Post on 21-Aug-2020
EXPENDITURE BY DISEASE, AGE & GENDER
15th meeting of the health accounts experts
• In 2007-08, project “Estimating Expenditure by Disease, Age and Gender under the System of Health Accounts (SHA) Framework”
– Guidelines developed
– Case studies of 6 countries
• Between 2011-2013, the follow-up project is launched to accelerate consistent and comparable health expenditure data by disease categories
– Increase # of countries for hospital (i.e. inpatient care) sector
– Expand the data collection beyond hospital expenditures to include outpatient (ambulatory) and pharmaceutical spending
– Investigate the use of other sources when resources do not allow for a full expenditure study (e.g. activity data)
– Assess the link between direct, indirect and intangible costs
Background and Objectives
SHA 2011 Framework
SHA Framework in Disease Accounts
Cost of Illness = Direct costs + Indirect Costs + Intangible costs
Direct (the National Health Service) + Indirect (ratio of indirect to direct costs) + intangible costs using WHO Global Burden of Disease data
Example of Direct, Indirect and
Intangible Costs
Economic burden of disease in England by disease
direct, indirect and intangible costs(indirect costs estimated using Canadian ratios : direct costs)
£0
£20,000
£40,000
£60,000
£80,000
£100,000
£120,000
£140,000
£160,000
Infe
ctio
us a
nd
para
sitic
dis
ease
s
Neo
plas
ms
Blo
od
End
ocri
ne,
nutr
ition
al a
nd
met
abol
ic
Men
tal/n
ervo
us
Eye
/ear
dis
ease
s
Cir
cula
tory
Res
pira
tory
Dig
estiv
e sy
stem Ski
n
Mus
culo
skel
etal
Gen
itour
inar
y
Pre
gnan
cy/p
erin
atal
Con
geni
tal
mal
form
atio
ns
Oth
er
Mill
ions
(£)
Intangible costs
Indirect costs
Direct costs
2011
Economic Burden of Disease in England, 2011
Source: Department of Health, 2013
Top-down allocation of expenditures
SHA Current Health Exp.
Partition into homogeneous cost units (HP, HC, HF)
Hospital in-patient
Hospital out-
patient
Dentist offices
Specialists ….. GP
offices
Use a cost unit specific utilisation key to allocate costs over dimensions (disease, age, gender)
• Increased from 6 in 2008 to 16 countries in 2011-13 – Mostly in hospital or inpatient spending
– Australia, Canada, Czech Republic, England, Finland, France, Germany, Hungary, Israel, Japan, Korea, the Netherlands, Slovenia, Sweden, Switzerland, and the United States
– Not all countries follow SHA framework (e.g. Germany, Korea and Netherlands v.s. England, Japan)
Overall data availability
Type Frequency Countries Disease Groups Direct cost components
Regularly producing
Regular (1-3 years)
Australia Canada Germany Netherlands Japan
Country-specific categories (all), but can be re-grouped to ICD-10/ISHMT
Direct costs by all HPs
Capable of producing
on an ad-hoc basis or on demand
Czech Republic Hungary Korea Sweden Finland Slovenia Israel Switzerland
ICD chapters, ISHMT
Direct costs by some HPs (mainly hospitals) or HCs (inpatient)
Producing but not official
Frequent (i.e. annual)
England Country-specific categories or GBD only
Varies
Countries at different stages of
production in disease accounts
Top spending in inpatient/hospital care
(HC.1.1/HP.1)
0%
5%
10%
15%
20%
25%
30%
IX - Circulatory system II - Cancer XIX - Injuries XIII - Musculoskeletal XI- Digestive system
• high share of spending on circulatory diseases in the inpatient sector in most countries (around 18% on average) with a range between below 15% in Australia and Korea and 25% or more in Japan and the Czech Republic
Mental Health by ISHMT (1)
0%
5%
10%
15%
20%
Canada(2008)
Czech Republic(2009)
Finland(2010)
Germany(2008)
Korea(2009)
Netherlands(2007)
Dementia Alcohol Psychoactive substances Schizophrenia mood disorders other mental
• Chapter V, Mental and Behavioural Disorders, consists of dementia and other mild to severe mental health conditions, thus, further breakdown is preferable.
• Higher share of spending on treatment of schizophrenia in Finland and Korea while mood disorders make up a higher share in Germany and the Netherlands.
