Health expenditure in the EU: Comparability is ailing Focus: Forecast of health ... · 2017-03-27 · Health expenditure in the EU: Comparability is ailing In an international comparison

I/Spring 2003

HEALTH SYSTEM WATCH Supplement of the journal Soziale Sicherheit by the Institute for Advanced Studies/Institut für Höhere

Studien IHS HealthEcon

Edited by the Hauptverband der österreichischen Sozialversicherungsträger (Federation of Austrian Social

Security Institutions)

Health expenditure in the EU: Comparability is ailing

Focus: Forecast of health expenditure in Austria

Maria M. Hofmarcher, Gerald Röhrling*

Summary According to official statistics, health expenditure in Austria amounted to 7.3 percent of GDP in 2001. This ratio corresponds to that of the United Kingdom or the Czech Republic. Nevertheless, in a classification established by the OECD Austria belongs to a group of countries whose health expenditures are far from competitive on the international level. According to our estimates public health expenditure in Austria is underestimated to at best four billion Euro, and its calculation is not yet based on the calculation standards suggested by the OECD. Private per-capita spending on health care in Austria grows at a considerably faster rate than GDP. Private health expenditure is characterised by a serious lack of definition, too. Depending on which deliniation is applied, user charges account for four to 18 percent of total health expenditure.

According to a forecast model developed by IHS HeathEcon Austria’s per-capita health expenditure at 1995 prices will almost have doubled by 2020. The increase is considerably lower (+64 percent) when taking into account the officially published health expenditure. For health care policy it is highly important to know the actual financing flow, not only with regard to the level of health care spending and the development of the financial burden, but also in the context of future growth dynamics. The official statistics in the field of health care spending comply with the current EU methods. It has to be pointed out, yet, that health expenditure in Austria is higher than officially indicated, implying a much higher pace of growth in the future.

*With special thanks to Monika Riedel and Andrea Weber for their helpful comments and Martina Szucsich for translation.

HEALTH SYSTEM WATCH I/2003 2

Health expenditure in the EU: Comparability is ailing

In an international comparison Austria is below the weighted EU average regarding both per-

capita health expenditure and GDP ratio (cf. tables A2 and A3). Total health expenditure in

terms of the NA concept (ESA 95) amounted to 15.6 billion Euro in 2001. In 2000 it was 15.3

billion Euro, which is approximately 1.1 billion Euro less than the value published last year (cf.

HSW I/2002). A subsequent revision of the calculation of total health expenditure revealed a

GDP share of 7.3 percent in 2001 (cf. table 2).

In its May-2000 edition of “A System of Health Accounts“ (SHA) the OECD published

guidelines to classifying health expenditure in compliance with international standards. Since

not all member states obey the methodologies, a EU-wide comparison of health expenditures

can only take place to a certain degree (cf. table 1).

Table 1: Comparability of health expenditure

Group 1:

High level of

comparability

EU/accession countries:

Denmark, France*, Germany*,

Hungary, Netherlands*, United

Kingdom

Other OECD countries:

Australia, Canada, Japan, Korea,

Switzerland*, United States

Calculation of health expenditure strictly

follows the OECD/SHA delimitation

Differences in definition in two areas of total

health expenditure:

Expenditure on hospital care vs. expenditure

on pharmaceuticals

Group 2:

Limited

comparability


Czech Republic, Finland, Poland,

Spain, Turkey


Mexico, New Zealand

Calculation of health expenditure does not

entirely follow the OECD/SHA definition

Group 3:

Low level of

comparability


Austria*, Greece, Ireland, Italy,

Luxembourg*, Portugal, Slovakia,

Sweden


Island, Norway

Calculation of health expenditure is based on

national accounts that are hardly appropriate

for estimating health care expenditure and

cause problems in an international comparison

Group 4:

Low level of

comparability


Belgium*

Other OECD countries: -

Calculation of health expenditure is carried out

by the OECD Secretariat on the basis of

national accounts and other sources

* Social Health Insurance countries

Source: OECD Health Data 2002.


Austria’s proportions of health care spending are flexible...

Not only the GDP shares of health expenditure published by Statistik Austria are lower than

those published last year, but also between 1997 and 2001 they decline at a rate of 0.3

percentage points . These disparities are mainly due to the “treatment“ of the tax share in total

health care expenditure which results from the conventions of the method applied by Statistik

Austria (NA Actual Final Consumption (ESA 95, SNA 93)). The method of calculating the official

health care expenditure focuses on final consumption without revealing the way of financing

health care. The data sources available can however be combined in a way so as to give

information on the financing, too. The percentage of health care expenditure financed by taxes

amounted to approximately 25 percent in 2000 and was mainly spent on hospital care1.

Figure 1: Financing of health care in Austria, in Social Health Insurance countries and

in the EU, as percent of total health care spending in 2000

Social health insurance countries: Austria, Belgium, Germany, France, Israel, Luxembourg, Netherlands,

Switzerland

Source: Statistik Austria, HVSV, OECD Health Data 2002, IHS HealthEcon calculations 2003.

Other EU countries do not entirely take into account the public share of hospital financing as

defined by the EU-NA actual final consumption, either. Nevertheless it has to be underlined that

in Austria the share of health expenditure and hospital care financed by taxes is high in

comparison to other Social Health Insurance countries such as Germany, France,

1 According to the calculations by the Court of Audit, in 2001 the financial burden was distributed among social health insurance institutions including health insurance institutions for government employees (50.7%), local authorities (27.9%) and private households (21.4 %) in 2001. Report issued by the Court of Audit, state 2002/4, Activity report by the Court of Audit for 2001, December 23, 2002.

46.2

25.3

25.5

3.0

57.4

19.4

11.6

6.4

29.0

45.9

17.8

4.7

0%

20%

40%

60%

80%

100%

Austria Social-health-

insurance(SHI)

countries

EU-Average

Private Health Insurance

Private expenditure + co-paymentsTaxes

Social health insurance


Luxembourg, Belgium and the Netherlands (cf. figure 1). This is why neglecting this major

financing share in total expenditure on health is a much greater problem in Austria.

