1. Maria M. Hofmarcher, M. Riedel, G. Röhrling Institute for Advanced Studies - Vienna, IHS HealthEcon Is health care expenditure susceptible to health policy? An econometric evaluation of determinants of Austrian health care expenditure

2. October 2, 2003IHS HealthEcon2 Overview What do cross country estimations tell us about the determinants of health care expenditure in the past? What do single country studies add? How can we translate this into forecasts for health care expenditure?

3. October 2, 2003IHS HealthEcon3 Driving Forces for Health Expenditure in the Past – Methods Used Cross-section studies – first generation Bivariate regressions Multivariate regressions Cross-section studies – 2nd generation Panel-data analyses Single-country studies

4. October 2, 2003IHS HealthEcon4 Driving Forces - Results from the Past Is health care a luxury good? Demographic variables Ageing, death costs, morbidity, education… Institutional variables Supply side factors Doctors, beds Price measurement

5. October 2, 2003IHS HealthEcon5 What did we learn for forecasts of health expenditure? Demographic component might gain importance – see population forecasts

6. October 2, 2003IHS HealthEcon6 Today, we have one youth for each person older than 65......but in 2030, we will have almost two elderly for each youth.

7. October 2, 2003IHS HealthEcon7 What did we learn for forecasts of health expenditure? Demographic component might gain importance – see population forecasts Are simple forecasts exaggerated by ‚Death Costs‘?

8. October 2, 2003IHS HealthEcon8 Death costs do not change expenditure forecasts too much...

9. October 2, 2003IHS HealthEcon9 What did we learn for forecasts of health expenditure? Demographic component might gain importance – see population forecasts Are simple forecasts exaggerated by ‚Death Costs‘? – yes, but not too much Does compression of morbidity ease the burden?

10. October 2, 2003IHS HealthEcon10 Compression of morbidity (Very) good health status according to age groups in percent, Austria Source: Doblhammer, Kytir 2001 women men

11. October 2, 2003IHS HealthEcon11 What did we learn for forecasts of health expenditure? Demographic component might gain importance – see population forecasts ‚Death Costs‘ exaggerate somewhat Does compression of morbidity ease the burden? – probably yes Partly by increased education levels?

12. October 2, 2003IHS HealthEcon12 Education and health Many studies observe better health in better educated population groups Causality unclear: better use of health resources (Grossman 1972) Unobserved causes for both, health and education (Fuchs 1982) Incorporation into forecasts is scarce, but suggests beneficial effect

13. October 2, 2003IHS HealthEcon13 What did we learn for forecasts of health expenditure? Demographic component might gain importance – see population forecasts ‚Death Costs‘ exaggerate somewhat Compression of morbidity probably eases the burden Partly by increased education levels Macroeconomic framework

14. October 2, 2003IHS HealthEcon14 Macroeconomic framework Demography related Participation rates Unemployment Productivity Overall economy Health sector

15. October 2, 2003IHS HealthEcon15 What did we learn for forecasts of health expenditure? Demographic component might gain importance – see population forecasts ‚Death Costs‘ exaggerate somewhat Compression of morbidity probably eases the burden Increased education levels as well Macroeconomic framework Technical Progress – next session

16. October 2, 2003IHS HealthEcon16 Part II: What do cross country estimations tell us about the determinants of health care expenditure in the past? What do single country studies add? How can we translate this into forecasts for health care expenditure in Austria?

17. October 2, 2003IHS HealthEcon17 Our approach Time series model: 1960 to 2000 Endogenous: growth rate of total per-capita health expenditure, in constant 1995 prices.

18. October 2, 2003IHS HealthEcon18 Determinants of Austrian Health Care Expenditure Demand factors An increasing share of people 65+ increases health expenditure noticeably. A higher number of deaths increases health expenditure slightly. An increasing life expectancy of the elderly is reducing health expenditure (compression of morbidity). Supply and Policy factors An increase in the number of radiologists increases health expenditure somewhat (supplier induced demand). The rise in acute-care beds leads also to rising health care expenditure. A high level of health expenditure leads to lower growth rates of health expenditure.

19. October 2, 2003IHS HealthEcon19 „Resistant policy“ leads to a noticeably higher GDP share spent on health Forecast of health care expenditure in percent of GDP, 2000 to 2020 Source: IHS HealthEcon 2002

20. October 2, 2003IHS HealthEcon20 How do/did each supply and demand factor contribute to expenditure growth? Scenario „neutral“, growth rates in percent IHS HealthEcon 2002

21. October 2, 2003IHS HealthEcon21... and finally We demand more efforts on the theory of the macroeconomic analysis of health expenditure, which is underdeveloped at least relative to the macroeconometrics of health expenditure Gerdtham / Jönsson: International Comparisons of Health Expenditure, Handbook of Health Economics 2000

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23. October 2, 2003IHS HealthEcon23

24. October 2, 2003IHS HealthEcon24 Age or Death related costs? Health expenditure for persons in their last year of life USA: 20-30% (Scitovsky, Capron 1986) UK: 29% of hospital costs (Seshamani, Gray 2003) A: 10-18% of public hospital costs (Riedel et al 2002)

25. October 2, 2003IHS HealthEcon25 Pros and Cons for future compression of health expenditure PRO: Increasing life expectancy also in high LE (= rich) countries and high LE population groups (Wilkinson 1996) CON: We do not observe any tendency that the prevalence of highly resource consuming diseases like Dementia and Alzheimer declines like prevalence of ‚physical‘ diseases (Wancata et al 2001) CON: pop share of disabled increasing recently Upshot: Better health could reduce growth of acute expenditure to 2/3 of the unadjusted growth rates.

26. October 2, 2003IHS HealthEcon26 Education reduces bad health 19962020 Men – no edu Men - edu 21.0 24.2 21.9 Women – no edu Women - edu 25.3 27.0 24.8 Source: Joung et al (2000) Population share in less-than-good-health

27. October 2, 2003IHS HealthEcon27 Policy Scenarios for 2000-2020 ScenariosAcute care bed densitiesRadiologist densities Neutral decreases as observed between 1960 and 2000 increases as observed between 1990 and 2000 Resistant constant on level of 2000increases twice as fast as observed between 1990 and 2000 Pro- gressive decreases more quickly than before and levels off in 2020 increases slower than in the past Source: IHS HealthEcon 2002

28. October 2, 2003IHS HealthEcon28 Future research questions To which extent do relative prices influence health expenditure development? How do various productivity assumptions translate into expenditure growth? Is the compression of morbidity sufficiently strong to counterbalance the rising share of the elderly?

29. October 2, 2003IHS HealthEcon29 Ergebnisse der Zeitreihenanalyse: Parameterschätzungen (t-Werte) für die WR gesamten Gesundheitsausgaben IHS HealthEcon 2002