Utilisation and cost of health services in
the last six months of life: a comparison
of cohorts with and without cancer
Rebecca Reeve, Preeyaporn Srasuebkul,
Marion Haas, Sallie Pearson, Rosalie Viney
on behalf of the EOL-CC team:
J Langton1, P Srasuebkul1, R Reeve2, B Parkinson2, M Haas2,
R Viney2, S Pearson1
1: Faculty of Pharmacy, The University of Sydney; 2: CHERE, University of Technology Sydney
Background and motivation
• The last year of life is one of the most resource and cost
intensive periods in cancer care
• Understanding patterns of care provides evidence to inform
resource allocation and planning decisions
• There has been little research on end of life care in Australia
(most existing research is in North America)
– Most existing Australian research focuses solely on hospital care or
palliative care
– Few studies comparing cancer and non-cancer cohorts
• Observational studies using linked administrative datasets
provide an approach to understanding patterns of care at the
end of life
2
Existing literature*
• 78 studies of end-of-life cancer care
– 55 from North America
– 33 published since 2008
– 71 examined resource use alone (52) or in combination with costs (19)
• 30 focus on only one aspect of resource use
– 7 costs only
– 15 quality of care indicators
• none Australian and only 1 with non-cancer comparator
• 5 local studies
– Focused on use of palliative care services, hospital admissions and
emergency department presentations
– All but one study conducted in the Western Australia
– Only one included data from the last decade
– Opportunities!!!
* Langton J et al “End-of-life resource utilization and costs: A systematic review of
retrospective observational studies of cancer decedents using health
administrative data (1990-2011)” article forthcoming in Palliative Medicine
3
Langton J et al “End-of-life resource utilization and costs: A systematic review of
retrospective observational studies of cancer decedents using health
administrative data (1990-2011)” article forthcoming in Palliative Medicine
4
Aims and objectives
• To undertake a program of research using linked data to examine
resource use, costs and quality of end of life care and to
investigate the factors associated with these outcomes for cancer
and non-cancer patients.
• In our first study within this program of research:
– To quantify resource use and costs in the last 6 months of life in a cohort of
elderly decedents
– To compare resource use and costs for decedents with and without a
cancer diagnosis
– To examine the distribution of resource use and costs across different types
of medical services at the end of life
– To determine the predictors of resource use and costs at the end of life
– To examine trends in resource use and costs over the 6 months to death
5
Study population and data sources
• Department of Veterans’ Affairs (DVA) gold card holders who
died between 2005 and 2009 and resided in NSW for the last
18 months of life
- DVA clients include eligible veterans, war widows and widowers
and their dependents
- Gold card holders are funded by the DVA for treatment of all
health conditions
- PBS, RPBS, other sundry pharmaceutical items
- MBS, dental and allied health services
- Hospitalisations and emergency presentations
6
Study population and data sources
• Age >=65 at death, Last 6 ‘months’ (180 days) of life
• Cancer cohort, N=9,862: identified by notifiable cancer
diagnosis or cause of death (CCR and ABS)
• Non-cancer cohort, N=15,483: no notifiable cancer diagnosis
(also excluded if received any cancer-related services)
• Datasets linked by the CHeReL
(provided by the DVA and NSW ministry of health)
– DVA client database
– PBS and RPBS and additional DVA approved items
– MBS, dental and allied health
– NSW registry of births deaths and marriages
– NSW Central Cancer Registry
– Admitted patient data collection
– Emergency department data collection
7
Methods: utilisation
• Compare utilisation of services for cancer and non-cancer
patients by service type and patient characteristics
• Report on utilisation of services in last 6 months of life and by
proximity to death (months to death)
– Medicines (includes PBS, RPBS and sundry items)
– Health care services (MBS, dental, community nursing, allied health)
– Hospital admissions (episodes of care)
– Emergency department visits
• Negative binomial regression of predictors of resource
utilisation
* Detailed methods outlined in Langton et al “Resource use, costs and quality of end of
life care: Observations in a cohort of elderly Australian cancer decedents” under review
by the DVA, to be submitted as a protocol paper
8
Methods: costs
• Allocate costs to resource items and report by service type and
overall for cancer and non-cancer patients.