Table 2: Health expenditure in Austria, according to Statistik Austria

1997 1998 1999 2000 2001 1997/2001 Average

annual In Mio. EURO

growth rate

Total health expenditure 13.839 14.644 15.353 15.344 15.561 3,0 Consumption spending, general government 9.047 9.544 9.896 9.764 9.887 2,2 Consumption spending of private households, health 3.815 4.045 4.310 4.483 4.659 5,1 Consumption spending, private NGOs 10 11 12 12 12 4,7 Investments 967 1.045 1.135 1.085 1.002 0,9 Public health expenditure 9.744 10.319 10.700 10.517 10.476 1,8 Public spending , consolidated 98,717 103,369 106,701 108,658 110,840 2.9 Social payments in kind - nominal 9,008 9,469 9,799 10,072 10,273 3.3 Social payments in kind – at 1995 prices5) 8,629 8,775 8,804 8,867 8,840 0.6

Gross Domestic Product (GDP) 182,486 190,628 197,154 207,037 211,857 3.8

Per capita, at 1995 prices in EURO Total health expenditure1) 1,721 1,809 1,870 1,858 1,872 2.1 % change 5.1 3.3 -0.6 0.8

Consumption spending by private households, health2) 480 507 533 553 574 4.5 % change 5.5 5.2 3.8 3.7

Public health care spendings3) 1,170 1,227 1,263 1,225 1,204 0.7 % change 4.9 2.9 -3.0 -1.7

Social payments in kind3) 1,081 1,126 1,157 1,173 1,180 2.2 % change 4.1 2.7 1.4 0.6

Social payments in kind5) 1,069 1,086 1.088 1.093 1.087 0.4 % change 1.6 0,2 0,5 -0,5

Total public expenditure4) 12,278 12,771 12,995 13,156 13,336 2.1 % change 4.0 1.8 1.2 1.4

Gross Domestic Product (GDP) 4) 22,121 22,956 23,540 24,383 24,439 2.5 % change 3.8 2.5 3.6 0.2

As percent of GDP Total health expenditure 7.6 7.7 7.8 7.4 7.3 Consumption spending by private households, health 2.1 2.1 2.2 2.2 2.2 Public health expenditure 5.3 5.4 5.4 5.1 4.9 Total public expenditure 54.1 54.2 54.1 52.5 52.3 Social payments in kind 4.9 5.0 5.0 4.9 4.8 Public health expenditure As percent of total health expenditure 70.4 70.5 69.7 68.5 67.3 As percent of total public spending 9.9 10.0 10.0 9.7 9.5

1)Price index total health care spending 2)Price index for private consumption, health 3)Price index for public consumption, health 4)Total economic price index (GDP deflator) 5) Collectively agreed wage rate index – Social health insurance institutions (“Tariflohnindex - Sozialversicherungsträger”)

Source: Statistik Austria, IHS HealthEcon calculations 2003.


...because hospitals have been classified as market producers since 1997…

Public health expenditure consists of public consumption spending, public investments and

current transfers. In 2001 it amounted to approximately 10.5 billion Euro or 4.9 percent of GDP.

Public expenditures at 1995’s prices have increased at an annual average of 0.7 percent since

1997 (cf. table 2). Since 1997 hospitals have been defined as market producers. Consequently,

not more than 50 percent of the fund hospitals‘ costs are entered into the health care

expenditure calculation. Until 2000 this loss of information was compensated for by public

health care spending as defined by the expenditure concept (COFOG), which accounted for the

entire costs.

...and Maastricht has claimed its tribute since 1997.

Public expenditure classified in terms of public tasks measure the government´s expenditure

on various fields such as the health care sector. In 2001 public expenditure on health amounted

to 12.3 billion Euro. They included public health expenditure (85 percent) and other public

expenditures in the field of health care (advance payments, returns from non-market producers

etc.). According to COFOG calculation public expenditure on health care amounted to

approximately 15.5 billion Euro in 1999 and 2000, which is clearly above 2001‘s value. The

rupture in 2001 can be explained by the shifting of limited liability companies

(“Krankenhausbetriebsgesellschaften”) and hospitals in the federal states without limited

liability companies into private sector accounts where they are now classified as “non-financial

corporations“2. As a consequence, the expenditure (costs) of public hospitals have been

included into public health care spending only up to the amount of payments effected via case

rate (“LKF”) scores (4.1 billion Euro in 2001, or 50 percent of total public inpatient care costs3)

since 2001. The hiving off is at present relieving the federal states’ budgets by about 4 billion

Euros.

Social payments in kind: the “new“ public health expenditure

Within total public expenditure, social payments in kind largely correspond to public

consumption expenditure on health care according to NA. In 2001 they amounted to 10.3

billion Euro (cf. table 2). Public health care expenditure and necessarily also social payments

in kind include the social health insurance’s entire expenditure on medical, dental and

paramedical services, pharmaceuticals and therapeutic products, including all user charges

and cost sharing. Whereas (public) health care spending according to ESA 95 and public

expenditure according to public tasks are only available for the period between 1995 and 2001,

social payments in kind have been calculated back to 1976.

Since hospital care belonged to advance payments before 1997, the time series shows a

rupture at this point. From this point of time on the nominal social payments in kind

approximate public health expenditure. In 2001 social payments in kind accounted for 9.3

percent of total public expenditure. Approximately 95 percent of these payments were spent on

2 Dannerbauer, H.: Gesundheitsausgaben 1995-2001, Statistische Nachrichten 1/2003, Statistik Austria Vienna. 3 Federal report of the Court of Audit, 2002/4, Activity report of Court of Audit for the year 2001, December 23, 2002


health care, the rest on initiatives in the field of education such as free school books and free

public transport for students. Sum total, 11 percent of total public expenditure is spent on

health care. Per-capita social payments in kind at 1995‘s prices have increased at an annual

average rate of 0.4 percent since 1997 on, reaching 1,087 Euro in 2001 (cf. table 2).

Figure 2: Development of (public) health expenditure and social payments in kind, in

mio. Euro, 1990-2001 nominal value

Source: Statistik Austria, IHS HealthEcon 2003.

Private health expenditure is growing dynamically...

The private households‘ consumption expenses, that is to say expenses for goods and

services that are not covered by obligatory insurance, have considerably increased. The growth

dynamics of expenses at 1995‘s prices clearly shows that this sector has increased at an

annual average of 4.5 percent since 1997, which is considerably faster than the GDP (+2.5

percent). The private households‘ consumption expenditures on health care are differentiated

according to COICOP (Classification of Individual Consumption by Purpose). One quarter of the

expenditure each is spent on inpatient, physician and dental care. The remaining quarter

consists of expenses on pharmaceutical, therapeutical and other medical products, services

provided by health professionals other than physicians and inpatient thermal bath or spas.

Expenditure on services provided by health professionals other than physicians (medical

laboratories, home care, psychotherapists etc.) have experienced the sharpest increase since

1995.

0

2.000

4.000

6.000

8.000

10.000

12.000

14.000

16.000

18.000

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Social payments in kind

Public health expenditure

Total health expenditure


Table 3: Consumption expenditure of private households according to COICOP

Medical products, appliances

and equipment

? Pharmaceutical products

? Other medical products

? Therapeutic appliances and equipment: from 1996 on

estimated on the basis of payments for and prescriptions

of therapeutic products

Out-patient services ? Medical and dental services: physicians‘ turnover minus

social security payments for medical, dental and

orthodontic specialists services and dispensing chemists

plus VAT

? Paramedical services: medical analysis laboratories,

home care, psychotherapists etc.

Hospital services

? Hospitals: private consumption by hospitals =

production value of hospitals minus social health

insurances‘ payments to the Hospital Funds, consumption

spending by private non-profit hospitals, consumption

spending by public hospitals plus VAT

? out-patient thermal bath or spas (part of the output)

Insurance services relating to

health

? Actual services rendered in the private health and

accident insurance

Source: Statistik Austria, IHS HealthEcon 2003.

