Costs of patients with and without dementia in the last year of life in Queensland

Megan McStea, Tracy Comans, Kim-Huong Nguyen, Trisha Johnston

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

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

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/

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?

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

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

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

Discuss your project with the linkage team

Email your queries but ensure you provide an

example and id numbers

TALK TALK TALK

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

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

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

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

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

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

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

Top 10 ICD codes by Principal Diagnosis

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

Principal diagnosis by Dementia

Series1

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

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

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

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

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)

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

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

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?

What about reducing the number of co-morbid

conditions?

How would this impact health care spending?

Co-morbiditycomorbidities.jfif

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

• Preventing additional co-morbidities in older

age

• Further examination into actual costs vs

DRGs

• Look at UTI diagnosis and treatment

Summary – healthy ageing

Megan McSteaCentre for Health Services ResearchFaculty of Medicine, The University of QueenslandM+61499113379