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Costs of patients with and without dementia in the last year of life in Queensland
Megan McStea, Tracy Comans, Kim-Huong Nguyen, Trisha Johnston
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Who we are and what we wanted Health Economics Research and Modelling Unit
- Centre for Health Services Research
University of Queensland
Investigate a matched cohort of dementia patients in their last year
of life to examine differences in hospital usage and costs
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Be careful what you wish for
We are all warned to think carefully for what we ask but with data
requests this is incredibly important
• Think first of your base cohort – ours was those that died over a period
of 2 years
- We of course were then in possession of a group of people that had
died so perhaps they were sicker than the norm
• Then your cohort bounds – consider base and upper age bands, Aria
codes, ICD codes , age range
- We asked for anyone over 55 years Then matching – think
carefully what you want to match on
• Then matching – think carefully what you want to match on
- What power do you want to achieve if you are doing a matched
cohort – we chose a 1:1 but a 1:3 would have been a better choice
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Power for matched cohorts Power increases but at a decreasing rate as the ratio of controls/cases increases. Little additional power is gained at ratios higher than four controls/case. There is little benefit to enrol a greater ratio of controls to cases.
https://onlinecourses.science.psu.edu/stat507/node/67/
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CHECK CHECK CHECK
It is your responsibility to check the data
Your data will not necessarily be logical or contain what you thought it would
Problems that may occur
• Hospital data entry issues
• Matching issues
• Hospitalisations out of data
• Last entry details
• Data may not be complete in the variables chosen
How to check?
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Identified problem - Country of Birth
study_id sepn_id age gender country_birth facility_num major_diag_cat
CASE_006044 1 70 Female Africa A Musculoskeletal Sys & Conn Tissue
CASE_006044 2 70 Female Australia B Musculoskeletal Sys & Conn Tissue
CASE_006044 3 70 Female Australia B Factors Influencing Health Status
CASE_006044 4 70 Female Africa A Factors Influencing Health Status
CASE_006044 5 70 Female Africa A Kidney & Urinary Tract
CASE_006044 6 70 Female Africa A Kidney & Urinary Tract
CASE_006044 7 71 Female Africa A Musculoskeletal Sys & Conn Tissue
CASE_006044 8 71 Female Australia B Musculoskeletal Sys & Conn Tissue
CASE_006044 9 71 Female Africa A Factors Influencing Health Status
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Identified problem - Gender
study_id sepn_id age gender postcode facility_num major_diag_cat
CASE_0062 1 70 Female 4XXX A Musculoskeletal Sys & Conn Tissue
CASE_0062 2 70 Male 4XXX B Kidney & Urinary Tract
CASE_0062 3 70 Female 4YYY C Kidney & Urinary Tract
CASE_0062 4 71 Male 4YYY B Nervous System
CASE_0062 5 71 Female 4YYY C Kidney & Urinary Tract
CASE_0062 6 71 Male 4YYY B Musculoskeletal Sys & Conn Tissue
CASE_0062 7 71 Female 4YYY D Musculoskeletal Sys & Conn Tissue
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8CRICOS code 00025B
Our experience Original RevisedCase Control Total Case Control TotalBoarder 4 8 12 7 8 15
Care Type Change 3,140 3084 6,224 3,261 3213 6,474
Died In Hospital 167 213 380 4,367 6522 10,889
Discharged At Own Ris 224 176 400 222 214 436
Episode Change 3,691 2841 6,532 4,088 2833 6,921
Home/Usual Residence 42,265 59797 102,062 43,709 64607 108,316
Medi-Hotel 2 4 6 1 5 6
Non Return From Leave 6 2 8 5 7 12
Organ Procurement 0 1 1
Other 160 144 304 177 130 307
Other Health Care Acc 237 179 416 242 195 437
Other Health Care Est 226 144 370 238 131 369
Residential Aged Care 3,019 1568 4,587 3,020 1455 4,475
Transferred To Anothe 5,191 5396 10,587 5,507 5523 11,030
Total 58332 73558 131,890 64844 84843 149,687
Status at separation of person
Original
Case Control Total
Boarder 4 8 12
Care Type Change 3,140 3084 6,224
Died In Hospital 167 213 380
Discharged At Own Ris 224 176 400
Episode Change 3,691 2841 6,532
Home/Usual Residence 42,265 59797 102,062
Medi-Hotel 2 4 6
Non Return From Leave 6 2 8
Organ Procurement 0 1 1
Other 160 145 305
Other Health Care Acc 237 179 416
Other Health Care Est 226 144 370
Residential Aged Care 3,019 1568 4,587
Transferred To Anothe 5,191 5396 10,587
Total 58332 73558 131,890
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Discuss your project with the linkage team
Email your queries but ensure you provide an
example and id numbers
TALK TALK TALK
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Consort Diagram
Total ICD/ED Sample
1 071 364
Cases 499 075
Control 572 289
Total Deaths Sample 23 864
Cases 11 932
Control 11 932
Deaths with no ICD/ED 1 420
Cases 785 (6.6)
Controls 635 (5.3)
Cases
No death or ICD dementia code 1 055
Remaining with any ICD/ED code 10 093
Remaining with DRG& ICD data 10 092
Other Error 2
Remaining 10 089
Controls
Controls with a dementia death 947
Remaining with any ICD/ED code 10 350
Remaining with DRG& ICD data 10 350
Death before Separation 1
Remaining 10 349
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Predominantly Australia
born (75%), evenly
spread male and female
(47% v 53%) group mean
age 85, starting at 52
years up to 105
Characteristics
Country of birth87 years [81- 91]
86 years [81 – 90]
Gender Split
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Controls had significantly more
comorbidities as defined by the
Charlson code
Charlson score comparison
0
500
1000
1500
2000
2500
3000
3500
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Nuum
ber
of P
art
icip
ants
Charlson score
Charlson comorbidity Index dementia removed
Case Control
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Charlsoncomorbidities
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Perc
enta
ge o
f part
icip
ants
with c
om
orb
idity
Charlson Comorbidity Case prevalence order
Case
Control
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Total Case Control
Patients (%)
Incidents (%)
Cost of period $
Patients(%)
Incidents (%)
Cost$
Patients (%)
Incidents (%)
Cost of period $
Dialysis 128 (0.6) 23571 (15.6) 116,722
38 (0.4) 6589 (11.0) 128,588 90 (0.9) 15678 (19.0) 110,100
Only dialysis 0 0
Chemotherapy
643 (3.1) 8482 (5.9) 11,780 94 (1.0) 1075 (1.8) 11,781 549 (5.3) 7407 (9.0) 11,780
Only Chemo 3 3
Due to repeated measures for
dialysis and chemotherapy
distort the cohort and so 3
patients who only received
chemotherapy were removed for
base analysis as were all
episodes marked as dialysis
and/or chemotherapy, however
these were used for sensitivity
analysis
Dialysis and chemotherapy patients
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Patients with dementia had
significantly more ED
presentations than controls, were
more likely to be at a public
hospital, had more intra-hospital
transfers and were marginally
more likely to be snapped.
Hospital dataED presentation by group Number of episodes involving change
of care by group
Number of Admissions
10.8%
9.6%
78% 72%
0
1000
0
2000
0
3000
0
4000
0
5000
0
36.9% 36.5%
Number of Episodes in excess of ALOSPatients with dementia had a
significantly longer length of stay
with a mean length of stay of 7.6
(7.3 – 7.8) days vs 6.6 (6.4 – 6.7)
days. No difference in number of
overstays but overstays longer for
controls
Cases
Con
trols
Average Number of Days
in excess of ALOS
Average number of days in excess of ALOS
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Patients with dementia were
more likely to present only once
immediately before death
Hospitalisations before Death
Death no hospitalisation
Single hospitalisation Single hospitalisation leading to death
Controls were marginally quicker
to die with a mean time to death
of 14.1 months as compared to
15.1 for patients with dementia.
Patients with dementia were
more likely to present only once
immediately before death
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Top 10 ICD codes by Principal Diagnosis
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
Principal diagnosis by Dementia
Series1
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UTI and pneumonia are most
common principal diagnoses for
patients with dementia Whilst
congestive heart failure and
pneumonia are the drivers for the
patients without dementia.
Concern with awaiting care
incidence and pneumonitis
Top 10 ICD codes by Principal Diagnosis
0
500
1000
1500
2000
2500
3000
Principal diagnosis by Dementia
Case Control
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Principal Diagnosis DRG code (Dialysis and chemo removed)
66%
42%
44%
49%
56%
54%
38%
46%
61%
31%
52%
34%
58%
56%
51%
44%
46%
62%
54%
39%
69%
48%
0 2000 4000 6000 8000 10000 12000 14000 16000 18000
Nervous System
Circulatory System
Respiratory System
Factors Influencing Health Status
Musculoskeletal Sys & Conn Tissue
Kidney & Urinary Tract
Digestive System
Skin, Subcutaneous Tissue & Breast
Injury, Poison & Toxic Effect Drugs
Blood, Blood Form Organs, Immunolog
Endocrine, Nutritional & Metabolic
Number of DRGs
Princip
al D
iagnosis
Cate
gory
Principal Diagnosis DRG Category
Case
Control
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Adjusting the DRG costs by
length of stay and removing the
chemotherapy and dialysis costs
results in controls being
marginally more expensive
Cost over last year of life–(no dialysis or chemotherapy)
In hos
pital las
t 6 m
onths
In hos
pital las
t 12 mon
ths
0
10000
20000
30000
40000
50000
Average Cost per Patient
Cost (AU$)
Cases
Controls
In hos
pital las
t 6 m
onths
In hos
pital las
t 12 mon
ths
0
5000
10000
15000
Presentations at hospital
Presentations
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No difference in costs when
looking at public hospital
Cost public v private in last 12 months (No dialysis or chemotherapy)
0
2000
0
4000
0
6000
0
8000
0
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No difference un an adjusted
basis with a p value of 0.852
Adjusted cost analysis
Characteristic Coefficient 95% CI P value
Study group Case/Control 528 (-1806 – -2862) 0.657
Age -478 (-631 – -324)
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Presentation Title | Date 23
Costs for cases vs controls
A$28,732 vs $29,088
with a p value of 0.664
CRICOS code 00025B
A quick look at real costs
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We know that most health care spending happens
at the end of life
Can these costs be avoided or are they just
delayed?
Health care costs
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Smoke
• Die at 65 of lung cancer – health care costs last six months of
life ~$30,000
Don’t smoke
• Die at 80 of dementia. Last five years of life in residential care at
cost of ~$400,000
• 15 years aged care pension
• Negative Savings!
What is the counterfactual?
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What about reducing the number of co-morbid
conditions?
How would this impact health care spending?
Co-morbiditycomorbidities.jfif
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27
As comorbidities increase costs
linearly increase
CRICOS code 00025B
Hospital cost of last 12 months of life by number of co-morbidities
$0
$20,000
$40,000
$60,000
$80,000
$100,000
$120,000
$140,000
$160,000
0 1 2 3 4 5 6 7 8 9
Number of Co-morbidities
Hospital cost of last 12 months of life by number of co-morbidities
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• Preventing additional co-morbidities in older
age
• Further examination into actual costs vs
DRGs
• Look at UTI diagnosis and treatment
Summary – healthy ageing
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Megan McSteaCentre for Health Services ResearchFaculty of Medicine, The University of QueenslandM+61499113379