... and does not comprise user charges

Prescription, expenses per health insurance voucher, outpatient fees and other cost sharing

are called the private households‘ individual financing contributions. They are not included in

the private consumption expenses on health. The user charges are entered as the private

households‘ transfers to the state. In particular, in the framework of ESA they are included into

the payments in kind rendered by social health insurance and provided by market producers. In

Austria, user charges can largely be classified into two groups. On the one hand, they mean a

co-payment in terms of percent of contribution (coinsurance), with patients paying a fixed

percentage of the costs by themselves. On the other hand, user fees are settled as charge per

service.


What are user charges...

User charges appear in manifold forms. As defined, they are part of a spectrum of services (in

kind) that are entirely paid by insurance institutions and of services (in kind) that are

exclusively paid privately. In the literature a distinction is made between direct and indirect

cost-sharing4.

Direct cost sharing (user charges) largely includes co-payments and user charges in terms of

percentage or contribution in the form of charge per service. Indirect cost sharing mainly

comprises expenses on services and/or products that are not (yet) included into the health

insurances‘ benefit packages or which require private payment. Examples of indirect cost

sharing in Austria in the private sector employees’ segment (80 percent of all insured

individuals) are the private households‘ expenses for dentures.

Next to the percentage-related user charges for self-employed persons and civil servants direct

co-payments in Austria mostly include fix charges (prescription and health insurance voucher

fees etc.) which are a special form of deductibles. The lower the charge as compared to the

income, the less steering effect may be expected. By now the main function of existing user

charges in Austria has consisted in relieving the health insurance budget.

User charges serve as financing source not only in Austria. It has to be mentioned, yet, that in

this very role they do not increase economic efficiency, for they just bring about a shift in the

financial burden.

User charges are most frequently applied in the field of pharmaceuticals. All EU countries have

different regulations5. In the EU only in Germany, Italy, the Netherlands, Spain and the United

Kingdom, patients have to pay user charges when consulting a physician. In 11 of the 15

member states consulting a specialist requires the payment of user charges. For dental

services all countries provide for cost sharing. In some countries dental services are not

classified as public task6. In spite of a high proliferation of user charges, all countries have

provided for exceptions, such as age limits, minimum incomes and chronic diseases.

...and what is their purpose?

The basic purpose of direct user charges is to steer demand of health services. One of the

factors7 suggesting the necessity of influencing the demand is “moral hazard“, which refers to

service utilization in generous insurance plans that exceeds marginal medical utility. This is

why cost sharing are expected to increase economic efficiency, since they make patients

4 Conceptual differences cf.: Robinson, R.; User charges for health care in Mossialos, E., et.al: Funding health care: Options for Europe, European Observatory on Health Care Systems. Open University Press Buckingham, Philadelphia 2002. 5 Rosian I., C. Habl, S. Vogler, Arzneimittel. Steuerung der Märkte in der EU. ÖBIG, Vienna, 2001 6 Cf. Robinson, R (2002) op.cit 7 Detailed discussion cf. Riedel, M.: Selbstbeteiligungen in Krankenversicherungen - theoretische Wirkungen und internationale Erfahrungen. Wirtschaftspolitische Blätter 1/1998, 95-103


reduce the consumption of services to a) necessary services and/or to b) a necessary

frequency of consulting a physician. The conditions a) and b) are fulfilled if 8:

• consumption habits change with changing prices

• private insurance does not step into the gap to insulate patients against potential out-

of-pocket costs

• health care providers do not over-compensate for possible decreases in patient-

initiated utilizations and

• if patients pay the fees.

When assessing the effect of user charges economically, not only efficiency, but also fairness

and administrative aspects of levying have to be considered. An evaluation of cost sharing must

therefore include effects on the efficiency as well as distributional aspects, both in terms of

affordability for the different income groups and in terms of utilization. In addition to that, public

acceptance has to be borne in mind.

The RAND experiment9 has up to now been the most important source when it comes to

assessing the efficiency of cost sharing. The most significant results can be found in Manning

et al. and in Brook et al 10:

1) In the group without cost sharing the consumption of services was 23 percent higher

than in the group with 25 percent user charge and 46 percent higher than in the group

with 95 percent user charge.

2) A 10-percent price increase led to a 2-percent decrease of service consumption both

in outpatient and inpatient settings (price elasticity of demand of –0.2).

3) Free inpatient care was not substituted for cost-shared outpatient care.

4) Cost sharing not only led to a decline in services that were not necessary from a

medical point of view, but also to a reduction of necessary services.

5) Adults of the group without cost sharing were in a better state of health in terms of

high-blood-pressure-related diseases, impaired sight and the risk of dying for those at

elevated risk. Yet, full insurance did not lead to a reduction of overweight or levels of

cholesterol.

8 Stoddart, G.L:, ML Barer, RG Evans: User charges, Snares and Delusions: Another look at the literature, Health Policy Research Unit, Center of Health Services and Policy Research, University of British Columbia, Canada, December 1993. 9 In the experiment starting in 1974 5,800 persons were attributed to one of 14 insurance institutions at random and insured for a period of 3 to 5 years. Co-payments were scaled (0, 25, 95 percent) and upper limits of co-payment (5, 10, 15 percent of the family’s income up to an annual $ 1,000 were levied. The test subjects belonged to the age group of up to 62-year-olds. Persons with an annual income of more than $ 25,000 and disabled persons insured with the federal programme Medicaid were not included. 10 Manning, W.G., J.P. Newhouse, N. Duan, E.B. Keeler, A.Leibowitz, S. Marquis (1987): Health Insurance and the Demand for Medical Care: Evidence from a Randomized Experiment, American Economic Review, 77:251-277. Brook R.H., J.E. Ware Jr., W.H. Rogers, et al. (1983): Does Free Care Improve Adults´ Health? New England Journal of Medicine, 309:1426-1434


6) Those belonging to the lower income groups profit most from cost-sharing free

insurance. A clear reduction of severe symptoms of illness could be observed here.

The amount of user charges in Austria can only be estimated...

The actual amount of direct cost sharing (user charges) can only be reckoned. In Austria they

ranged from four to 18 percent of total health expenditure in 2001, depending on what

expenditure elements were taken into account (cf. figure 3).

Figure 3: Co-payments in Austria, in percent of total health expenditure

Sources: HVSV, Statistik Austria, IHS HealthEcon calculations 2003

At the lower bound, the distinction between user charges and private payments according to

IHS HealthEcon considers expenditures on non-contract physicians not as direct user charges

but as private payments. This is insofar questionable as the concept of these expenses

corresponds to direct co-payments if freedom of choice of medical providers is contained as a

valid health policy goal in Austria. Thus, including private household expenses on non-contract

physicians would increase the share of user charges in the total health expenditure to

approximately nine percent. What is also unclear is the distinction between the private

households‘ expenditure on in-patient care. This part ranks second after family physician and

dentist care in terms of expenses and basically consists in the co-payments by self-employed

persons and civil servants. The share of user charges in total health expenditure amounts to 14

percent when adding up the private households‘ expenses on physicians and hospitals. Taking

into account the considerable user charges for therapeutic appliances, too, user charges

further increase to approximately 3.6 billion Euro. This corresponds to a share in the total

health expenditure of approximately 18 percent, the highest value among social health

insurance countries in the EU (cf. figures 3 and 4).