• All costs expressed in common year (2009/10 reflecting most
recently published NSW Cost of Care Standards Report)
• NSW Cost of Care Standards used to derive hospitalisations
and ED costs in last 6 months of life.*
• Medications and health care services costs inflated to 2009/10
using inflation rates derived from AIHW published price indices.
• Report on utilisation of services in last 6 months of life and by
proximity to death (months to death)
• Negative binomial regression of predictors of total resource cost
* See Reeve and Haas, 2014, “Estimating the cost of Emergency
Department presentations in NSW.” CHERE Working Paper 2014/01'.
9
Cohort characteristics
Sex, F% : M%
Median age at death (range), years
Age 85+ at death, %
SEIFA decile, %
1 - 2 Most disadvantaged
3 -4
5-6
7- 8
9 - 10 Least disadvantaged
Unknown
Remoteness area, %
Major cities
Inner Regional
Outer Regional
Remote
Very Remote
Unknown
Co-morbidity burden %
0
1-2
3-5
>6
10
Cancer (n=9862)
Non Cancer (n=15,483)
31.6 : 68.4
86 (65 - 107)
55.7
48.9 : 51.4
87 (65 - 111)
65.9
11.8
28.7
20.6
14.4
20.5
4.1
12.0
28.9
19.9
14.5
20.6
4.1
62.3
28.2
8.8
0.4
0.1
0.2
61.6
28.4
9.1
0.5
0.0
0.4
4.9
13.4
39.9
41.8
5.5
13.8
39.5
41.2
Resource utilisation in the last 6 months of life
Utilisation
Emergency visits
Hospital episodes
Health care services, OOH
Non-Cancer
Cancer
Health care services, OOH + in hospital
Prescribed medicines
0
10
20
30 40 50 60 70
Mean resources utilised
80
90 100
Health care services include MBS, dental, community nursing
and allied health items
11
Resource costs in the last 6 months of life
Cost
Emergency visits
Hospital episodes
Health care services, OOH
Non-Cancer
Cancer
Health care services, OOH + in hospital
Prescribed medicines
Mean resource cost
Health care services include MBS, dental, community nursing
and allied health items
12
Resource utilisation and costs
by month to death: ED visits
Mean ED visits per person
per month
Utilisation
0.6
0.5
0.4
0.3
0.2
0.1
0
Cancer
Non-Cancer
6
5
4
3
Month to death
2
1
Mean ED cost per person
per month
Cost
300
250
200
150
100
50
0
Cancer
Non-Cancer
6
5
4
3
Month to death
2
1
13
Resource utilisation and costs
by month to death: Hospital episodes
Mean hospital episodes per
person per month
Utilisation
1.2
1
0.8
0.6
0.4
0.2
0
Cancer
Non-Cancer
6
5
4
3
Month to death
2
1
Mean hospital cost per
person per month
Cost
12000
10000
8000
6000
4000
2000
0
Cancer
Non-Cancer
6
5
4
3
Month to death
2
1
14
Resource utilisation and costs
by month to death: Health care services*
Mean health care services
per person per month
Utilisation
30
25
20
15
10
5
0
Cancer
Non-Cancer
6
5
4
3
Month to death
2
1
Mean health care services
cost per person per month
Cost
2,500
2,000
1,500
Cancer
1,000
Non-Cancer
500
0
6
5
4
3
Month to death
2
1
* Includes MBS, dental, community nursing and allied health items (in and out of hospital)
15
Resource utilisation and costs
by month to death: prescribed medicines
Mean prescribed medicines
per person per month
Utilisation
10
8
6
4
Cancer
2
Non-Cancer
0
6
5
4
3
Month to death
2
1
Mean prescribed medicine
cost per person per month
Cost
400
300
200
Cancer
100
Non-Cancer
0
6
5
4
3
Month to death
2
1
16
Total resource costs by month to death:
Cancer cohort
17
Total resource costs by month to death:
Non-Cancer cohort
18
Regression results: ED presentations
Results expressed as incident rate ratios (IRR) – base category IRR = 1
Also controlled for sex, year of death, comorbidities (Charlson and Rx risk)
19
Regression results: Hospital episodes
Results expressed as incident rate ratios (IRR) – base category IRR = 1
Also controlled for sex, year of death, comorbidities (Charlson and Rx risk)
20
Regression results: Health care services
Results expressed as incident rate ratios (IRR) – base category IRR = 1