Breakdown of different mental health conditions as a share of acute in-patient expenditures
Mental Health by ISHMT (2)
• Hospitals are by far the common platform to provide care of those with mental health conditions, followed by long-term care insititutions.
• Ambulatory sector plays a large role in caring of mental health patients in Czech Republic comparing to other countries.
• Per capita spending differs greatly from country to country. For example, hospital spending ranges from US$295 (NLD), $147 (DEU), $71.7 (KOR) and $36 (CZE).
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Germany Korea Netherlands Czech Republic
Breakdown of mental health conditions by ISHMT
Hospital Long-term care Ambulatory Pharmaceuticals Other providers
0%
5%
10%
15%
20%
25%
30%
35%
DEU FRA KOR JPN NLD SVN Average
Digestive system Symptoms/Other factors Musculoskeletal system Circulatory system Respiratory system Genitourinary system
Top spending in outpatient/ambulatory
sector
• On average 25% of outpatient spending relates to Chapter XI (Digestive system) which includes expenditure on oral health.
• Between 6 and 10% on average, relate to Chapter XIII (Musculoskeletal), Chapter X (Respiratory) and Chapter XIV (Genitourinary).
• Challenges are that the sector combines separate data sources and the greater role of private financing
• Availability of medical goods and particularly pharmaceuticals which typically account for around 90% of the category.
• Chapter IX: Circulatory disease accounts for 20% on average of pharmaceutical spending and more than twice the level of the next category, Chapter X: Respiratory system.
Top spending on medical goods/retailers
0%
5%
10%
15%
20%
25%
30%
DEU FRA HUN KOR NLD SVN Average
Circulatory system Respiratory system Disease of the eye Endocrine, nutritional Digestive system
• Difficulties in allocating across the SHA classification categories (e.g. different data sources, private spending)
• Unallocated amounts (0% in Korea and Germany up to 35% in Czech Republic for CHE)
• Allocation by provider versus function
• The lack of or reduction in resources in statistical offices and ministries
• Reason for identifying other ‘short-cuts’ through existing data (e.g. activity data such as hospital discharge, etc)
Challenges need to be addressed
• Question: Is it possible to derive expenditures using the data from countries with good expenditure by disease data and health utilisation data (e.g. bed-days)? – Using per-diem (which assumes all bed-days for
all diseases use are the same) not enough
– Resource intensity is not homogeneous across treatment of different diseases • E.g. Diagnosis Related Groups (DRGs) classifying
patient based on primary diagnosis used for reimbursement of hospital stays
Deriving expenditure by disease for in-
patient curative care (1)
• Steps: – Using country specific health utilisation data (e.g.
bed-days by ICD), health spending and health data (e.g. morbidity and mortality)
– Coming up with average weight by ICD by country [the ratio of the share of expenditures (as a percentage of all hospital spending) to the share of bed-days (as a percentage of all bed-days), by diagnostic category]
– Fitting a regression model to see if we can actually ‘predict’ the level of spending (i.e.%)
– Filling information gaps of countries that do not produce expenditure by disease category
Modeling inpatient expenditures using
activity data (2)
Average weights (initial)
0.0
0.5
1.0
1.5
2.0
2.5
I. I
nfe
ctio
us
an
d p
ara
siti
c d
isea
ses
II.
Neo
pla
sms
III.
Dis
ease
s o
f th
e b
loo
d
IV.
En
do
crin
e,et
c d
isea
ses
V.
Men
tal
dis
ord
ers
VI.
Ner
vo
us
syst
em
VII
. E
ye a
nd
ad
nex
a
VII
I. E
ar
an
d m
ast
oid
pro
cess
IX.
Cir
cula
tory
sy
stem
X.
Re
spir
ato
ry s
yst
em
XI.
Dig
esti
ve
syst
em
XII
. S
kin
an
d s
ub
cuta
neo
us
tiss
ue
XII
I. M
usc
ulo
skel
eta
l sy
stem
XIV
. G
en
ito
uri
na
ry s
yst
em
XV
. P
reg
na
ncy
etc
XV
I. P
erin
ata
l p
eri
od
XV
II.
Co
ng
enit
al
ma
lfo
rma
tio
ns
XV
III.
Sy
mp
tom
s, e
tc,
n.e
.c.