2,5

7,2

12,6

16,5

3,8

8,8

14,1

18,1

0

5

10

15

20

co-paymentsminium

co-payments incl.outpat. health

services

co-payments incl.outpat. and inpat.

health services

co-payments incl.outpat. and inpat.

health servicesresp. medical aud

therapeuticalproducts

19972001


…and they cannot be clearly distinguished from private payments…

According to the OECD’s definition “out-of-pocket payments” comprise direct (user charge)

and indirect (private payments) cost sharing by private households, no matter whether the

patient has contacted the health system after a referral by a physician or out of his/her own

initiative. The Austrian example already shows that this definition would lead to payments

amounting to 23.9 percent (direct and indirect cost sharing) of the entire health care spending.

This means that the current definition undervalues the share of private payments as presented

by the OECD. According to OECD data, out-of-pocket payments in Austria accounted for 18.6

percent of the entire health care expenditure in 2000 (cf. figure 4). This roughly corresponds to

the upper boundary of direct co-payments (cf. figure 3), but is unlikely to include indirect private

payments.

…this is most probably not only the case in Austria.

According to the OECD data Austria registers the second largest increase in “out-of-pocket

payments” after Sweden: Since 1995 the share of “out-of-pocket payments” in the entire health

expenditure has risen to 4.0 percentage points, and in 2000 it was clearly above the EU

average (14.9 percent). In the social health insurance countries of the EU (Belgium, Germany,

France, Luxembourg and the Netherlands) the average share of user charges amounts to 10.9

percent of total expenditure on health. In this comparison Austria turns out to show the highest

percentage of user charges (cf. figure 4). Among the countries with particularly low shares of

user charges are Germany, France and the Netherlands, all of which follow OECD calculation

standards (cf. table 1) and show relatively high GDP shares spent on health (cf. table A3).

In the accession countries except from Slovenia, Slovakia and the Czech Republic, “out-of-

pocket payments” as percent of total expenditure on health exceeded the weighted EU average

in 2000 (cf. figure 5). The largest increase compared to 1995 was registered in the Baltic

countries Lithuania and Estonia. Cyprus, Latvia and Romania topped the ranking in 2000, with

shares of over 35 percent of the total health care expenditure.


Figure 4: “Out of pocket payments“ in percent of total health expenditure, EU

Source: The World Health Report 2002, IHS HealthEcon 2003.

Figure 5: “Out of pocket payments“ in percent of total health expenditure, accession

countries

Source: The World Health Report 2002, IHS HealthEcon 2003.

0

5

10

15

20

25

30

35

40

45

50

Gre

ece

Spa

in

Italy

Sw

eden

Finl

and

Por

tuga

l

Aus

tria

Den

mar

k

Bel

gium

Irela

nd

Ger

man

y

Uni

ted

Kin

gdom

Fra

nce

Net

herla

nds

Luxe

mbo

urg

1995

2000

EU15-2000EU-SHI6-2000

0

5

10

15

20

25

30

35

40

45

50

Cyp

rus

Latv

ia

Rom

ania

Mal

ta

Tur

ky

Lith

uani

a

Pol

and

Bul

garia

Hun

gary

Est

onia

Slo

veni

a

Slo

vaki

a

Cze

ch R

epub

lic

19952000

EU15 2000AC13 2000


Focus: Forecast of health expenditure in Austria

This chapter aims at identifying determinants of health care expenditure in the past and, based

on the model thereby created, to estimate the future development of health care expenditure in

Austria. The forecast depicts two scenarios. The one is based on the officially published health

care expenditure, the other one on our estimations of the levels of health care spending

between 1997 and 2000.

International evidence

The interest in statistically investigating the development of health care spending in more detail

dates back to a study carried out in 1977, in which it was found that health care expenditure in

developed countries increase faster (more elastically) than the Gross Domestic Product11. The

study gave rise to the assumption that health is a luxury good. A series of papers followed,

which investigated international data to identify several factors of influence: changes in

incomes, price effects, the extension of persons entitled to social health insurance as well as

the widening of the range of health care services. Yet and in most cases, these comparisons

have been attributing only little importance to the institutional design of the health care system

and the age structure of persons entitled12.

When using time series (panel data), the specifications of the second generation of models

focused on identifying the influences on health care expenditure, taking into account time-

independent effects13. Gerdtham found out that country and time specific effects exert an

influence on health care expenditure14. In further papers institutional factors such as physician

density or the proportion spent on inpatient care have been identified as significant factor on

the level of health care expenditure15. In an econometric examination of growth rates of the

OECD countries‘ health care expenditure between 1960 and 1990, no significant effect could

be observed for institutional factors .16.. What was identified as significant factors were only the

original level of health care expenditure and economic growth. The investigations of the second

generation of model specifications all support the assumption that health is a luxury good,

since income elasticity was always estimated to approximately the value one.

In the late 1990s, the specifications were expanded by further econometric procedures that

aimed at eliminating possible deterministic or stochastic trends from the variables. The results

11 Newhouse, J.P. (1977), Medical care expenditure: a cross-national survey, Journal of Human Resources 12:115-125. 12 Gerdtham, Ulf, Jönsson, Bengt (1991), Price and Quantity in International Comparisons of Health Care Expenditure. Applied Economics, vol 23, 1519-1528. Gerdtham, Ulf, Sögaard, Jes, Jönsson, Bengt, Andersson, Fredrik (1992), A pooled cross-section analysis of the health care expenditures of the OECD countries. Zweifel, Frech (eds.): Health Economics Worldwide. Kluwer. 13 Greene, W (1993), Econometric Analysis, 2nd Edition, Prentice-Hall Inc, Englewoods Cliffs, NJ. 14 Gerdtham, Ulf, Sögaard, Jes, Jönsson, Bengt, Andersson, Fredrik (1992), Econometric analyses of health expenditure: a cross sectional study of the OECD countries, Journal of Health Economics 11:63-84. 15 Gerdtham, Ulf, Jönsson, Bengt (2000), International Comparison of Health Expenditure: Theory, Data and Econometric Analysis, Handbook of Health Economics, Vol 1, Ed.: A.J. Culyer and J.P. Newhouse, Elsevier Science B.V. 16 Barros, P.P. (1998), The black box of health care expenditure growth determinants, Health Economics 7:741-803.


are partly contradictory. Some of the authors point out that the relation between Gross

Domestic Product and health care expenditure is not correctly depicted in the cross section

measurements over time 17. On the other hand there is evidence suggesting that this

inappropriateness is less serious than assumed18.

There are fewer papers on possible factors determining the health care expenses that take only

data in individual countries into account. In a regression model, Breyer, Ulrich (2000)19 explain

the development of the average per-capita spending per insured by factors like age structure,

relative prices, the number of deaths and technical progress. For Canada, investigations have

revealed that only a negligible amount of the increasing expenses on medical care are caused

by an increase in the share of elderly people in the entire population20. A slightly different time

series analysis of US data for the period between 1960 and 1997 tries to identify factors

determining the increase in life expectancy. For this purpose a health production function has

been estimated, which finds that both technical progress, measured by the number of new

chemical entities, and public health care expenditure have a significant effect on the increase

of life expectancy21.

Estimation method and data

Our econometric estimation is based on a time series model. A time series model describes

the behaviour of variables with respect to their past values. It is a regression to delayed values

of variables with an additional disturbance term. The estimation has been implemented in

Eviews and can be described by the following equation:

∑=

++=k

jjjjk xxxy

11 ),....( εβα

As frequently found in literature, we have chosen a logarithmic specification of the regression

equation in order to be able to depict also non-linear relations:

j

k

jjjk xxxy εβα ++= ∑

=11 ln),....(ln

The growth rate of total per-capita health expenditure at 1995‘s prices is the endogenous

variable (y). The selection of exogenous variables has been optimised by several diagnostic

and operational procedures in order to guarantee for the estimation’s quality. The model

generates elacticities by using logarithmic specification, so that the growth rate of the

17 Gerdtham, Ulf, Jönsson, Bengt (2000), op.cit. 18 McCoskey, S.K., T.M. Seldon (1998), Health Expenditure and GDP: Panel data unit root test results, Journal of Health Economics 17:369-376. 19 Breyer, Friedrich, Volker Ulrich (2000), Gesundheitsausgaben, Alter und medizinischer Fortschritt: Eine Regressionsanalyse. Jahrbücher für Nationalökonomie und Statistik, 220/1, 1-17. 20 Barer, M.L., R.G. Evans, C. Hertzman (1995), Avalanche or Glacier? Health care and the demographic rhethoric, Canadian Journal on Ageing 14:2, 193-224 quoted after Rosenberg, Mark W. (2000), The Effects of Population Ageing on the Canadian Health Care System, SEDAP Research Paper No 14, February 2000. 21 Lichtenberg, F. (2002), Sources of U.S. Longevity Increase 1960-1997, National Bureau of Economic Research, Working Paper 8755.


dependent variables, i.e. total health expenditure, are associated with the growth rates of the

independent variable.

The period chosen was 1961 to 2000, since the sources used did not provide for any older data

on health spending. The time series obtained showed 35 to 41 complete data points according

to the availability of explanatory variables.

Table 4: Variables of the regression model

Average Medium Maximum Minimum Number of observations

Total per-capita health care spending at 1995‘s prices, in EURO, (1997-2000 according to Statistik Austria)

1.065 1.103 1.896 300 41

Total per-capita health care spending at 1995‘s prices, in EURO, (1997-2000 according to IHS HealthEcon estimates)

1.101 1.126 2.251 328 41

Share of persons aged over 65 in the entire population

14.4 14.7 15.5 12.2 41

Share of radiologists per 100,000 5.6 4.8 9.0 3.4 35

Number of actual acute-care beds per 100,000

895.7 946.3 1.003.0 694.4 40

Life expectancy at age 65

15.0 14.6 17.6 13.2 41

Per-capita Gross Domestic Product at 1995‘s prices, in EURO

15.607 16.340 24.042 7.025 41

Source: OECD Health Data, Statistik Austria, BMSG, IHS HealthEcon calculations 2003.

Table 4 gives an overview of the average, median, minimum and maximum of the dependent

and independent variables used. The time series of health expenditure data showed some

breaks that are due to some changes in the calculation methods. We smoothed the time

series (three-years‘ average of health care expenditure) in order not to endanger the quality of

the estimation by technically created artefacts.

Hypotheses The estimation of our model was guided by the following hypotheses: Likely to represent

determinants of cost-increasing technical progress, the share of the population aged over 65

and the number of radiologists per 100,000 inhabitants was employed. This means that we

expect a positive correlation of coefficients with health care spending: if the number of elderly

persons or the ratio of radiologists increases, health care expenditure goes up, too. The

assumption that the increasing percentage of elderly persons reflects the cost-increasing

medical progress has the following reasoning: life-prolonging medical interventions are

performed later and later on in the life cycle and the mere increase in the number of elderly

persons leads to an increase in health care expenditure.


The number of acute-care beds per 100,000 and the life expectancy of 65-year-olds, in turn,

represent cost-reducing technical progress. As for life expectancy we expect a negative

coefficient: if life expectancy goes up, health expenditure goes down. There seems to be no

reason for rejecting this hypothesis since there is sufficient empirical evidence available for

Austria showing that a compression of morbidity is accompanied by mounting life

expectancy22. As for the density of acute-care beds and health expenditure we expect a

positive correlation, since length of stay is continuously decreasing. Being a frequently used

regulatory measure, acute-care bed density is expected to be positively associated with health

expenditure: With increasing density of acute-care beds, which in this context is used as a

proxy for supplier induced demand, health expenditure will increase.

Most model estimations suggest a positive correlation between GDP (as an approximation of

non-available data on personal income) and health care expenditure. Upon adding further

explanatory variables, the significant effect of income however disappears. Our time series

model indirectly considers the total economic income, since we define the quotient of health

care expenditure and GDP as independent variable. It is particularly important to include this

quotient as correction factor into the estimation equation since the amount of the growth rates

of health care expenditure depends on the level of health care expenditure in the past.

Therefore. This relation has been referred to in pertaining literature23. As for the variable

“expenditure quotient”, which keeps the ratio between health expenditure and GDP constant in

the course of time, we reckon with a negative coefficient: if the expenditure ratio increases,

growth rates of health expenditure decreases.

Determinants of health expenditure

The results of the estimation are summarized in table 524. All coefficients show the expected

sign and are significantly associated with health care spending. The coefficient of determination

(Adjusted R2) measures the quality of the estimation. In our model, the independent variables

used explain more than 60 percent of the variability of health care expenditure. The Durbin-

Watson statistics measures autocorrelations in the unexplained part of the regression

(residuals). Autocorrelations occur particularly frequently in time series models. The ideal

statistics would mean a value of 2. In our specification this test statistics approximately

amounts to 1.4. For this reason we performed a series of further tests (Dicky Fuller Test,

cointegration test), but we could finally reject the hypothesis that deterministic or stochastic

trends in the time series distort the estimation results.

22 Cf. Doblhammer, J. Kytir, Compression or expansion of morbidity? Trends in healthy-life expectancy in the elderly Austrian population between 1978 and 1998. Social Science and Medicine 52, 2001, 385-391. 23 Barros (1998), op.cit. 24 As for the determinants presented here, both the crude death rate and the share of people with compulsory education contributed a positive, significant explanation of the growth of health care spending in several model estimations. Taking into account relative prices did not yield any significant explanation. The estimations relate both to the total and the public health care expenditure. Cf. Riedel M., M. M. Hofmarcher, R. Buchegger, J. Brunner: Nachfragemodell Gesundheitswesen, IHS Projektbericht, Vienna, July 2002.


Table 5: Result of the time series analysis: Parameter estimations and t-values of total

health expenditure

Constant -0.219 ** -2.452

Share of over 65-year-olds in the entire population 1.776 ** 3.995

Number of radiologists per 100, 000 0.648 ** 3.052

Number of acute-care beds available, per 100, 000 0.589 * 1.812

Life expectancy at the age of 65 -0.990 ** -2.370

Expenditure quotient: health care expenditure/GDP -0.091 ** -2.836

Adjusted R-squared 0.660 Durbin-Watson Statistics 1.383 N 33

** p=0.05, *p=0.10

Source: IHS HealthEcon calculations 2003.

Results of the estimations

The group of persons aged 65 and more shows a significantly positive correlation with health

care expenditure. This is one of the most robust results of our model estimation. Attempts to

take another age group, as e.g. that of over-80-year-olds, to explain health care expenditure

growth, have not proved a quarter as firm. The results suggested that a one-percent increase in

the population share of persons over 65 makes – ceteris paribus - the average per-capita health

care expenditure rise 1.8 percent. In other words, with an increase in the share of over-65-year-

olds from 15.5 to 16.5 percent health care expenditure goes up slightly more than 10 percent.

The literature pertaining to health care economics frequently refers to the following effect: A

large supply of services can increase the amount of services actually consumed. As a

consequence, expenses go up and sometimes even exceed a level that is optimal (supplier-

induced demand). The question whether supplier-induced demand can be found in Austria or

not cannot be answered in the framework of this investigation. The relation between supply or

availability of medical services and health care spending seems in any case worth paying

attention to.

Attempts involving several variables of supply have led to the conclusion that radiologists and

the density of acute-care beds render the best (most firm) results as for supply-related factors.

A one-percent increase in the number of radiologists increases – ceteris paribus - the average

growth rates of per-capita health care expenditure 0.6 percent, according to the model

specification. Alternative attempts, e.g. regarding the number of contract physicians or

employed physicians, led to less significant results.


Taking into account possible cost driving effects of the hospital sector seems particularly

important in the context of Austria. It has repeatedly been observed that the Austrian hospital

sector is characterised by over- rather than by under-capacities25. The estimations show a

significantly positive correlation between health care expenditure and density of acute-care

beds. Elasticity amounts to 0.6, depending on the specification chosen. The result indicates

that increasing bed density is significantly associated with increasing health care expenses.

It is not quite clear in what way increasing life expectancy influences the growth dynamics of

health care expenditure. The pressure on the health care budget depends on the question

whether rising life expectancy brings about an expansion or a compression of morbidity.

According to our results the probability that an increase in the life expectancy of people aged

65 increases health care expenditure amounts to only five percent. In other words the negative

coefficient indicates a probability of 95 percent that a one-percent increase of life expectancy

results in a one-percent reduction of health care expenditure.

The development of health care expenditure is tightly linked to the overall economic

development.. In the majority of the developed countries a high level of health expenditure goes

hand in hand with a slower growth of health care expenditure26. In our estimations, the quotient

of health care expenditure and Gross Domestic Product is significantly associated with the

growth rates of health care spending. If the health care expenditure ratio increases from 8.0 to

9.0 percent, the growth rate of average per-capita health care spending decreases

approximately 0.9 percent.

Forecasting health expenditure

The forecast of health care expenditure relates to the results of the estimations depicted in

table 5 and covers the period of 2000 to 2020. The forecast is based on the time series of

health care expenditure since 1960, and for the years 1997 to 2000 on the health care

expenditure as published by Statistik Austria in December 2002 (scenario “underestimated”) on

the one hand. On the other hand, the predictions relate to our estimations of health care

expenditure of the years 1997–2000, since the officially published health care expenses have

been underestimated by approximately four billion Euro since 1997 due to calculation

provisions (cf. standard part of the present edition). We call this outlook as scenario “probable”.

25 Hofmarcher, Riedel: 2001: Resource Consumption in the EU: Innovation occurs at a price. Focus: Regulating the Drug Market Makes it Safer for All, HSW II/2001, www.ihs.ac.at 26 Barros, 1998 op.cit.


The forecast is based on the following assumptions:

Scenario: “underestimated“

(health care spending 1960 to 2000 according

to Statistik Austria 2002)

Scenario: “probable“

(health care spending 1960 to 1997 according

to Statistik Austria and 1997 to 2000

according to IHS HealthEcon estimates)

• The share of persons aged over 65 in the entire population is derived from the main

variant of the population forecast for 2000 and increases from 15.5 percent to 20.3

percent in 2020.

• The increase in the density of radiologist taking place between 2000 and 2020

corresponds to the annual rate of increase observed between 1990 and 2000 and

reaches 13.1 per 100,000 inhabitants in 2020.

• The decrease in the density of acute-care beds between 2002 and 2020 corresponds

to the decrease observed between 1960 and 2000, reaching 592 beds per 100,000

inhabitants in 2020.

• Life expectancy of persons aged over 65 is also derived from the main variant of the

population forecast. It increases from 17.6 years in 2000 to 19.6 years in 2020.

• The development of GDP is based on an annual productivity increase of 1.75 percent.

This implies economic growth as already assumed in the forecast of age-related health

care spending27.

Results of the forecast

Figure 6 shows the development of the GDP ratios of total expenditure on health according to

scenarios. The underestimations of health care expenditure results in a clearly slower increase

in the GDP share spend on health. The difference to the scenario “probable“ however

decreases with a prolonged forecast period. In the scenario “probable“ the share health care

expenditure takes in the Gross Domestic Product reaches approximately 10 percent in 2020,

in the scenario “underestimated“ 9.4 percent.

The officially underestimated health care expenditure leads to a significantly slower growth of

per-capita expenses (at 1995‘s prices). Whereas in the scenario “underestimated“ per-capita

expenditure will have surpassed its original level by two thirds in 2020, per-capita expenses

almost double in the scenario “probable“(cf. figure 7).

27 Riedel M., M. M. Hofmarcher: Nachfragemodell Gesundheitswesen, part 1, IHS Project Report, September 2001.


Figure 6: Development of health expenditure as percent of GDP, 2000-2020

Source: IHS HealthEcon calculations 2003.

Figure 7: Development of per-capita health expenditure at 1995‘s prices, 2000=100

Source: IHS HealthEcon calculations 2003

As for health policy it is of great importance to know the actual financing flow, not only with

regard to the level of health care expenditure and the development of the financial burden, but

also regarding future growth dynamics.

100

120

140

160

180

200

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

2020

Ind

ex 2

000=

100

Scenario probable

Scenariounderestimated

0

2

4

6

8

10

12

2000 2005 2010 2015 2020

Scenario underestimated

Scenario probable


In the framework of current provisions, the official statistics of health care expenditure are

correct. It has to be pointed out yet that health care spending in Austria is higher than officially

indicated. The entire extent of the Austrian health care sector can only be revealed by

calculations that include all hospital-related expenses, which account for the major share of

health care spending.

Forming the basis of the present forecast, the IHS HealthEcon Model is a supplement to other

methods, since it explicitly takes into account supply factors (densities of acute-care beds and

radiologists) and technical progress in the health care sector. We distinguish between cost-

increasing and cost-reducing technical progress. The density of radiologists is taken as an

example of cost-increasing, that of acute-care beds of cost-reducing progress. The latter may

also be reflected by an increase in life expectancy. In the regression model life expectancy of

persons aged over 65 has turned out to be more appropriate than that of younger people and

considerably enhances the model’s quality. This result fits with the hypothesis of a relatively

cost-saving compression of morbidity. Considering the assumption on the overall economic

productivity it will in the future be crucial to calculate scenarios of various assumptions on

productivity. Including relative prices has not yielded any explanation to the development

dynamics of health care expenditure. The development of prices in the health care sector

should be paid special attention to as they might provide crucial information on quality-

enhancing technical progress as well as on distortions caused by administratively fixed prices.


Table A1: Real per-capita Gross Domestic Product, US Dollar, purchasing power parity Annual average Index EU15=100 growth rates 1990 1995 1996 1997 1998 1999 2000 1990 1995 1996 1997 1998 1999 2000 90-95 95-00 90-00

Austria 16,971 21,410 22,316 23,549 24,582 25,646 27,158 105 110 111 110 110 110 115 4.8 4.9 4.8 Belgium 16,849 21,890 22,411 23,731 23,551 24,767 27,178 104 112 111 111 106 106 115 5.4 4.4 4.9 Denmark 17,096 22,939 24,203 25,546 26,711 27,690 27,627 105 117 120 119 120 119 117 6.1 3.8 4.9 Germany 18,327 21,416 21,530 23,040 23,759 24,542 25,103 113 110 107 108 107 105 106 3.2 3.2 3.2 Finland 16,489 18,777 19,421 21,220 22,064 23,300 24,996 102 96 96 99 99 100 106 2.6 5.9 4.2 France 17,622 20,638 20,890 21,712 22,587 23,745 24,223 109 106 104 101 102 102 102 3.2 3.3 3.2 Greece 9,455 12,743 13,311 14,034 15,012 15,722 16,501 58 65 66 66 67 68 70 6.2 5.3 5.7 Ireland 11,780 18,066 18,837 22,055 23,125 25,840 29,866 73 92 94 103 104 111 126 8.9 10.6 9.7 Italy 16,475 20,136 20,874 21,762 23,003 24,037 23,626 102 103 104 102 103 103 100 4.1 3.2 3.7 Luxembourg 24,286 33,360 34,239 37,499 40,613 43,527 50,061 150 171 170 175 183 187 212 6.6 8.5 7.5 Netherlands 16,602 21,249 21,814 24,020 25,056 26,552 25,657 102 109 108 112 113 114 108 5.1 3.8 4.4 Portugal 9,875 13,813 14,283 15,900 16,135 16,776 17,290 61 71 71 74 73 72 73 6.9 4.6 5.8 Sweden 17,646 19,949 20,523 21,771 22,056 23,476 24,277 109 102 102 102 99 101 103 2.5 4.0 3.2 Spain 12,269 15,295 15,976 16,981 18,121 19,128 19,472 76 78 79 79 81 82 82 4.5 4.9 4.7 United Kingdom 16,137 18,877 20,252 21,815 22,330 23,303 23,509 100 97 101 102 100 100 99 3.2 4.5 3.8

EU15* 16,205 19,543 20,145 21,421 22,251 23,270 23,655 100 100 100 100 100 100 100 3.8 3.9 3.9 EU12* 16,161 19,602 20,042 21,261 22,163 23,180 23,596 100 100 99 99 100 100 100 3.9 3.8 3.9

Switzerland 21,488 25,673 25,234 27,285 27,836 28,778 28,769 133 131 125 127 125 124 122 3.6 2.3 3.0 United States 23,053 27,924 29,224 30,833 32,267 33,763 35,657 142 143 145 144 145 145 151 3.9 5.0 4.5

Bulgaria 4,700 4,604 n.a. 4,010 4,809 5,071 5,710 29 24 n.a. 19 22 22 24 -0.4 4.4 2.0 Estonia 6,438 4,062 n.a. n.a. 7,682 8,355 10,066 40 21 n.a. n.a. 35 36 43 -8.8 19.9 4.6 Latvia 6,457 3,297 n.a. 3,940 5,728 6,264 7,045 40 17 n.a. 18 26 27 30 -12.6 16.4 0.9 Lithuania 4,913 3,843 n.a. 4,220 6,436 6,656 7,106 30 20 n.a. 20 29 29 30 -4.8 13.1 3.8 Malta 8,732 13,316 n.a. 13,180 16,447 15,189 17,273 54 68 n.a. 62 74 65 73 8.8 5.3 7.1 Poland 4,899 7,004 7,330 7,544 8,471 8,991 9,051 30 36 36 35 38 39 38 7.4 5.3 6.3 Romania 2,800 4,431 4,580 4,310 5,648 6,041 6,423 17 23 23 20 25 26 27 9.6 7.7 8.7 Slovakia 6,690 b 8,554 9,244 10,036 10,795 11,112 11,243 41 44 46 47 49 48 48 5.0 5.6 5.3 Slovenia 9,156 a 12,500 13,200 14,100 14,293 15,977 17,367 57 64 66 66 64 69 73 6.4 6.8 6.6 Czech Republic 11,533 12,378 12,983 13,148 13,318 13,595 13,991 71 63 64 61 60 58 59 1.4 2.5 2.0 Turkey 4,691 5,638 5,999 6,469 6,272 5,966 6,974 29 29 30 30 28 26 29 3.7 4.3 4.0 Hungary 8,362 9,057 9,316 9,977 10,841 11,501 12,416 52 46 46 47 49 49 52 1.6 6.5 4.0 Cyprus 12,784 16,939 17,384 17,560 18,232 19,393 20,824 79 87 86 82 82 83 88 5.8 4.2 5.0

Accession 13* 5,351 6,521 n.a. 7,117 7,647 7,813 8,427 33 33 n.a. 33 34 34 36 4.0 5.3 4.6 CEEC 10* 5,640 6,933 n.a. 7,411 8,371 8,840 9,213 35 35 n.a. 35 38 38 39 4.2 5.9 5.0 * population-weighted average a 1991, b 1992 Sources: WHO Health for all Database, January 2003, Statistik Austria for Austria, OECD Health Data 2002 for the USA, Word Development Indicators for Cyprus, IHS HealthEcon calculations 2003.


