Location
Children living in metropolitan areas accounted for thehighest proportion (86 percent) of oral hospitalization costs.
Table 1 The Australian Refine Diagnosis Related Group Cost of Hospitalization of Western Australian Children Based on Different Variables
Variable Subcategory Mean rank† nCost (DRG)in million†
Indirect costin million† Total
All children 19,975 43,937 92 138 230Age (years) 0-4 20,631 16,367 34 52 86
5-9 23,183 15,862 33 49 8210-14 22,195 11,708 25 37 62
Gender Male 21,667 22,728 48 71 119Female 22,292 21,209 44 67 111
Aboriginal* Indigenous 24,185 2,119 5 7 12Non-Indigenous 21,857 41,818 87 131 218
Hospital type* Public 21,473 17,303 38 57 95Private 22,283 26,591 54 81 135Commonwealth 27,254 43 0.089 0.133 0.222
Hospital area* Urban 22,300 37,412 79 119 198Rural 20,072 6,525 13 19 32
SEIFA Most disadvantage 21,525 7,202 15 23 38Below average disadvantage 21,130 8,133 17 25 42Average disadvantage 21,630 8,128 17 26 43Above average disadvantage 22,315 8,918 19 28 47Least disadvantage 22,560 11,422 24 36 60
ARIA* Highly accessible 22,506 8,690 19 28 47Accessible 21,786 26,162 55 82 137Moderately accessible 20,923 4,720 10 15 24Remote 21,120 2,043 4 6 11Very remote 22,808 2,092 4 7 11
Insurance status* Insured 22,569 23,134 48 73 121Uninsured 21,302 20,803 44 65 109
* P < 0.001, Kruskal–Wallis test.† AUD $ = Australian dollar.
A. Talal Alsharif et al. Cost description study of oral treatment of Western Australian children
3© 2015 American Association of Public Health Dentistry
The mean DRG cost among children living in urban areas($22,300) actually was higher than rural living children($20,072) (P < 0.01) (Table 1).
Socioeconomic status
The oral condition-associated costs of hospitalization weremuch less for the most disadvantaged children (17 percent ofthe total cost) when compared with the other socioeconomicgroups (Table 1).
Remoteness/accessibility
The proportion of admissions decreased with increasing geo-graphic remoteness. Therefore, total disease-attributablecosts of oral hospitalization varied significantly by ARIA(P < 0.01). The direct cost of hospitalization of childrenliving in Accessible areas was 12 times higher than childrenliving in Very Remote areas. However, the mean DRG cost ofadmission among children living in very remote areas actu-ally was the highest ($22,808) among other ARIA groups(P < 0.01) (Table 1).
Insurance status
The cost of hospitalization of insured children was higherthan their uninsured counterparts by approximately$5million AUD (Table 1).
Cost per condition overtime
In 2000, the direct cost of child (younger than 14 years old)hospitalization for oral related conditions reached about $6million AUD. Since then the cost had more than doubled to$13 million AUD in 2009 (Figure 1). The variations overtimewere statistically significant (P < 0.01).
Direct cost (based on the most commonoral conditions)
Of all admitted cases 94 percent (n = 41,475) accounted forseven major categories of oral conditions with half (50percent) of those hospitalizations for “Dental caries,” whichcost approximately $45 million AUD. This was followedby, “Embedded and impacted teeth” (14 percent = $12million AUD), “Pulp and periapical” tissue conditions(11 percent = $10 million AUD), “Developmental andBirth defects” (5 percent = $11.5 million AUD), and “Dentalfractures” (5 percent) and “Dentofacial anomalies”4 percent, which costs around $4 million AUD each(Table 2).
Age in years on admission
Oral-related hospitalization costs did differ by age group. Thehighest costs were significantly accounted for 5- to 9-year-oldchildren who were hospitalized for “Dental caries,”“Pulp andperiapical,” or “Developmental defects” (P < 0.01). “Embed-ded and impacted teeth” significantly incurred the highestcosts among 10- to 14-year-olds (P < 0.01). However, in theyounger than 5-year-old group, the highest hospitalizationcosts were incurred by the conditions classified as “Dentalfracture” or “birth defects” (Table 2).
Indigenous status
Non-Indigenous child hospitalization costs were significantlyhigher than those of Indigenous children across the conditioncategories of “Birth defect,”“Developmental defects,”“Dentalcaries,” and “Pulp and periapical conditions” (P < 0.01)(Table 2).
Gender
It has been observed that hospitalization costs for“Embeddedand impacted teeth” conditions were significantly higheramong females than males (P < 0.01) (Table 2).
Socioeconomic status
Significantly higher costs were observed among childrenliving in least disadvantage areas admitted for “Dental caries”conditions (P < 0.01). However, of children admitted with“Pulp and periapical” conditions, the admissions costs ofchildren living in the most disadvantaged areas were 1.5 timeshigher than the admission cost of those living in the least dis-advantaged areas (P < 0.01) (Table 2).
0
2
4
6
8
10
12
14
Dir
ect c
ost
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UD
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illio
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Figure 1 The Australian Refine Diagnosis Related Group cost of dentalhospitalization of Western Australian children over time in million.*AUD $ = Australian dollar. Amount expressed in constant dollars toaccount for inflation.
Cost description study of oral treatment of Western Australian children A. Talal Alsharif et al.
4 © 2015 American Association of Public Health Dentistry
Remoteness/accessibility
Across all conditions, the majority of hospitalization costswere driven by children living in Accessible areas. (Table 2)These variations were significantly higher among childrenhospitalized for “Developmental defects,” “Dental caries,” or“Pulp and periapical” conditions (P < 0.01).
Insurance status
The cost of insured children admitted due to “Dental caries,”“Embedded and impacted teeth,”or“Developmental defects”conditions were more likely to be higher than those withoutinsurance admitted with the similar conditions. However, thecost of insured children hospitalized as a result of “Pulp andperiapical,” “Birth defects,” or “Dental fracture” conditionswere lower than those without dental insurance hospitalizedwith parallel conditions (Table 2).
Hospital type
The highest admission costs of “Dental caries,” “Embeddedand impaction,” or “Developmental defects” were signifi-
cantly incurred in the private sector, (P < 0.01). For “Dentalfracture,” “Birth defects,” and “Pulp and periapical” condi-tions, the greatest children hospitalization costs wereincurred in public hospitals (P < 0.01) (Table 2).
Location
The admission costs for all common conditions (except“Dental caries” and “Embedded and impacted teeth”) weresignificantly higher among children living in rural areas,when compared with their urban living counterparts(P < 0.01). Conversely, the cost of hospitalization of childrenwith “Dental caries” or “Embedded and impacted teeth” con-ditions living in metropolitan areas were 5.5, and 5.2 timeshigher than their rural living counterparts, respectively(Table 2). However, the admissions cost of rural living chil-dren (admitted for birth defects, pulp, and periapical ordentofacial anomalies condition) were significantly higheramong urban living counterparts (P < 0.01).
Cost per condition over time
Figure 2 shows that the costs of hospitalization for commonoral conditions except “Dental caries” were nearly doubled in
Table 2 The Australian Refine Diagnosis Related Group Cost (in Million) of Hospitalization of Western Australian Children Based on Most Common OralConditions and Different Variables
AR-DRG cost based on variables (AUD)*Dentalfracture
Birthdefect
Developmentaldefects
Embedded &impaction
Dentalcaries
Pulp andperiapical
Dentofacialanomalies
All children 4.1 6.5 4.5 11.9 44.8 9.5 3.8Age 0-4 3 5.1 0.7 0.04 19.7 4.2 0.08
5-9 0.7 0.8 2.2 0.9 21 4.6 0.710-14 0.3 0.6 1.6 10.9 4.1 0.7 3
Indigenous status Indigenous 0.3 0.3 0.04 0.03 2.4 1.1 0.01Non-Indigenous 3.8 6.2 4.46 11.86 42.4 8.4 3.8
Gender Male 2.4 3.7 2.4 4.9 23.6 5.3 1.6Female 1.7 2.8 2.2 7 21.2 4.2 2.2
SEIFA Most disadvantage 0.8 1.2 0.5 1 7.7 2.4 0.4Below average disadvantage 0.83 1.3 0.6 1.8 4.1 2.2 0.5Average disadvantage 0.82 1.3 0.8 2.4 8.1 1.6 0.7Above average disadvantage 0.73 1.3 1 2.8 8.9 1.7 0.8Least disadvantage 0.9 1.4 1.6 3.9 16 1.6 1.4
ARIA Highly accessible 0.8 1.2 0.8 3 8.6 2 0.7Accessible 2.7 4.1 3 6.7 25.4 5.6 2.4Moderately accessible 0.3 0.7 0.4 1.4 5 0.9 0.4Remote 0.1 0.2 0.2 0.5 2.2 0.4 0.2Very remote 0.2 0.3 0.1 0.2 3.6 0.6 0.1
Insurance status Insured 1.5 2.8 3.2 8.5 23.7 2.5 2.8Uninsured 2.6 3.7 1.3 3.4 21.1 7 1
Hospital type Public 3. 4.4 0.8 1.1 15.8 7.5 0.9Private 0.5 2.1 3.7 10.8 28.9 2 2.9Commonwealth 0 0 0.004 0.008 0.07 0.009 0.002
Hospital area Rural 3.7 6.1 4.1 1.9 6.9 8.2 3.2Metropolitan 0.4 0.4 0.4 10 37.9 1.3 0.6
* AUD $ = Australian dollar.
A. Talal Alsharif et al. Cost description study of oral treatment of Western Australian children
5© 2015 American Association of Public Health Dentistry
2009 (P < 0.01). However, the admission cost of “Dentalcaries” in 2009 was almost threefolds higher than the admis-sion cost of children in 2000 (P < 0.01).
Discussion
This study indicates that, overtime, the hospital admissionsfor dental reasons (in children) were associated with anincreasing economic burden on Australian dental healthexpenditure. A steady but significant rise can be seen in theoral-related admission rates of children over the period (2).As the average cost per admission has increased, this inevita-bly led to an increase in total costs. Most of these funds wenttowards treating “Dental caries” and “Embedded and impac-tion” conditions. This is consistent with previous studies(4,5).
Significant cost differences were found based on age, withchildren younger than 5 years old, incurred the highestadmission costs as a result of traumatic dental fracture orbirth defects (mainly cleft lip and palate). On the other hand,among children aged between 5 and 9 years old, the highestadmission costs of dental caries or pulp and periapical condi-tions might be attributed to the fact that children at this agegenerally have deciduous teeth that were exposed to cario-genic factors for a longer time. This explanation is supportedby finding low costs of dental caries admissions for childrenin the oldest age group, as new healthy permanent dentition ispresent. In addition, older children are able to cope betterwith dental treatment under local anesthesia than youngerchildren (12). However, the greater cost related to treatmentfor embedded and impacted teeth at this age group wasmainly attributable to the impaction of maxillary permanentcanine that is common oral pathological finding reportedafter 12 years of age, especially among those seeking orth-
odontic treatment. Moreover, it has been evident that animpacted canine is twice more likely to be common in femalesthan males (13).
The Indigenous population is disadvantaged across a rangeof socioeconomic conditions that sequentially affect childhealth outcomes. The literature is replete with evidence thatIndigenous children experience worse oral health than theirnon-Indigenous counterparts (14,15), but this is not reflectedin the costs of hospitalization among Indigenous children.These challenges in accessing dental care are fundamentallylinked to issues of affordability, lack of healthcare service(even SDS), and the proportion of insured Indigenous chil-dren. In addition, most Indigenous children live in rural areaswhere dental healthcare services may be sparse and located atgreat distances from the patient.
The structure of the dental system in Australia is largelyprivate, consequently most hospitalizations concerning oralproblems for children take place in private hospitals withboth providers and services concentrated in major cities(5,16). In an urban environment, healthcare services may belocated closer in distance; therefore, the availability of theservice increases the utilization and consequently increasesthe cost. On the other hand, it might be obvious that thegreater costs of admissions in public hospitals were incurredby emergency oral conditions, whereas the highest costs ofadmissions in private hospitals were incurred by dental cariestreatment and impacted teeth removals. Dental health insur-ance coverage is known to be the dominant predictors of theprivate sectors utilization of and access to dental care. This isbecause of their ability to mitigate the costs of care (17).
Researches over the past decade have continued to showthat low socioeconomic status children suffer disproportion-ately from many dental diseases and a delayed access to thehealthcare system that will increase their risk for other com-plications (18). However, our study indicates that hospitaliza-tion costs of the most disadvantaged group are low, except for“Pulp and periapical” conditions. This may be attributed tothe fact that children only access dental health care when con-ditions reached an advanced stage that requires admission formore invasive treatment, and accordingly a much greaterpublic expense, than if they had been provided dental treat-ment or prevention in early stages.
Furthermore, for children living in remote regions of thestate where access to dental care is difficult, resulting in longdelays in the provision of treatment and, most likely, signifi-cant morbidity associated with dental pain and oral infection.Additionally, traveling to distant centers for treatment undergeneral anesthesia by specialist pediatric dentists has becomethe usual method by which treatment is provided to themajority of affected children. In this context, the costs thataccounted primarily for this significant difference were traveland treatment costs associated with hospitalization and theadministration of general anesthesia (19). Many parents,
0.00
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4.00
5.00
6.00
7.00Co
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D$*
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mill
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Years
Embedded & Impacted teeth
Fracture & dislocated tooth
Pulp & periapical
Developmental defects
Birth defects
Dental caries
Figure 2 The Australian Refine Diagnosis Related Group cost of WesternAustralian children by condition, overtime.*AUD $ = Australian dollar. Amount expressed in constant dollars toaccount for inflation.
Cost description study of oral treatment of Western Australian children A. Talal Alsharif et al.
6 © 2015 American Association of Public Health Dentistry
especially rural-based or Indigenous, cannot afford such highhospitalization and treatment costs. Accordingly, a proceduresuch as extraction of decayed teeth, which is relativelycheaper, is more preferable option. However, whenaffordability and accessibility issues are overcome, the remoteband groups had significantly higher costs than groups thatwere located closer to treatment centers.
Over the last decade, there has been a substantial growth inhospitalization costs for all conditions particularly dentalcaries. This might be explained by the increase in child popu-lation over the study period; however, hospitalization ratesalso shows increases (2). It has also been anecdotally reportedthat in light of the recent global economic crisis, overalldental treatment prices in Australia have increased wellbeyond inflation, and the shift toward demanding moreexpensive private services has occurred. Furthermore, it canbe argued that a decline in the robustness of the currentschool dental service approach has an impact on child dentalhospitalizations, resulting in elevated costs in WA. Figures ofincreasing cost overtime would have implications for thefuture, indicating a significant burden on the Australianhealthcare system.
In Australia, dental care is not subjected to the tenets of theAustralian Health Act, hence the funding structure in thedental system is different to the rest of the health system inthat individuals pay for the majority of their care. Althoughgovernment funding is significant, the subsidies available arefar less than those provided in the general health system. Theamount of funding available to the public system is dwarfedby consumer expenditure in the private system. However, his-torically, the UK included dental care in their National HealthService system. Therefore, economic analyses in the UK andother European nations are not generally applicable to Aus-tralia, given that different patterns of dental care utilizationand payment systems between countries result in markedvariations in dental healthcare expenditures.
Conclusion
In brief, our study concludes that it is important to preventcostly inpatient treatment by early detection, prevention, andintervention as findings indicate a substantial economicburden of child hospitalization (for dental reasons) (20-23).Therefore, with limited public health resources, strategies areneeded to focus on best practice principles of care anddemand management for better utilization of available healthresources. In our view, tremendous monetary benefits areexpected when primary prevention of dental caries, especiallyin children, through SDS is implemented. The high economicburden of children dental hospitalization implies the need forhealth resources redistribution based on a regional need inconjugation with the development of community-based pre-ventive programs and treatment programs.
Acknowledgment
The authors would like to thank Professor John McGeachieOAM for his continuous ongoing support of the whole team.
Conflict of interest
None declared.
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11. Drummond M, Sculpher MJ, Torrance GW, O’Brien BJ,Stoddart GL. Methods for the economic evaluation ofhealthcare programmes. 2nd ed. Oxford: Oxford UniversityPress; 1997.
12. Nsour H, Almoherat F. Characteristics of childrenundergoing dental treatment under general anasthesia. J RMed Serv. 2013;20(4):45-9.
13. Litsas G, Acar A. A review of early displaced maxillarycanines: etiology, diagnosis and interceptive treatment. OpenDent J. 2011;5:39-47.
14. Australian Institute of Health and Welfare. Oral health ofAboriginal and Torres Strait Islander children [Internet].Dental Statistics and Research Series No. 35, AIHW cat. no.DEN 167. Canberra: Australian Institute of Health andWelfare; 2007. [cited 2013 Nov 2]. Available from: http://www.aihw.gov.au/publication-detail/?id=6442468050.
15. Smith K, Kruger E, Dyson K, Tennant M. Oral health in ruraland remote Western Australian Indigenous communities: atwo year retrospective analysis of 999 people [Internet]. IntDent J. 2007;57(2s1):93-9. [cited 2014 Feb 20]. Availablefrom: http://www.ncbi.nlm.nih.gov/pubmed/17506468.
16. Australian Institute of Health and Welfare. Australia’s health2010 [Internet]. Australia’s health series no. 12, Cat. no. AUS
122. Canberra: AIHW; 2010. [cited 2013 Nov 30]. Availablefrom: https://www.aihw.gov.au/publication-detail/?id=6442468376
17. Alsharif AT, Kruger E, Tennant M. Disparities in dentalinsurance coverage among hospitalized Western Australianchildren. Int Dent J. 2014;64(5):252-9.
18. Marshall R, Spencer J. Accessing oral health care in Australia[Internet]. Med J Aust. 2006;185(2):59-60. [cited 2014 Mar10]. Available from: https://www.mja.com.au/journal/2006/185/2/accessing-oral-health-care-australia
19. Milnes A, Rubin CW, Karpa M, Tate R. A retrospectiveanalysis of the costs associated with the treatment of nursingcaries in a remote Canadian aboriginal preschool population[Internet]. Community Dent Oral Epidemiol. 1993;21(5):253-60. [cited 2014 Feb 20]. Available from: http://www.ncbi.nlm.nih.gov/pubmed/8222597
20. Donly KJ, Brown DJ. Identify, protect, restore: emergingissues in approaching children’s oral health [Internet]. GenDent. 2005;53:106-10. [cited 2014 Mar 2]. Available from:http://www.ncbi.nlm.nih.gov/pubmed/15833010
21. Pienihakkinen K, Jokela J, Alanen P. Risk-based earlyprevention in comparison with routine prevention of dentalcaries: a 7-year follow-up of a controlled clinical trial; clinicaland economic aspects [Internet]. BMC Oral Health. 2005;5:2.[cited 2014 Mar 2]. Available from: http://www.biomedcentral.com/1472-6831/5/2
22. Splieth CH, Nourallah AW, Konig KG. Caries preventionprograms for groups: out of fashion or up to date? [Internet].Clin Oral Investig. 2004;8:6-10. [cited 2014 Mar 10]. Availablefrom: http://www.ncbi.nlm.nih.gov/pubmed/14714197
23. Davies RM. The prevention of dental caries and periodontaldisease from the cradle to the grave: what is the best availableevidence? [Internet]. Dent Update. 2003;30:170-9. [cited 2014Mar 12]. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12830693
Cost description study of oral treatment of Western Australian children A. Talal Alsharif et al.
8 © 2015 American Association of Public Health Dentistry
Appendix E
Future projections of child oral-related hospital admission ratesin Western Australia
Alla AlsharifA, Estie KrugerA,B and Marc TennantA
AInternational Research Collaborative – Oral Health and Equity, University of Western Australia,Nedlands, WA 6009, Australia.
BCorresponding author. Email: [email protected]
Abstract. This study aimed to project the hospital admission rates of Western Australian children for oral conditions,with a particular focus on dental caries, embedded and impacted teeth, and pulp and periapical conditions through tothe year 2026. Two methods were used to generate projection data through to the year 2026, using the Western AustralianHospital Morbidity Dataset for the period 1999–2000 to 2008–2009. The projected admission rate increase in thosechildren aged 14 years and younger from 2000 to 2026 was 43%. The admission rates are expected to more than doubleover time (7317 cases in 2026 compared to only 3008 cases in 2000) for those children living in metropolitan areas. Dentalcaries, embedded and impacted teeth, and pulp and periapical conditions will remain the top (mostly) preventable causesof admission throughout this time. Anticipating the future burden of oral-related hospital admissions in children, in termsof expected numbers of cases, is vital for optimising the resource allocation for early diagnosis, prevention and treatment.A concerted effort will be required by policymakers and oral healthcare communities to effect substantial change forthe future.
Additional keywords: dental care for children, hospitalised child, oral health.
Received 19 August 2015, accepted 10 October 2015, published online 11 January 2016
a previous study has shown a clear urban–rural divide in childhospital admissions; the estimated age-adjusted hospitalisationrates (AARs) of urban-dwelling children were twice that of theirrural-dwelling counterparts (Alsharif et al. 2014a).
By 2040, the WA population is projected to double, withmetropolitan areas remaining the dominant population centresin the state (ABS 2013). Hence, an increase in oral-relatedconditions in children is expected to have a significant impacton the demands for oral health services over the next 20 years.This is likely to be exacerbated by limited resources andworkforce shortages. Projections of oral-related admission ratesand their associated costs need to be performed to inform policy,planning and resource allocation. Previously, projections haveled to better planning and resource allocation (Madge 2000;Goss 2008; Commonwealth Department of Health 2009;Australian Institute of Health and Welfare 2014; HealthWorkforce Australia 2014).
To date, there are no data available on future child oral-healthhospitalisation demands inWestern Australia. An understandingof the projected incidence of children’s oral conditions is afundamental obligation toenable rational planning formonitoringand treatment of oral conditions. Against this backdrop, the aimof this study was to analyse projected oral-health-relatedadmission rates of Western Australian children, with a particularfocus on dental caries, embedded and impacted teeth, and pulp
Introduction
Over the past 30 years, there have been significant improvements in the oral health of Western Australian children, partly associated with the development of a comprehensive school dental service (SDS) and public health measures, such as widely accessible fluoridated water supplies (Kruger et al. 2006). As a result, the prevalence of dental disease in children has diminished (Blinkhorn and Davies 1996). However, dental caries are still a major public health concern in most developed countries, affecting 60–90% of school-age children, and their incidence is expected to increase significantly over time in many developing countries (WHO 2015). Oral health conditions are responsible for the highest number of acute preventable hospital admissions and significant cost to Australia (SCRGSP 2010), and cause considerable social concern within the community.
In Western Australia (WA) during 1999–2000 and 2008–09, dental conditions accounted for 933 and 1081 hospital admissions per 100 000 person-year (PY), respectively; these numbers could be reduced by providing early access to appropriate services (Alsharif et al. 2014a). The majority of cases were for dental caries and extractions. Dental conditions cost the state more than $92 million over the last decade (Alsharif et al. 2015a). Overall, 546 cases per 100 000 children per annum were admitted for ‘dental caries’ and 144 admissions per 100 000 had ‘embedded or impacted teeth’ (Alsharif et al. 2015a). In addition,
Journal compilation � La Trobe University 2016 www.publish.csiro.au/journals/py
CSIRO PUBLISHING
Australian Journal of Primary Healthhttp://dx.doi.org/10.1071/PY15132
and periapical conditions through to 2026, based on 10 years ofpast hospitalisation data for robustness.
Materials and methodsData source
This study involved a de-identified detailed analysis of the dataobtained from the Western Australian Hospital MorbidityDataset for the period 1999–2000 to 2008–2009 under ethicsapproval from the University of Western Australia. A principaldiagnosis was obtained for every child under the age of 15 yearsadmitted for an oral health condition (in both private andpublic hospitals) in WA for the study period, using theInternational Classification of Diseases Tenth Revision-Australian Modification (ICD-10-AM) system. All principaldiagnoses of oral health conditions (ICD-10-AM) were includedin the analysis. The ICD-10-AM ‘is the standard classificationscheme now used for reporting diagnoses in all hospital statisticalcollections, including the National Minimum Data Set andthe Hospital Casemix Protocol’ (Commonwealth Department ofHealth and Aged Care 1998). Age and residential area foreach child were analysed. Future predictions for dental caries,embeddedand impacted teeth, andpulpandperiapical conditions,which accounted for 75%of all hospitalised conditions during thestudy period, were also analysed.
Data analysisAll projections were based on age-specific hospitalisation ratesand AARs, which were calculated using the Health StatisticsCalculator, a software package developed by the HealthDepartment of WA. Population data (denominators) for hospitaladmission rates were obtained from estimations by the HealthDepartment of WA. These estimations were based on populationdata obtained by Australian Bureau of Statistics census surveys.Two separate methods were used to project future cases (Gillet al., 1997). Both methods accounted for the projected increasein both the population and the incidence of these conditions,using 10 years of data. The first method, the linear method, usedhistorical data to estimate a line of best fit for each 5-year agegroup, using the method of least squares. Based on the estimatedAARs, the future number of cases was determined. The secondmethod, the exponentially weighted moving average (EWMA),used historical trends tomodel future points equally. Thismethodplaces greater weight on more recent data. Applying the twomethods separately resulted in very similar trends; therefore, onlythe results of the linear method are presented. There is a general
consensus among statisticians that a relatively simple linearmodel of age-specific rates provides a good fit to the data whilegiving reasonably accurate predictions over a short to mediumtime span (Australian Bureau of Statistics 2013). The acceptedapproach among statisticians preparing projections of thisnature is to assume a linear model for increasing rates to preventprojecting admission rates below zero. Further, there is afundamental presumption in this approach that the factors thataffect oral-related admissions, such as risk factors, change inan approximately linear way with time for each age group(Australian Bureau of Statistics 2013). This presumption holdson condition that there are no major quantitative changes in anyunderlying factors, such as the introduction of an interventionprogram.
Cost projections
Based on a previous study, Australian refined diagnosis-relatedgroups (AR-DRGs) were used to calculate the direct cost of eachpatient episode on the basis of actual data about the treatmentprocess (Alsharif et al. 2015b). EachAR-DRG represents ‘a classof patients with similar clinical conditions requiring similarhospital services’ (AIHW 2013). The DRG cost was dividedinto categories: low (0–4000); middle (4001–10 000); high(10 001–20 000); and extremely high (20 001 and over). Thelow-cost category was most representative of the overall costdistribution,whichwas normally distributed. Therefore, low-costwas deemed appropriate to use in future cost projections.
Other data analyses were performed using SPSS 21 forWindows (IBM, Chicago, IL, USA) and Excel 2007 (Microsoft,Redmont, WA USA).
Results
A total of 43 937 children (0–14 years) were admitted to hospitalfor oral-health-related conditions over the study period. Ofthese, 15% (n = 6525) were rural-dwelling children.
Projections of all oral-related hospitalisations rates
Population projections through 2026 for WA indicated asignificant increase (66%) in the total population. The actualprojected oral-related admission rates increase in those aged14 years and younger from 2000 to 2026 is 43% (Fig. 1). Of thetotal projected oral-related admissions, a 171% increase inhospitalisation rates of children aged 5–9 years is projected tooccur in 2026. However, in 2026, a 23% decrease inhospitalisation rates among children younger than 5 years isprojected. (Fig. 1)
It is anticipated that the AARs will more than double (7317cases in 2026 compared to only 3008 cases in 2000) for thosechildren living in metropolitan areas (Fig. 2). In contrast, a slightreduction is projected in the AARs among rural-dwellingchildren (Fig. 2).
The overall direct costs of all oral-related child hospitalisationsare estimated to increase from $10million in 2009 to $16millionin 2026, an increase of 61% (Fig. 3). From 2016 to 2026, oralhospital admissions will cost the state a minimum of AU$147million (Fig. 3).
What is known about the topic?* To date, there are no data available on future child oral-health hospitalisation demands in Western Australia.
What does this paper add?* Future oral-related hospital admission rates amongchildren are an important measure of the burden of oralhealth care in Australia and have implications for futureresource allocation and planning.
B Australian Journal of Primary Health A. Alsharif et al.
Projections of dental caries hospitalisation rates
Hospitalisation due to oral conditions among children is highlyinfluenced by dental caries, as this condition accounts for~50% of all cases. Assuming hospitalisation rates will follow asimilar trend in future, it is projected that the overall AARs ofdental caries will more than double from 406 to ~937 cases per100 000 PY between 2000 and 2026. With the anticipatedincreases in the population, this equates to ~3742 new casesexpected to be hospitalised in 2026 (Fig. 4). In addition, theoverall AARs of hospitalisation in children living inmetropolitan areas is projected to rise from 417 to ~1190 casesper 100 000 PY between 2000 and 2026, which equates to~3982 new cases expected to be admitted in 2026 (Fig. 5). Asignificant gap is predicted to occur in the future between thehospitalisation rates of children living in rural areas comparedto those living in metropolitan areas. (Fig. 5)
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Fig. 5. Age-adjusted hospitalisation rates (AAR) projection to 2026 ofhospitalised children due to dental caries based on location.
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Projections of hospitalisation rates for embeddedand impacted teeth
The admission rates of children with embedded and impactedteeth is projected to stabilise over the next decade, with childrenaged 10–14 years still accounting for the highest admission rates(Fig. 6). Although hospitalisation rates of children living inmetropolitan areas will decrease slightly over time, remarkablevariations in admission rateswill continue to occur between rural-and urban-dwelling children. (Fig. 7)
Projections of hospitalisation rates for pulp and periapicaltreatment
The admission rates of children for pulp and periapical treatmentare projected to stabilise over the next decade and are expected to
reach ~244 cases per 100 000 PY in 2026, an increase of almost66% from 2000 (Fig. 8). The significant split in admission ratesbetween rural- and urban-dwelling childrenwill continue throughthe next 10 years, with children living in urban areas 2.4 timesmore likely to be admitted to hospital as a result of pulpal andperiapical conditions than their rural-dwelling counterparts.(Fig. 9)
Discussion
Although there has been a significant reduction in dental cariesin children over the last generations in Australia (as inother developed countries), the rates of oral-related hospitaladmissions among children have increased substantially overthe past decade. The annual rates of admissions in WA arepredicted to increase significantly over the next 20 years. It isimportant to note that projections are not intended to functionas exact forecasts, but to indicate what might be expected if the
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D Australian Journal of Primary Health A. Alsharif et al.
stated assumptions were to apply over the projected timeframe. More recently, our team has revealed that the AAR ofhospitalisations for oral conditions increased from 926 in 2000to 1085 cases per 100 000 PY in 2009 (Alsharif et al. 2015a).By 2026, the rates of avoidable hospitalisation and associatedcosts are projected to increase. It is reasonable to predict thatthe number of children with oral conditions will increase by aneven greater percentage, as only school-registered children areclinically diagnosed and treated within the limited SDS scope.An increase in age-adjusted dental caries admission rates hasbeen observed over the past 10 years and this trend is likely tocontinue, resulting in an estimated 52% increase in the annualnumber of admissions due to dental caries by 2020. If thesetrends continue, an estimated 83% increase in dental cariesadmissions can be expected by 2026. The dramatic increase inthe anticipated number of dental caries in school-age childrenshould be alarming to all those concerned with planning andproviding dental services to children in WA.
The projected rates of hospitalisation for embedded andimpacted teeth removal/treatment are expected to remain stableor decrease slightly. This might be attributed to the changingrates of procedures as a result of changing trends in clinicianbeliefs, as well as changing health insurance levels in thecommunity. However, the authors believe that this trend is notexpected to continue indefinitely and there will be an increase inthe projected number of cases admitted to hospital for theremoval of embedded and impacted teeth among disadvantagedchildren once they have access to appropriate services. Thisassumption is based on the fact that disadvantaged children areat higher risk of systemic and metabolic disorders, geneticdisorders and deciduous teeth injuries, which are all causesof delay in tooth eruption or impaction (Almonailiene et al.2010).
It is predicted that there will be an increase in admission ratesfor pulpal and periapical conditions in children aged 5–9 yearsold over the next 20 years as a result of population growth andpoor dental health service access. Long intervals betweenSDS visits might delay interventions and early prevention;consequently, children only access care when dental conditionshave reached advanced stages. In addition, the lack of affordabledental care and insurance coverage lead to the postponementof dental treatment, often for years. These untreated symptomsinevitably become more severe, resulting in children requiringadmission for more invasive treatment at a much greater publicexpense than if they had been provided dental treatment whenthe symptoms first occurred.
The health of rural- and remote-dwelling children in Australiais poorer than that of urban-dwelling children formost indicators,including marked inequalities in oral health and oral healthservices (AIHW 2008). Geographical access to health services isclearly the reason for these inequalities in health. In metropolitanareas, clinics are located mainly in community health centres,or on school or hospital grounds. However, in some ruralcommunities, mobile dental clinics provide limited oral healthservices for children. This inequality is evident in the fact thatchildren living in metropolitan areas are more likely to beadmitted to a hospital for dental procedures than children livingin rural areas (Alsharif et al. 2015a). Children in rural andremote regions are also less likely to have private health cover
(Alsharif et al. 2014b), which plays an important role in theprivate-driven oral healthcare delivery system in Australia.Further contributing to inequalities is the fact that WA isexperiencing a dental workforce shortage in rural and remoteareas, especially in dental therapists and specialists (Steele et al.2000).
Over the last decade, there has been substantial growth inhospitalisation costs for all oral conditions, particularly dentalcaries (Alsharif et al. 2015b). This cost-pressure scenario is onlyexpected to increase in the near future. As a result of the recentglobal economic crisis, dental treatment prices in Australia areexpected to increase well beyond inflation rates and a demand formore expensive private services has occurred. In addition, adecline in the robustness of the current SDS approach has had animpact on child dental admissions, resulting in elevated costs inWA. The projected increasing costs will have implications forthe future, indicating a significant burden on the Australianhealthcare system.
Increases in the AARs of children admitted for oral conditionsmay be explained by several factors. For example, demographicshifts in the Australian population will have a major influenceon the projected number of oral-condition cases in the future.Although evidence indicates that some minority populationshave higher oral-condition rates that are not reflected bylower admission rates, additional increases in the projectedadmission rates are expected once these groups gain access tothe service. In addition to an actual increase in the incidenceof oral diseases, population growth (primarily in urban areas),workforce shortages and misdistribution, changes in diagnosticand treatment ?A3B2 tlsb?> practices, and limited resources forspecific conditions, are likely to affect the future burden of thesediseases. These shifts will create a significant socioeconomicburdenon theAustraliandental health system, sincedental servicesare not covered by the principle of universal access. Clearly,opportunities to target early intervention towards those at higherrisk of the need for admission, and to target primary and preventiveservices towards areas of need, are key research and policydirections that come from this research.
Conclusion
Projections indicate increasing rates of oral-related admissionsamongWesternAustralian children, especially for dental caries,and pulp and periapical conditions. Oral diseases amongchildren have a considerable impact on the Western Australiancommunity. The rates of oral-related admissions occurring inWestern Australian hospitals each year is an important measureof the burden of oral conditions inAustralia and has implicationsfor resource allocation and planning. Investment decisions onthe prevention of oral conditions and treatment facilities,workforce planning and evaluation of oral health policy rely notonly on knowing how many cases were hospitalised in agiven year, but on how many can be expected to be admitted inthe future. Therefore, a universal strategy is needed to set theplatform for oral health actions in WA into the next decade.Anticipating the future burden of oral-related admissions inchildren in terms of expected numbers of cases is vital inoptimising the allocation of resources to enable children to havetimely access to preventively focused dental care that meets
Child oral-related hospital admissions Australian Journal of Primary Health E
the minimum standard benchmarks for oral health serviceprovision.
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Appendix F
Community Dental Health (2015) 32, 1–6 © BASCD 2015Received 10 September 2015; Accepted 17 October 2015 doi:10.1922/CDH_3853Alsharif06
Identifying and prioritising areas of child dental service need: a GIS-based approachA.T. Alsharif1, E. Kruger2 and M. Tennant2
1The University of Western Australia, Australia; 2International Research Collaborative, Oral Health and Equity, The University of Western Australia, Australia
Aim: To identify and prioritise areas of high need for dental services among the child population in metropolitan Western Australia. De-sign: All children hospitalised due to an oral-condition from 2000 to 2009, at metropolitan areas of Perth were included in the analysis of a 10-year data set. QGIS tools mapped the residential location of each child and socioeconomic data in relation to existing services (School Dental Service clinics). Results: The tables and maps provide a clear indication of specific geographical areas, where no services are located, but where high hospital-admission rates are occurring, especially among school-age children. The least-disadvantaged areas and areas of high rates of school-age child hospital-admissions were more likely to be within 2km of the clinics than not. More of high-risk-areas (socio-economically deprived areas combined with high oral-related hospital admissions rates), were found within 2km of the clinics than elsewhere. Conclusion: The application of GIS methodology has identified a community’s current service access needs, and assisted evidence based decision making for planning and implementing changes to increase access based on risk.
Key words: Geographic Information System, hospital admissions, child oral health, Australia
Introduction
With the substantial reduction in dental decay prevalence in child populations there is an ongoing need for the systems that underpin care for this group to evolve to meet chang-ing oral health profiles. Consistent with the greater expo-sure of many societies to fluoride, dental decay in children has diminished dramatically. In most developed countries caries prevalence hovers around 50% of the population, and severity as measured by the DMFT index at age 12 years, is below two (Petersen, 2003). Caries experience in Australia is consistent with these global measures (Mejia et al., 2012). Several countries have, for many years, oper-ated School Dental Services (SDS), as a universal service model to provide primary dental care to the child population. These services have adapted to falling burdens of dental disease by, for example, means testing, integration with adult services and, in rare cases, cessation or outsourcing to private dental providers. With most of the disease burden now resting with a small minority of children, targeting of dental services to those in greatest need becomes important for effective services. Results of our previous studies indi-cated that Indigenous status, absence of private insurance, low socioeconomic status and rural living are the most common risk indicators of decreased receipt of preventive service or increased perceived unmet need (Alsharif et al., 2014a;b; 2015). In addition, it is well known that previous history of dental caries is the best indicator of higher future risk. In this study, we used geographic information systems (GIS) methods to identify areas of need for primary dental services for children. GIS is a computational approach to health planning using geo-referenced data (Aronoff, 1993).
Correspondence to: Estie Kruger, International Research Collaborative- Oral Health and Equity, The University of Western Australia, Nedlands, Western Australia 6009, Australia. Email: [email protected]
The aim of this study was to identify and prioritise areas of high need for dental services among the child population in metropolitan Western Australia using the oral health related hospitalisation data of all children over a ten year period.
Material and Methods
Ethics approval to conduct the study was granted by the Ethics Committee of the University of Western Australia RA/4/1/5502.
To identify any possible gaps in primary dental service provision to children, data from metropolitan Western Aus-tralia (WA) were used. WA occupies the western third of the Australian continent; comprising an area of about 2.5 million sq.km with a population of about half a million aged under 15 years (ABS, 2014). Of those, 19% live in the capital city of Perth region (ABS, 2011a). Perth was used for this study as 73% of all hospital admissions for children under age 15 occurred in the metropolitan area, and existing SDS clinics are located predominantly in that area. The existing SDS in WA is a universal coverage model, providing free primary dental care to all school registered children who choose to enrol in the service. Despite being a universally applied system however, it reaches a under 30% of children (GWA DHS, 2008a). Some parents who choose to not enrol their children can access private dental services, but this is not an affordable or accessible option for many. Since 2000, SDS coverage has been declining rapidly, and more children are hospitalised for preventable oral related conditions (Spencer, 2012). Against this backdrop it is important that reliable methods are used to determine the distribution of demand for SDS clinics, to inform policy development and service planning.
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Hospitalisation data were analysed for every 0-14-year old, diagnosed and accordingly admitted to hospital in WA for an oral health condition, as classified by the International Classification of Disease – Tenth Australian Modification (ICD-10AM) (CDHAC, 1998). These data were obtained from the WA Hospital Morbidity Dataset (HMDS) for 10 financial years, from 1999/00 to 2008/09. Primary place of residence at the time of hospitalisation were also analysed, using Statistical Local Areas (SLAs) - 37 SLAs cover WA without gaps or overlaps (ABS, 2012a), and their boundary files were obtained from the (ABS) website (ABS, 2011b). Age Standardised Rates (ASR) of child hospital admis-sions per SLA were calculated using the Health Statistics Calculator developed by the Health Department of Western Australia and population data based on ABS census data. Based on these admission rates per SLA, the entire child population was categorised into five quintiles, separately for each age group.
Admission data for each child was available at SLA level, but for higher accuracy and precision analysis, a smaller area-based analysis was needed, and therefore cen-sus Collection Districts (CDs) were used. A CD is much smaller than an SLA, and is a quasi-measure of density of residents (based on an area that a single census officer can collect data from). Census collection districts and the geographic boundaries of each CD were obtained from the ABS webpage (2011b). The Perth metropolitan area covers 2,840 CDs, 65% of the WA’s CDs, with more than 270,000 under 14-year-olds. Hospitalisation data across each of the 37 WA SLAs were distributed by age groups (0-4, 5-9 and 10-14 years). For each age group, the rates of child hospitalisations was calculated for each SLA then this SLA rate was applied to each of the SLA’s CDs.
The number of under-15-year-olds for each CD were obtained from the ABS (2006) census data (ABS, 2013b).
For socioeconomic data, each CD has a Socio-Economic Indexes of Area score (SEIFA 2006) assigned by the ABS, based on socio-economic indicators of the CD’s popula-tion (ABS, 2013a). SEIFA is a nationally accepted coding system ranking areas in Australia according to relative socio-economic advantage based on five-yearly census data (ABS, 2013b). These rankings were dichotomised into most disadvantaged areas (Poorest, SEIFA deciles 1 to 5) and least disadvantaged areas (Wealthiest, SEIFA deciles 6 to 10).
The addresses of all fixed SDS clinics were obtained from the Department of Health (ABS, 2011b) and geocoded, i.e. changed into map coordinates and located on a map. The populations of children who lived within 2km of each SDS clinic were identified.
Geographic information systems (GIS) in this study were used as a technique for integrating hospitalisation data related to dental disease with known risk indicators (e.g. socioeconomics), to identify and prioritise geographic areas of high need for a dental service. The approach while tested on this one city was designed to be universally ap-plicable. The resultant maps indicated where SDS clinics were located, as well as the following attributes of the child population both within and outside of a 2km zone around it: population density, age-specific hospital admission rates and an indication of area socio-economic disadvantage.
All mapping and geocoding of data used QGIS v.2.6 (Boston, USA), analyses used SPSS 21 for Windows and data were tabulated in Excel 2007.
Results
From 2000 to 2009, 31,910 metropolitan Perth children aged from 0-14 years were hospital admissions for oral-related conditions. All 77 fixed SDS clinics were included, with a ratio of 2,414 school aged child popu-lation per clinic.
The distributions of hospital admissions rates by both socio-economic status and location inside or out-side 2km of a clinic are presented in Tables 1, 2 and 3. More children (68%) lived within 2km of existing SDS clinics than further away. Of all children living within 2km of a clinic, 18% of 0-4 year olds come from areas with higher (i.e. high or very high) admission rates and low socio-economic scores (poorest urban areas) (Table 1). In addition, 11% and 5% of 5-9 and 10-14 year-olds, respectively, were living in the poorest areas with higher admission rates (Table 2 and 3).
About a third of children live outside the 2km zones, 6% of them come from the poorest and higher admission rates urban areas. Meanwhile, 41% of all the children are from the wealthiest areas with higher hospitalisation rates and lived predominantly more than 2km from a clinic (Tables 1-3).
Admission rates1 Inside the 2km zones Outside the 2km zones
Poorest areas Wealthiest areas
Overall Poorest areas Wealthiest areas
Overall
Very low 3,964 (7%) 7,791 (13%) 11,758 (20%) 1,153 (4%) 5,349 (20%) 6,502 (24%)Low 4,656 (8%) 6,181 (10%) 10,837 (18%) 1,340 (5%) 4,525 (17%) 5,871 (22%)Moderate 6,355 (11%) 6,947 (12%) 13,302 (23%) 967 (4%) 3,525 (13%) 4,492 (17%)High 5,000 (8%) 7,170 (12%) 12,170 (20%) 1,077 (4%) 3,073 (11%) 4,150 (15%)Very high 5,431 (9%) 5,528 (9%) 10,962 (18%) 1,950 (7%) 4,103 (15%) 6,080 (22%)All rates 25,406 (43%) 33,617 (57%) 59,029 (100%) 6,487 (24%) 20,575 (76%) 27,097 (100%)
Table 1. Zero to four years old child population distribution by hospital admission rates and socioeconomic status inside/out-side the 2km Zone of existing SDS clinics
1All admission rates per 100,000 population: Very low=0-1141, Low=1142-1183, Moderate=1184-1209, High=1210-1299, Very high≥1300)
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In this analysis, the term ‘highest risk areas’ refers to CDs with the poorest areas and having high oral related hospital admissions rates; ‘lowest risk areas’ being the wealthiest with the lowest admission rates. Note that admissions were based on children’s addresses at the time of admission. The location of clinics were considered as a potential barrier to children’s hospital admissions through access to early diagnosis and treatment.
Large geographical variations of high risk areas in relation to age, either outside of, or inside the 2km zone of existing SDS clinics, were observed (Figures 1 and 2). More high risk areas were observed among pre-school aged children, regardless of their location in relation to the clinics. High risk areas for children aged under 5 years were more likely to be within, rather than outside of a 2km radius of a clinic. There were also more high risk areas within, rather than outside 2km of clinics (Fig-ures 1 and 2) for children older than 5 years. Most high risk areas were in the peripheral areas of this particular metropolitan region.
Figures 3 and 4 compared the high oral related ad-mission rates of children living in the wealthiest areas, outside and inside the 2km zone of existing SDS clinics and reveal large geographical variation. For the wealthi-est areas, those with high admission rates of school-age children were more likely to be within a 2 km of a clinic than further away. However, many areas at risk of high (school-age children) hospitalisation rates were found more than 2km from a clinic, where no SDS service is available. Most wealthier areas with high pre-school child
hospital admission rates, were concentrated in peripheral areas of this metropolitan region.
When comparing children of different age groups, from poorest/wealthiest areas, where high risk of hos-pitalisations occur, differences were observed (Figures 1-4). Most areas with high risk pre-school admission rates, were from the poorest areas. In contract, most of high risk school-age hospital admissions areas, were from the wealthiest areas, with a significant number being in areas with worse SDS coverage.
Discussion
While there has been a significant reduction in tooth decay levels in children over the last generation in Australia as in other developed economies, marked inequalities in oral health still exist. Results of our earlier work on the incidence of oral related hospitalisations among the child population of Western Australia were previously published (Alsharif et al., 2014a). It has been determined that the total Diagnosis Related group (DRG) cost of these admissions was $92 million, with an estimated additional $138 million as indirect cost (Alsharif et al., 2015). While hospitals are a vital component of any health system, the Australian dental health care system is searching for ways to increase SDS coverage and reduce costs of hospitalisations. One clear strategy is to increase the access to and utilisation of those universal primary care and preventive services.
Admission rates1 Inside the 2km zones Outside the 2km zones Poorest areas Wealthiest
areasOverall Poorest areas Wealthiest
areasOverall
Very low 8,046 (13%) 5,606 (9%) 13,652 (22%) 2,904 (10%) 3,059 (11%) 59,729 (21%)Low 5,356 (9%) 7,161 (12%) 12,520 (21%) 1,229 (4%) 3,203 (11%) 4,438 (15%)Moderate 5,287 (9%) 7,255 (12%) 12,545 (21%) 1,301 (5%) 3,226 (11%) 4,546 (16%)High 4,567 (7%) 6,499 (11%) 11,066 (19%) 1,058 (4%) 5,240 (18%) 6,298 (22%)Very high 1,884 (3%) 9,256 (15%) 11,140 (18%) 18 (0.1%) 7,115 (25%) 7,133 (25%)All rates 25,140 (41%) 35,777 (59%) 60,923 (100%) 6,510 (100%) 21,843 (100%) 28,387 (100%)
Table 2. Five to nine years old child population distribution by hospital admission rates and socioeconomic status inside/outside the 2km Zone of existing SDS clinics
1All admission rates per 100,000 population: Very low=0-1041, Low=1042-1139, Moderate=1140-1209, High=1210-1391, Very high≥1392)
Admission rates1 Inside the 2km zones Outside the 2km zones Poorest areas Wealthiest
areasOverall Poorest areas Wealthiest
areasOverall
Very low 8,691 (13%) 5,356 (8%) 14,053 (21%) 2,186 (7%) 1,793 (6%) 3,985 (13%)Low 6,362 (10%) 9,564 (14%) 15,929 (24%) 1,605 (5%) 4,124 (13%) 5,806 (18%)Moderate 7,964 (12%) 9,103 (14%) 17,067 (26%) 1,708 (5%) 2,813 (9%) 4,534 (14%)High 2,346 (4%) 7,263 (11%) 9,609 (15%) 1,117 (4%) 8,130 (26%) 9,247 (30%)Very high 580 (1%) 8,042 (12%) 8,686 (13%) 43 (0.1%) 7,647 (24%) 7,690 (24%)All rates 25,943 (40%) 39,328 (60%) 65,344 (100%) 6,659 (21%) 24,507 (78%) 31,262 (100%)
Table 3. Ten to fourteen year old child population distribution based on hospital admission rates and socioeconomic status inside/outside the 2km Zone of existing SDS clinics
1All admission rates per 100,000 population: Very low=0-652, Low=653-773, Moderate=774-817, High=818-980, Very high≥981)
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1. The following are not a continuation of the typescript but the full sized images for use as mocked=up above
Figure 1. High age-adjusted oral related admission rates of children living in low socioeconomic areas (SEIFA<6) inside 2km zones of existing School Dental Service clinics in PerthFigure 1. High age-adjusted oral related admission rates of children living in low socioeconomic areas (SEIFA<6) inside 2km zones of existing School Dental Service clinics in Perth
Figure 2. High age-adjusted oral related admission rates of children living in low socioeconomic areas (SEIFA<6) outside 2km zones of existing School Dental Service clinics in PerthFigure 2. High age-adjusted oral related admission rates of children living in low socioeconomic areas (SEIFA<6) outside 2km zones of existing School Dental Service clinics in Perth
Figure 3. High age-adjusted oral related admission rates of children living in high socioeconomic areas (SEIFA>5) inside 2km zones of existing School Dental Service clinics in PerthFigure 3. High age-adjusted oral related admission rates of children living in high socioeconomic areas (SEIFA>5) inside 2km zones of existing School Dental Service clinics in Perth
Figure 4. High age-adjusted oral related admission rates of children living in high socioeconomic areas (SEIFA>5) outside 2km zones of existing School Dental Service clinics in PerthFigure 4. High age-adjusted oral related admission rates of children living in high socioeconomic areas (SEIFA>5) outside 2km zones of existing School Dental Service clinics in Perth
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In the present study, integrated data from hospital admissions, socio-economic population-based indicators, and service locations, were used to form a cohesive risk-based geographic output to support the spatial configuration of future service planning. The study demonstrates an application of GIS to population-based oral health planning.
The findings reflect the oral health profile disparities of a metropolitan population. Preventable oral hospi-talisations have been proposed as a key marker of poor health plan performance (AIHW, 2014). Currently, SDSs are the main public child dental program in Australia, providing dental checkups, emergency and basic treat-ment, but cover only limited care for enrolled school children, particularly those within disadvantaged families (NSW OHA, 2010). Treatment outside the scope of the SDS is referred to other providers and any costs are the responsibility of the parent or guardian (GWA DHS, 2008b). Many studies confirmed that lower use of pre-ventive health services, delay seeking primary care and higher levels of oral diseases are observed among chil-dren living in low socioeconomic areas, these untreated symptoms get more severe and admission for complex treatment may be inevitable (ABS, 2010). However, admission rates do not reflect the actual burden of the disease among disadvantaged groups possibly due to economic constraints and reduced mobility.
On the other hand, a different admission pattern was evident among children from high SES areas. These chil-dren were more likely to be admitted for oral conditions than those living in more deprived areas. Based on our previous study using the same data set, 76% of children in wealthy areas have private dental health insurance (compared to only 24% of those in poor areas) which might indicate that insurance enabled improved access to dental care and led to greater demand for hospital-based care once access had been obtained (Alsharif et al., 2014b; Bagramian et al., 2009).
This can be confirmed by the findings in Figures 3 and 4, where children from wealthy areas are more likely to be admitted for oral related conditions than children living in poor areas. Nevertheless, it is obvious from our previous analysis that insured, wealthy children are more likely to be admitted for less invasive treatment than their most deprived counterparts (who were probably more likely to receive invasive treatment), (Alsharif et al., 2014a;b) despite individuals from poor backgrounds carrying a higher burden of oral disease (AIHW, 2011). In general, it is evident that people from the most de-prived areas were less likely to have taken preventive health actions such as dental screening, or having their teeth cleaned (ABS, 1999). Our study findings suggested that variations in SES may lead to variations in utilising complex health service based on need. This may contribute to widening oral health inequalities among Australians, with more low-SES children requiring admission for more invasive treatment which has a much greater public expense than if they had been provided dental treatment when the symptoms first occurred.
The results and maps provide a clear indication of specific geographical areas (in this city) where no local service is provided, but where high hospital admission rates occur especially among school-age children.
Therefore, our findings provide valuable insights to the extent of child oral health admissions in relation to access to existing services and deprivation mapped in detail across the city. These findings provide a meth-odological approach that can be applied, not just locally, but elsewhere to assist in planning resource allocation, prioritising services and targeting of interventions.
Conclusion
This study has applied GIS methodology to identify a community’s current service access needs, and informed evidence based decision making for planning and imple-menting changes to increase access based on risk. The methods developed in this framework can be adopted by other communities to identify a set of target areas with vulnerable populations and subsequently to monitor the effectiveness of remedial interventions. This model may be particularly well suited for planning and prioritising future health services in other urban communities, based on population projections and disease models of the current population.
Acknowledgments
The authors thank Professor John McGeachie OAM for his continuous ongoing support of the whole team and thank Taibah University, Saudi Arabia, for sponsoring Dr Alsharif’s PhD studies.
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