XIX
. In
jury
(e
xte
rna
l ca
use
s)
XX
I. O
ther
fa
cto
rs i
nfl
uen
cin
g h
ealt
h
• Model 1: employed ICD chapter level data
• Model 2: employed ISHMT level data
• E.g. Canada - Results: predicted expenditure values, as expected, perform better than using straight bed-days as an allocation key
Modelling and filling information gaps
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
bed-days exp model 1 model 2
• Expenditure on medical goods accounts for 23% of CHE across EU on average
• Private spending data is limited (e.g. OTC medicines)
• An inventory of pharmaceutical consumption and sales figures has also been compiled
• Australia, Canada, Germany, Korea, and the Netherlands, are examples
• Australia and the Netherlands reply upon national physician surveys. Korea from social insurance data. Canada and Germany from IMS
• Mapping ATC to ICD needed
Linking Pharmaceutical Data to Disease
• Derive a general, or average, mapping based on the data that is currently available for Australia, and the Netherlands based on the national samples of physicians.
• Derive a general, or average, mapping based on the data that is currently collected by IMS.
• Use the country-specific data that IMS collects in the 24 OECD countries. Under this option there further exists the option of using IMS’ data on expenditures or the available national data.
Options on mapping from ATC to ICD
• Data: physician surveys or bottom up methods based on encounter data.
• Less variation in the intensity of services according to disease, particularly for basic GP consultations.
• A clear relationship between number of consultations per disease category and the resource costs of the associated health care services.
• In the absence of detailed costing data, the use of basic encounter information (i.e. ambulatory sector to total numbers of outpatient/ physician and dentist consultations) can be used.
Linking Physician/Outpatient Spending
to Disease
• The Bettering the Evaluation and Care of Health (BEACH) programme continuously collects information about the clinical activities in general practice in Australia including: – characteristics of the GPs
– patients seen
– reasons people seek medical care
– problems managed, and for each problem managed (direct link)
• Data from BEACH were used to allocate private medical services provided by both GPs and specialists.
Example of Australian BEACH survey
• Data is allocated according to ICD-10 chapters at minimum;
• Using International Hospital Morbidity Short List (ISHMT) to properly analyse the expenditures associated with specific diseases;
• All attempts should be made to allocate as possible; where data is lacking expenditures should remain unallocated; and
• The frequency of reporting needs to be standardised (3 years, for example).
Overall recommendations
• The OECD.Stat data warehouse as summary tables
– The accessibility of the data and the transparency of the methodologies will act as a spur to improve the country coverage and comparability in the future.
• Dedicated page for health spending by disease will be created as part of the OECD SHA website.
• Health Working Paper comparing the methodologies and results of the available country data is planned to be released by Q1 2014.
Dissemination Plan (1)
• The following tables and charts are expected to be made available:
– Current health expenditure by ICD chapter (age, gender) - NCU, % current health spending, per capita spending;
– Hospital/inpatient expenditure by ICD chapter (age, gender) - NCU, % total hospital/inpatient spending, expenditure by discharge / bed day;
– Outpatient/ambulatory expenditure by ICD chapter (age, gender) - NCU, % total outpatient/ambulatory spending;
– Medical goods expenditure by ICD chapter (age, gender) - NCU, % total medical goods spending.
Dissemination Plan (2)
• More innovative and dynamic charts for countries and changes over time will be produced
In bubble charts
I. Infectious diseases 3.0%
II. Neoplasms 10.9%
III. Diseases of the blood 0.8%
IV. Endocrine,etc diseases 2.3%
V. Mental disorders 7.4%VI. Nervous system
3.0%
VII. Eye and adnexa 0.4%
VIII. Ear 0.4%
IX. Circulatory system 17.7%
X. Respiratory system6.3%
XI. Digestive system 7.6%
XII. Skin 0.9%
XIII. Musculoskeletal system 7.0%
XIV. Genitourinary system 4.0%
XV. Pregnancy etc 5.3%
XVI. Perinatal period 2.3%
XVII. Congenital malformations 1.3%
XVIII. Symptoms, etc, n.e.c. 4.7%
XIX. Injury 11.6%
Other 3.0%
Total hospital inpatient
expenditure72 242 mln SEK
2011
• COMMENT on the plans to disseminate available data;
• REVIEW the country data sources in Chapters 5, 7 and 8;
• INFORM the Secretariat of the intention to undertake expenditure by disease studies in the near future.
The Secretariat invites participating
experts to: