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

October 2, 2003 IHS HealthEcon 2

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?

October 2, 2003 IHS HealthEcon 3

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

October 2, 2003 IHS HealthEcon 4

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

October 2, 2003 IHS HealthEcon 5

What did we learn for forecasts of health expenditure?

Demographic component might gain importance – see population forecasts

October 2, 2003 IHS HealthEcon 6

Today, we have one youth for each person older than 65...

...but in 2030, we will have almost two elderly for each

youth.

24% 17% 14%

62%68%

61%

14% 16% 25%

0%

20%

40%

60%

80%

100%

1970 2000 2030

65+

15-65

<15

October 2, 2003 IHS HealthEcon 7

What did we learn for forecasts of health expenditure?

Demographic component might gain importance – see population forecasts

Are simple forecasts exaggerated by ‚Death Costs‘?

October 2, 2003 IHS HealthEcon 8

ITALYBaseline scenario

ITALY

Death-costs scenario

NETHERLANDSBaseline scenario

NETHERLANDSDeath-costs scenario

SWEDEN

Baseline scenarioSWEDEN

Death-costs scenario

0

1

2

3

4

5

6

7

8

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Pu

blic

ex

pe

nd

itu

re o

n h

ea

lth

ca

re e

xp

res

se

d a

s a

sh

are

of

GD

P (

%)

Death costs do not change expenditure forecasts too much...

October 2, 2003 IHS HealthEcon 9

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?

October 2, 2003 IHS HealthEcon 10

Compression of morbidity(Very) good health status according to age groups in percent, Austria

Sou

rce:

Dob

lham

mer

, Ky t

ir 20

01

women men

0

10

20

30

40

50

60

70

60 65 70 75 80 85

1978

1983

1991

1998

0

10

20

30

40

50

60

70

60 65 70 75 80 85

1978

1983

1991

1998

October 2, 2003 IHS HealthEcon 11

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?

October 2, 2003 IHS HealthEcon 12

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

October 2, 2003 IHS HealthEcon 13

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

October 2, 2003 IHS HealthEcon 14

Macroeconomic framework Demography related

Participation rates Unemployment

Productivity Overall economy Health sector

October 2, 2003 IHS HealthEcon 15

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

October 2, 2003 IHS HealthEcon 16

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?

October 2, 2003 IHS HealthEcon 17

Our approach Time series model: 1960 to 2000

Endogenous: growth rate of total per-capita health expenditure, in constant 1995 prices.

j

k

jjjk xxxy

11 ln),....(ln

October 2, 2003 IHS HealthEcon 18

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.

October 2, 2003 IHS HealthEcon 19

„Resistant policy“ leads to a noticeably higher GDP share spent on health

Forecast of health care expenditure in percent of GDP, 2000 to 2020

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

neutral

progressive policy

resistant policy

Source: IHS HealthEcon 2002

October 2, 2003 IHS HealthEcon 20

How do/did each supply and demand factor contribute to expenditure growth?Scenario „neutral“, growth rates in percent

IHS HealthEcon 2002

-7,0%

-5,0%

-3,0%

-1,0%

1,0%

3,0%

5,0%

7,0%

Expenditure quotientLife expectancy at the age of 65Number of acute-care bedsNumber of radiologists Share of over 65-year-olds "net growth"

October 2, 2003 IHS HealthEcon 21

... 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

October 2, 2003 IHS HealthEcon 22

October 2, 2003 IHS HealthEcon 23

October 2, 2003 IHS HealthEcon 24

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)

October 2, 2003 IHS HealthEcon 25

Pros and Cons for futurecompression 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.

October 2, 2003 IHS HealthEcon 26

Education reduces bad health

1996 2020

Men – no eduMen - edu

21.021.0

24.221.9

Women – no eduWomen - edu

25.325.3

27.024.8

Sourc

e:

Joung e

t al (2

00

0)

Population share in less-than-good-health

October 2, 2003 IHS HealthEcon 27

Policy Scenarios for 2000-2020

Scenarios

Acute care bed densities Radiologist densities

Neutral decreases as observed between 1960 and 2000

increases as observed between 1990 and 2000

Resistant constant on level of 2000 increases 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

October 2, 2003 IHS HealthEcon 28

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?

October 2, 2003 IHS HealthEcon 29

Ergebnisse der Zeitreihenanalyse: Parameterschätzungen (t-Werte) für die WR gesamten Gesundheitsausgaben

Konstante -0,174 -0,159 -0,171 -0,108(-2,152) ** (-1,897) * (-2,062) ** (-0,641)

Anteil der über 65Jährigen an der Ges.bevölkerung 1,886 1,854 1,941 1,611-4,584 ** -4,447 ** -4,708 ** -3,511 **

Anzahl der Fachärzte für Radiologie pro 100.000 0,606 0,563 0,493 0,418-3,083 ** -2,738 ** -2,618 ** -1,403

Anzahl der aufgestellten Akutbetten pro 100.000 0,596 0,57 0,444 0,499-1,979 * -1,864 * -1,533 -1,152

Lebenserwartung mit 65 Jahren -0,989 -0,854 -1,331(-2,557) ** (-1,993) * (-1,987) *

Ausgabenquotient# -0,076 -0,069 -0,072 -0,06(-2,586) ** (-2,241) ** (-2,375) ** (-0,927)

Relativer Gesundheitspreisindex (BIP) 0,146 0,158-0,758 -0,835

Anzahl der Gestorbenen pro 100.000 0,487-2,07 **

Anteil der Pflichtschulabsolventen der 25-60-jährigen 0,503-1,948 *

Adjusted R-squared 0,689 0,684 0,687 0,604Durbin-Watson Statistik 1,415 1,452 1,485 1,842N 33 33 33 19

# Gesamte Gesundheitsausgaben/Bruttoinlandsprodukt** p=0,05, *p=0,10

1960-2000 1980-2000Modell 1 Modell 2 Modell 3 Modell 4

IHS HealthEcon 2002