Place of death for people who may benefit from palliative care: How does New Zealand compare in a multi-national population-level study? Wayne Naylor

1. Place of death for people who may
benefit from palliative care: How
does New Zealand compare in a
multi-national population-level
study?
Wayne Naylor, Hospice Waikato
(on behalf of the End of Life Care Research Group)
Hospice NZ Conference, November 2014
1

2. International Place of Death Study
(IPoD) Authors
Lara Pivodic, Koen Pardon, Lucas Morin, Julia
Addington-Hall, Guido Miccinesi, Marylou
Cardenas-Turanzas, Bregje Onwuteaka-Philipsen,
Wayne Naylor, Miguel Ruiz Ramos, Lieve Van den
Block, Donna Wilson, Martin Loucka, Agnes
Csikos, Yong Joo Rhee, Joan Teno, Luc Deliens,
Dirk Houttekier, Joachim Cohen
2

3. Why does place of death matter?
 Increasing number of people dying of
chronic conditions
 Patient preference to die at home
 Deaths in hospital still high and increasing
◦ Avoidable admissions
◦ Burdensome/aggressive treatments
◦ High cost
 Changing policies worldwide to focus on
enabling death in community settings
 Few cross-national comparisons of PoD
3

4. Why does place of death matter?
 Essential for planning, implementation
and evaluation of policy decisions
 Optimal allocation of health and social
care resources
 International benchmarking
 Reveal inequities
 Provide hypotheses about alternative
ways to provide EOLC
4

5. Aim of the study
 To describe and compare place of death
for people who died of diseases indicative
of palliative care need in 14 countries
across four continents
◦ to what extent place of death is associated
with socio-demographic characteristics,
cause of death, and healthcare supply
◦ to what extent differences in these
characteristics explain country-differences in
place of death
5

6. Method
 Part of the IPoD Study
 27 countries approached
 14 countries provided anonymized individual death
certificate data for the full population of deaths
during one year (2008)
◦ Belgium ◦ New Zealand
◦ England ◦ Spain (Andalusia, 2010)
◦ Wales ◦ Canada
◦ France ◦ Czech Republic
◦ Italy ◦ Hungary
◦ Mexico ◦ South Korea
◦ Netherlands ◦ USA (2007)
 Data collected during 2011-2013
6

7. 7

8. Variable Categories NZ data fields equivalent
PLACE OF DEATH  Hospital
 Care home / long term care
institute/ residential care
 Home/private residence
 Hospice
 Other institute
(drug/alcohol/IHC facility)
 Other
 Unknown
Place of death category
(as per Needs Assessment data
set)
AGE (continuous) exact age Age at death
SEX  male
 female
Sex
SOCIO-ECONOMIC-STATUS ??? NZ deprivation index decile
Underlying CAUSE OF DEATH In ICD-10 codes Underlying cause of death
(Diagnosis type ‘D’)
MUNICIPALITY OF RESIDENCE Code TLA of domicile
MUNICIPALITY OF DEATH ZIP code TLA of domicile
DHB of domicile
CITIZENSHIP/RACE/ETHNICITY New Zealand vs. other Ethnic group (prioritised at level 2)
INTERMEDIARY CAUSES OF
DEATH
In ICD-10 codes Other contributing causes
(Diagnosis type ‘G’)
IMMEDIATE CAUSE OF DEATH In ICD-10 codes (as above for underlying cause of
death)
COMORBIDITIES In ICD-10 codes Other relevant diseases present
(Diagnosis type ‘F’)
8

9. Study Population
 All deaths of persons aged 1 year and over
 Those who would benefit from palliative
care
◦ Underlying cause of death corresponding to
Minimal Estimate of the potential palliative care
population (by ICD-10 code) (Rosenwax et al., 2005)
◦ Cancer ◦ Motor neurone disease
◦ Heart failure ◦ Parkinson’s disease
◦ Renal failure ◦ Huntington’s disease
◦ Liver failure ◦ Alzheimer’s disease
◦ COPD ◦ HIV/AIDS
9

10. Study data: dependent variable
 Place of death
◦ Home
◦ Hospital
◦ Long-term care facility
◦ Other
 Similar certification of deaths in all countries
 Death certificate data were linked with statistics on
density of hospital and long-term care beds, and GPs
per health region
Hungary: hospital vs other
Mexico: home vs hospital vs other
England, Wales, New Zealand, USA:
additional category palliative
care institution
10

11. Study data: independent variables
 Socio-demographic
◦ age, sex, marital status
 Clinical
◦ underlying cause of death
 Residential
◦ degree of urbanization of region of residence
 Healthcare supply
◦ density of hospital and long-term care beds
and GPs per region of residence
11

12. Results
 Total deaths N = 5,570,066
 Study population N = 2,330,843
 % of deaths in different settings
 Multivariable binary logistic regression
 Hierarchical binary logistic regression analysis
with the dependent variable death at home vs in
hospital
◦ Model 1 - country
◦ Model 2 - cause of death, age, gender, marital status
◦ Model 3 - health care supply
◦ Belgium as reference country
12

13. Cause of death in total population
(N = 5,568,827)
31 29.4
13.2
8.9 17.2
0.7
5.9
1
60
50
40
30
20
10
0
IT ES FR BE NL ENG WAL CZ HU NZ US CA KR MX
Cancer Organ failure Diseases of the nervous system HIV/AIDS
13

14. Population potentially benefitting from PC
 Italy 41.9%
 Spain (Andalusia) 46.9%
 France 43.5%
 Belgium 43.5%
 Netherlands 48.8%
 England 41.5%
 Wales 41.2%
 Czech Republic 32.6%
 Hungary 38.8%
 New Zealand 44.3%
 USA 45.3%
 Canada 46.3%
 South Korea 37.6%
 Mexico 24.9%
14

15. Place of death (N = 2,220,997)
23
13
53
25
28
85
35
33
1
13
4
100
90
80
70
60
50
40
30
20
10
0
FR IT ES BE NL ENG WAL CZ HU NZ CA US MX KR
Home Hospital LTC setting PC institution
15

16. Death at home in relation to cause of
death (N = 2,220,997)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
FR IT ES BE NL CZ ENG WAL NZ CA US MX KR
Cancer Non-cancer
Home death more likely if death from cancer
(multivariable analysis controlling for sex, age,
marital status, degree of urbanization, healthcare
supply)
16

17. Death at home in relation to age
(N = 2,220,997)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
FR IT ES BE NL CZ ENG WAL NZ CA US MX KR
≤69 70-79 ≥80
Home death more likely if <80 years
(multivariable analysis controlling for sex, cause of
death, marital status, degree of urbanization,
healthcare supply)
17

18. Factors associated with home death
(N = 1,544,759) - Reference category: Belgium
1.99
0.71
1.25
2.87
0.51
0.59
0.93
0.74
0.43
1.71
2.44
0.33
KR
MX
US
CA
WAL
ENG
CZ
NL
FR
IT
1.93
0.68
1.25
2.97
0.61
0.98
0.77
0.42
1.99
3.13
0.32
0.96
0.69
0.46
2.40
0.38
0.60
0.30
1.03
0.72
0.23
ES
0 0.5 1 1.5 2 2.5 3 3.5
OR model 1
OR model 2
OR model 3
18

19. Conclusions
 Considerable differences in place of death
and factors associated with it between
countries
 Variations only partly explained by
differences in independent variables
 Indicate current settings for EOLC
 Highlight settings in need of evaluation of
availability and quality of PC and EOLC
 High number of hospital deaths in many
countries
19

20. http://endoflifecare.be
20