Ageing, Health Status and Determinants of Health Expenditure Data availability and comparability – challenges and possible solutions – (WPVIA) Dr. Erika

Ageing, Health Status and Determinants of Health Expenditure

Data availability and comparability – challenges and possible solutions – (WPVIA)

Dr. Erika Schulz

Erika Schulz28.06.2007

Determinants of health expenditure

Population Health size, age-structure Use of insurance

Life health Health Prices, schemesexpectancy Morbidity/ care expenditure costs

Acut services Supply/health status access

Medical/ Socio-economic General frameworktechnological determinants/ conditionsprogress healthy behavior/ (policies, rules,

genetic conditions assets, economy)



Aims of WP VI

– WP VI focuses on the determinants fo health spending taking into account of a combination of demand and supply factors.

– It aims at making predictions of changes in aggregate expenditure due to marginal changes in age composition by taking supply factors into account.

– The analyses include economic, institutional, demographic and social factors.


Determinants mentioned in previous studies

– As demand factors were mostly performed: age, sex, health status, income, marital status, household composition, activity status and dependency

– As supply factors were mostly performed: hospital beds, staff in hospitals, number of physicians, political decisions, general economic development, medical-technological progress (one result of a study for Germany was that technology is the main driver of health expenditure (Breyer 1999))


Health Care Expenditure

– HCE US$ PPP (in million)– HCE US$ PPP per capita– Public expenditure US$ PPP (in million)– Public expenditure US$ PPP per capita– Public expenditure as % of total HCE (US$ PPP per

capita)– Private payment as % of total HCE– Out-of-pocket payments (household) as % of total HCE– Private insurance as % of total HCE– All other privat funds as % of total HCE


Demand Factors I– Population– total population at 1. January– age-composition as share of total– 0-5,6-19,20-34,35-49,50-64,65-74,75-84,85+– life expectancy at birth– male– female– life expectancy at 65– male– female– total fertility rate – migration per 1000 inhabitants– crude death rate per 1000 population


Demand Factors II

– health status (share of people in bad health)– health behaviour: alcohol consumption– health behaviour: tobacco consumption– education level - attainment ISCED 0/1/2– education level - attainment ISCED 3/4– education level - attainment ISCED 5B– education level - attainment ISCED 5A/6

– Utilisation of health care services– doctor's consultation per capita– Acute care occupancy rate in % of available beds


Supply Factors

– physicians per 1 000 inhabitants– physicians per 100 hospital beds– acute care beds per 1 000 inhabitants– nursing and elderly home beds per 100 000 inhabitants– MRI (and CT scanners) per million inhabitants– (MRI and) CT scanners per million inhabitants– dialyses per 100 000 inhabitants


Health Care System I

– Organisational structure– Health care system (public contract, public integrated,

mixed)– Gatekeeper to non-acute hospital treatment or

specialist– Free choice GP or family doctor– Free choice of specialists– Free choice of hospitals– Free choice of dentists– Waiting lists for specialist care– waiting lists for surgeries in hospitals


Health Care System II

– Financing the health care system– Population covered by public health system % of total

population– Multiple or single source financing system– population covered by privates health insurance– Co-payment in connection with GP visits– Co-payment in connection with specialists visits– Co-payment in connection with hospital admission– Co-payments in connection with dentist care– Co.payments for pharmaceuticals


Health Care System III

– Reimbursement of hospitals– (global budget, fee-for-service, per diem, per discharge)– Reimbursement of physicians in hospitals– (fee-for-service, fixed salary)– Reimbursement of general practitioner – (fee-for-service, salary, capitation)– Reimbursement of specialists– (fee-for-service, salary, capitation)– Reimbursement of dentists– (fee-for-service, salary, capitation)– Overall ceiling of hospital expenditure


Framework conditions

– Gross domestic product per capita, US$ PPP– female labour force participation – unemployment rate in % of labour force


Data sources

– OECD Health Data Version 2004• Health care expenditure, education, docotrs consultation, supply of health care

services, acute care occupancy rate, population covered by public health care systrem. GDP per capita, share of female labour force in total labour force

– WHO Health For All database• Life expectancies at birth, and at age 65, crude death rates, heath behaviour

(alcohol, tobacco), nursing and elderly home beds

– EUROSTAT• Population

– ILO• Harmonized unemployment rates

– Health Care Systems in Transition reports, MISSOC, MISSCEEC• Institutional variables


Data comparability

– OECD Health Data Version 2004• The OECD has the principle to ensure that the data presented

in their database are as comparable as possible across countries and over time.

• For example: A System of Health Accounts was published with guidelines for reporting health care expenditure. Countries can be grouped in four categories: I (close to SHA): Denmark, France, Germany, Hungary, Netherlands, United Kingdom, Spain and Turkey. II (near by SHA): Finland and Poland. III (problems in international comparison): Greece, Portugal. IV (OECD estimates): Belgium.


Data comparability II

– The OECD data base is the most comparable data set, but nevertheless, in some cases the specification of HCE was not really clear (sometimes a part of HCE was included in other parts of the social budget)

– The different data sources show for the same variable different figures. Therrefore we decided to use as a main data base the OECD (combined with WHO data if possible) and for the population EUROSTAT.


Data included in the model estimating HCE- Demographic variables:

• AGE0-5, AGE65-74 and AGE75+(share of population aged .. in total population)

• AVELE65 (life expectancy at age 65)• MORTALITY (Crude death rate)

– Behavioural variables:• ALCCON (pur alcohol in litres per capita 15+ per year)

– Supply variables:• BEDS (acute care beds per 1000 inhabitants)

– Institutional variables• Reimbursement (SALARYGP, CAPGP, GLOBALHO, CASEHO)• Copayments (COPAYGP, COPAYHO)• Free choice (FREEGP, FREEHO)• PUSHES (share of public HCE in total HCE)

– Economic variables• GDP in US$ PPP per capita, UNEMPL


Conclusion

– The used data for the model are the most comparable data• Demographic variable stem from EUROSTAT and are comparable• Demand and supply factors stem from OECD and are most

comparable• Institutional variables are created by ourselfs and therefore

comparable• Only the definition of health care expenditure may be in some cases

not fully comparable, but OECD Health Data provided the most comparable data


Development of health care expenditure per capita US$ PPP 1980-2003 EU 15

0

500

1000

1500

2000

2500

3000

3500

1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Austria Belgium Denmark Finland France

Germany Greece Ireland Italy Luxembourg

Netherlands Portugal Spain Sweden United Kingdom


Health care expenditure per capita and share of people aged 65+ in 2001

4

6

8

10

12

14

16

18

20

0 500 1000 1500 2000 2500 3000 3500

HCE

Pro

port

ion

65+

TR

IT

GEBE

SWGR

ES

PTFRUK

A

DKFIHUETLA

SV

LI LUNECZRO

MTPL

IRECYSK


Changes in HCE per capita and changes in the share of people aged 65+ between 1980 and 2002 in selected countries

0

1

2

3

4

5

6

0 1 2 3 4 5 6

Changes in the share of people aged 65+

Cha

nges

in H

CE

per c

apita

PT

SPGR

FI

BE

NL

UK

SW

IRE

DK

LU

AU


Health care expenditure and GDP per capita in 2002

0

10 000

20 000

30 000

40 000

50 000

60 000

0 500 1000 1500 2000 2500 3000 3500

HCE per capita US$ PPP

GD

P p

er c

apit

a U

S$

PP

P

LU

IREDK NL

A FRUK BE

SV GEFI

ITES

GRSLCY

PT

MT

CZHUSK

EE

PLLV

LT

TRRO


Health care expenditure of % of GDP

0

2

4

6

8

10

12

1992 2002

Documents

Ageing, Health Status and Determinants of Health Expenditure Data availability and comparability – challenges and possible solutions – (WPVIA) Dr. Erika