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Mobility of elderly patients across
healthcare institutions
Inês Videira, Inês Jorge, Iolanda Ferreira, Ivete Afonso, Jennifer
Pires, Joana Ribeiro, Joana Vaz, Joana Fernandes, Joana Costa,
Joana Magalhães
Faculdade de Medicina da Universidade do
Porto
Introdução à Medicina
Class 10
2005/2006
Mobility of elderly patients across healthcare institutions
Presentation Summary
Introduction
Aim
Methods
Results/Discussion
Discussion Synthesis
Limitations - Bias
Mobility of elderly patients across healthcare institutions
Introduction
Progress in Medicine and Informatics influences the development of health information systems
Wyatt, JC. Clinical Data Systems, part 1: Data and medical records. Lancet. 1994 Dec 3; 344 (8936): 1543-7
Medical information, present in medical records, helps decision making (sic)
Haux, R. Health information systems – past, present, future. Int J Med Inform. 2005 Sep 15
Mobility of elderly patients across healthcare institutions
Organizing patients’ information is essential
Katehakis DG, Sfakianakis S,m Tsiknakis M, Orphanoudakis SC. An infrastructure for integrated electronic health record services: the role of XML (Extensible Markup Language). J Med Internet Res. 2001 Jan-Mar; 3(1): E7.
Communication between healthcare services influences the quality of the provided service
Introduction
Branger PJ, van’t Hooft A, Duisterhout JS, van der Lei J. A standardized message for supporting shared care. Proc Annu Symp Comput Appl Med Care. 1994;473-7
Mobility of elderly patients across healthcare institutions
Patients’ data is spread in all the places where they have received clinical services
Katehakis DG, Sfakianakis S,m Tsiknakis M, Orphanoudakis SC. An infrastructure for integrated electronic health record services: the role of XML (Extensible Markup Language). J Med Internet Res. 2001 Jan-Mar; 3(1): E7.
Introduction
Elderly people demand much of health services [1], being the main consumers of the NHS [2]
[1] Scanaill CN, Carew S, Barralon P, Noury N, Lyons D, Lyons GM. A Review of Approaches to Mobility Telemonitoring of the Elderly in Their Living Environment. Ann Biomed Eng. 2006 Mar 21
[2] Victor C R, Higginson I. Effectiveness of care for older people: a review. Qual Health Care 1994;3:210 6.
Mobility of elderly patients across healthcare institutions
In Central and Northern Portugal, elderly people do not usually attend the doctor when facing a disease
Santana P. Ageing in Portugal: regional iniquities in health and healthcare. Soc Sci Med. 2000 Apr;50(7-8):1025-36.
Introduction
Effective care and treatment is required for this group [1], which may be enhanced with information systems
[1] Victor C R, Higginson I. Effectiveness of care for older people: a review. Qual Health Care 1994;3:210 6.
Mobility of elderly patients across healthcare institutions
Aim
To study elderly patients’ mobility
across healthcare institutions.
Mobility of elderly patients across healthcare institutions
Study Classification
Observational: the observer only collects data,
without interference in the manipulation of variables Transversal: data is collected in a single moment
Retrospective: information refers to the previous
year Analysis Unit: all the individuals aged 65 years old
or over per household
Methods
Mobility of elderly patients across healthcare institutions
Sample design
Random sample of elderly individuals out of the available population (elderly individuals with household phone numbers)
Methods
Target population: individuals aged 65 years old or over of Oporto’s region (Espinho, Gondomar, Matosinhos, Maia, Oporto, Paredes, Stª Maria da Feira, Trofa, Valongo, Vila do Conde, Vila Nova de Gaia) Available population: individuals aged 65 years old or over of Oporto’s region with household phone number starting with 22.
Mobility of elderly patients across healthcare institutions
Methods Data collection
Random Digit Dialling - two stage random sample Telephone interviews
Questionnaire design The questionnaire included sociodemographic characteristics (age, sex, town)
Questions related to the aim of the study
Scale pilot - interview with seven subjects, in which the five questions were developed
Mobility of elderly patients across healthcare institutions
Methods
The telephone number was randomly selected, using two computer generated directories for prefix and suffix
The following situations have been rejected: Non existent phone numbers
Non residential phone numbers
Within the valid households, these did not result into questionnaires:
Insufficient Age
Refused to Answer
100 questionnaires have been obtained within the time available for the telephone interviews
Mobility of elderly patients across healthcare institutions
Methods
Statistic Issues
Simple frequency distribution - to show the characteristics of the subjects and their answers
Variance was calculated for every variable. Relations between variables were defined using, multiple response tables and compute variables Analyses performed with SPSS for Windows 13.0
Mobility of elderly patients across healthcare institutions
Results
Table 1. Characterization of telephone calls (approximated percentages related to the total amount of telephone calls)
Of the 1892 telephone calls made, only 100 questionnaires were obtained response rate = 58%
Non-existent numbers 1226 (65%)
Non-residential telephone numbers 312 (16%)
Total amount of invalid telephone calls 1538 (81%)
Insufficient age 182 (10%)
Refused to answer 72 (4%)
Answered questionnaires 100 (5%)
Total amount of valid telephone calls 354 (19%)
Total amount of telephone calls 1892
Mobility of elderly patients across healthcare institutions
Results
Sample Results: 65 women, 34 men and 1 missing
Mean number of age was 72,7 years
old
Ages between 65 and 90 years old
Mobility of elderly patients across healthcare institutions
Results/Discussion
The mean number of different healthcare institutions visited in 2005 was 4.83, whether within the same type or across different types
111087654321
Total_institutions
30
25
20
15
10
5
0
Co
un
t
Figure 1. Bar chart showing the amount of people by number of healthcare institutions attended.
Mobility of elderly patients across healthcare institutions
Mobility patterns: 41% attended at least
four different institutions
There is certain mobility among different types of institutions
Results/Discussion
Figure 2. Mobility pattern considering distinct types of institutions.
Linking medical institutions appears
to be a relevant issue
L,P,PhC,L,PhH,C,L,PhH,C,L,P,Ph
Mobility Pattern
25%
20%
15%
10%
5%
0%
Per
cen
t
6%7%
19%
22%
Mobility of elderly patients across healthcare institutions
Figure 2. Number of healthcare institutions attended to within the same type and the corresponding amount of inquiries who visited them, in percentage (sample of 100 individuals)
Results/Discussion
People usually go to one medical institution per type.
0
1
2
3
4
5
Amount_visited
hospital centre lab priv_phisician pharmacy
Institution
0
20
40
60
Per
cen
t
Mobility of elderly patients across healthcare institutions
Results/Discussion
Hospitals: 24% attended more than one
Pharmacies: 33% of the inquired individuals went to
more than one There is a certain mobility within the
same type of these medical institutions
Results/Discussion 42% of HSJ users establish
connections with other hospitals
HSJ should be primary linked to HSA, with a long term benefit for 5% of the elderly population
The second most relevant linkage should be HSJ-IPO (3%)Table 2. Existing relations between all the hospitals visited and the associated amount of elderly people.
Hospital pattern Cases (N)
HSJ…………………………………….. 24
Just HSJ………………………….
14
With others………………………
10
HSJ-HSA…………………..
5
Just HSJ-HSA……….
4
HSJ-HSA-Valongo….
1
HSJ-IPO……………………
3
Just HSJ-IPO...............
2
HSJ-IPO-Prelada.........
1
HSJ-Valongo……………….
2
Just HSJ-Valongo........
1
HSJ-Valongo-IPO.......
1
HSJ-Prelada...........................
2
Just HSJ-Prelada.........
1
HSJ-IPO-Prelada…….1
Mobility of elderly patients across healthcare institutions
Results/Discussion
Figure – Mobility pattern focusing on number of different institutions per type
Mobility patterns: Most common: 1H,
1HC, 1PL, 0P, 1Ph
In an hypothetical priority list these institutions should be the first ones to be linked
2H 1C 1L 1P1Ph
0H 1C 1L 0P1Ph
1H 1C 1L 1P1Ph
1H 1C 0L 0P2Ph
1H 1C 1L 1P0Ph
0H 1C 0L 0P1Ph
1H 1C 1L 0P1Ph
Mobility Pattern 2
12%
10%
8%
6%
4%
2%
0%
Per
cen
t
4%
11%
3%3%
4%
3% 3%
Mobility of elderly patients across healthcare institutions
Results/Discussion
Men and Women Women often go, in average, to more hospitals, health centres
and pharmacies
Men go, in average, to more private laboratories and physicians
Typical elderly individual – attends one medical institution per type
Hospitals Health Centres Private Laboratories Private Physicians Pharmacies
Men 0.76 0.71 0.97 0.79 1.41
Women 1.14 0.82 0.91 0.66 1.45
Both Genders 1.02 0.77 0.93 0.70 1.42
Table 3. Mean numbers of attended healthcare institutions, within the same type, by men and women separately and both genders together.
Mobility of elderly patients across healthcare institutions
Discussion Synthesis
Patients’ mobility has been registered: More pronounced between different
types of healthcare institutions Less distinct among the same type of
medical institutions
Patients would indeed benefit from an information linkage between different types of healthcare institutions
Mobility of elderly patients across healthcare institutions
Not every individual in target population owns a
household phone number
Restricted time period of interviews
Limitations - Bias
Some of the phone numbers starting with 22
include places out of the Oporto’s region
Data collected in one moment may not also reflect
the reality due to people’s memory lapses
Individuals that refuse to participate