Also controlled for sex, year of death, comorbidities (Charlson and Rx risk)
21
Regression results: Prescription medicines
Results expressed as incident rate ratios (IRR) – base category IRR = 1
Also controlled for sex, year of death, comorbidities (Charlson and Rx risk)
22
Regression results: Total cost of EoL care
Results expressed as incident rate ratios (IRR) – base category IRR = 1
Also controlled for sex, year of death, comorbidities (Charlson and Rx risk)
23
Discussion
• Previous local research has focused on hospitalisations, ED
and palliative care (in NSW only hospitalisations)
• We have extended this to provide a more complete picture
over multiple resource types
• People with cancer have higher total EoL health care costs
and use more of all resource types
• Our findings with respect to decreased EoL costs for
hospitalisations in older age groups is consistent with NSW
general population research
• Our findings also suggest that overall recourse use and costs
of care to the health system are lower for older age cohorts
• This has implications for planning in the context of an ageing
population – whilst more people are aged >65 more will be
dying at older ages
24
Future analyses
• Detailed investigation of utilisation and costs by subcategories of resource types
• Subgroup analyses by patient characteristics
• Disaggregate cancer cohort by whether cancer was the
cause of death (58.9% of cancer cohort died of cancer)
• Investigate specific cancer types
• Develop indicators of quality of care for our data based on
international validated indicators identified in the literature
and report on these (examples to follow)
• Expand our approach to a general population
• Inform data collections by CINSW and CCNSW – collecting
and making better use of data
25
‘Aggressiveness of Care’ Indicators
Chemotherapy
Last 14 days
Last 30 days
Emergency Department Visits
Last 14 days
>1 visit last 30 days
Hospital Admissions
Last 7 days
Last 30 days
>1 admission last 30 days
>14 days of last 30 days in hospital
Intensive Care Unit Admissions
Last 14 days
Last 30 days
Life Sustaining Treatments
CPR last 30 days
Intubation last 30 days
Mechanical ventilation last 30 days
Rate (%)*
Previous Studies
1-19
10-38
7
3
27-37
7-19
3
6
16
45-64
8-33
11-58
1
2
4
3
5-6
3-19
2
6
7-12
17-27
19-33
2
2
2
* Rate = average rate of use in cancer cohort (if reported) in previous studies
Langton J et al “End-of-life resource utilization and costs: A systematic review of
retrospective observational studies of cancer decedents using health
administrative data (1990-2011)” article forthcoming in Palliative Medicine
26
Palliative Care Indicators
Hospice Enrolment
≤3 days before death (late enrolment)
≤7 days before death (late enrolment)
No enrolment last 30 days
Enrolment duration ≥2 months (appropriate enrolment)
‘Prior to death’
>180 days before death (inappropriate enrolment)
Opioids
Outpatient prescription short- or long-acting last 30 days
Outpatient prescription short- or long-acting last 60 days
Other
Physician house call last 14 days
Community follow-up last 6 months
Home care last 6 months
Rate (%)*
Previous Studies
11-36
19-23
66
6-29
51-57
6-8
6
2
1
2
2
1
25
46
1
1
25-28
16
21-78
1
1
2
* Rate = average rate of use in cancer cohort (if reported) in previous studies
Langton J et al “End-of-life resource utilization and costs: A systematic review of
retrospective observational studies of cancer decedents using health
administrative data (1990-2011)” article forthcoming in Palliative Medicine
27
Acknowledgements
This research is supported by a NHMRC Capacity
Building Grant (571926) and a Cancer Australia
Grant (568773). S Pearson is also supported by a
Cancer Institute NSW Career Development
Fellowship (09/CDF/2-37)
Special thanks to the Department of Veterans’
Affairs and their clients
28