Table A2 Total health expenditure per capita, US Dollar purchasing power parity Average annual growth rates Index EU15=100 1990 1995 1996 1997 1998 1999 2000 1990 1995 1996 1997 1998 1999 2000 90-95 95-00 90-00

Austria 1206 1831 1940 1786 1888 1997 2013 95 108 110 97 99 99 95 8.7 1.9 10.8 Belgium 1245 1896 1982 2013 2008 2144 2269 99 112 112 109 105 106 107 8.8 3.7 12.8 Denmark 1453 1882 2004 2100 2241 2358 2420 115 111 114 114 118 117 114 5.3 5.2 10.7 Germany 1600 2264 2341 2465 2520 2616 2748 127 134 133 134 132 130 129 7.2 4.0 11.4 Finland 1295 1415 1487 1550 1529 1605 1664 103 84 84 84 80 80 78 1.8 3.3 5.1 France 1517 1980 1997 2046 2109 2226 2349 120 117 113 111 111 110 110 5.5 3.5 9.1 Greece 712 1131 1179 1224 1307 1375 1399 56 67 67 66 69 68 66 9.7 4.3 14.5 Ireland 777 1300 1318 1526 1576 1752 1953 62 77 75 83 83 87 92 10.8 8.5 20.2 Italy 1321 1486 1566 1684 1774 1882 2032 105 88 89 91 93 93 95 2.4 6.5 9.0 Luxembourg 1492 2122 2192 2204 2361 2613 n.a. 118 125 124 119 124 129 n.a. 7.3 5.3 ~ 15.0 ~ Netherlands 1333 1787 1818 1958 2040 2172 2246 106 105 103 106 107 108 106 6.0 4.7 11.0 Portugal 611 1146 1211 1360 1345 1402 1441 48 68 69 74 71 69 68 13.4 4.7 18.7 Sweden 1492 1622 1716 1770 1748 n.a. n.a. 118 96 97 96 92 n.a. n.a. 1.7 2.5 ~ 5.4 ~ Spain 813 1184 1238 1294 1384 1469 1556 64 70 70 70 73 73 73 7.8 5.6 13.9 United Kingdom 972 1315 1422 1481 1527 1666 1763 77 78 81 80 80 83 83 6.2 6.0 12.6

EU15* 1263 1694 1763 1845 1907 2019 2128 100 100 100 100 100 100 100 6.0 4.7 11.0 EU12* 1310 1767 1827 1914 1980 2082 2195 104 104 104 104 104 103 103 6.2 4.4 10.9

Switzerland 1836 2555 2615 2841 2952 3080 3222 145 151 148 154 155 153 151 6.8 4.7 11.9 United States 2739 3703 3854 4005 4178 4373 4631 217 219 219 217 219 217 218 6.2 4.6 11.1

Bulgaria 244 214 b n.a. n.a. n.a. n.a. n.a. 19 13 n.a. n.a. n.a. n.a. n.a. -2.5 n.a. n.a. Estonia 301 a 240 n.a. n.a. 453 543 594 24 14 n.a. n.a. 24 27 28 -4.5 19.9 14.6 Latvia 161 138 n.a. 177 235 326 338 13 8 n.a. 10 12 16 16 -3.0 19.6 15.9 Lithuania 162 200 n.a. 253 405 406 426 13 12 n.a. 14 21 20 20 4.3 16.4 21.3 Malta n.a. n.a. n.a. n.a. n.a. 1262 1522 n.a. n.a. n.a. n.a. n.a. 63 72 n.a. n.a. n.a. Poland 258 420 469 461 543 557 n.a. 20 25 27 25 28 28 n.a. 10.2 7.3 ~ 21.2 ~ Romania 79 142 156 134 232 272 n.a. 6 8 9 7 12 13 n.a. 12.4 17.7 ~ 36.2 ~ Slovakia 340 a 530 684 608 641 649 690 27 31 39 33 34 32 32 9.3 5.4 15.2 Slovenia 311 975 1030 1086 1115 1230 1389 25 58 58 59 58 61 65 25.7 7.3 34.9 Czech Republic 576 902 917 930 944 972 1031 46 53 52 50 50 48 48 9.4 2.7 12.3 Turkey 171 190 234 272 303 231 297 14 11 13 15 16 11 14 2.1 9.4 11.7 Hungary 510 677 671 693 751 787 841 40 40 38 38 39 39 40 5.8 4.4 10.5 Cyprus n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

Accession 13* 313 482 n.a. 518 549 576 668 25 28 n.a. 28 29 29 31 9.0 6.7 16.4 CEEC 10* 360 559 n.a. 612 640 664 901 29 33 n.a. 33 34 33 42 9.2 10.0 20.1 * population-weighted average a 1992, b 1994, ~ or most recent year available

Sources: WHO Health for all Database, January 2003, Statistik Austria for Austria, OECD Health Data 2002 for the USA, IHS HealthEcon calculations 2003.


Table A3: Total health expenditure in percent of Gross Domestic Product Index EU15=100 1990 1995 1996 1997 1998 1999 2000 2001 1990 1995 1996 1997 1998 1999 2000

Austria 7.1 8.6 8.7 7.6 7.7 7.8 7.4 7.3 92 99 99 88 90 90 85 Belgium 7.4 8.7 8.8 8.5 8.5 8.7 8.7 n.a. 96 100 101 99 99 100 100 Denmark 8.5 8.2 8.3 8.2 8.4 8.5 8.3 8.4 110 94 95 95 98 98 95 Germany 8.7 10.6 10.9 10.7 10.6 10.7 10.6 n.a. 113 122 124 124 124 123 121 Finland 7.9 7.5 7.7 7.3 6.9 6.9 6.6 n.a. 102 86 88 85 81 79 76 France 8.6 9.6 9.6 9.4 9.3 9.4 9.5 n.a. 111 111 110 109 109 108 109 Greece 7.5 8.9 8.9 8.7 8.7 8.7 8.3 9.2 97 103 102 101 102 100 95 Ireland 6.6 7.2 7.0 6.9 6.8 6.8 6.7 n.a. 85 83 80 80 80 78 77 Italy 8.0 7.4 7.5 7.7 7.7 7.8 8.1 8.0 104 85 86 89 90 90 93 Luxembourg 6.1 6.4 6.4 5.9 5.8 6.0 n.a. n.a. 79 74 73 69 68 69 n.a. Netherlands 8.0 8.4 8.3 8.2 8.1 8.2 8.1 n.a. 104 97 95 95 95 94 93 Portugal 6.2 8.3 8.5 8.6 8.3 8.4 8.2 n.a. 80 96 97 100 97 97 94 Sweden 8.5 8.1 8.4 8.1 7.9 n.a. n.a. n.a. 110 93 96 94 92 n.a. n.a. Spain 6.6 7.7 7.7 7.6 7.6 7.7 7.7 n.a. 85 89 88 88 89 89 88 United Kingdom 6.0 7.0 7.0 6.8 6.8 7.1 7.3 n.a. 78 81 80 79 80 82 84

EU15* 7.7 8.7 8.8 8.6 8.5 8.7 8.7 n.a. 100 100 100 100 100 100 100 EU12* 6.4 7.3 7.3 7.2 7.1 7.2 7.2 n.a. 82 84 83 83 84 83 83

Switzerland 8.5 10.0 10.4 10.4 10.6 10.7 10.7 n.a. 110 115 119 121 124 123 123 United States 11.9 13.3 13.2 13.0 12.9 13.0 13.0 n.a. 154 153 151 151 151 150 149

Bulgaria 4.1 4.0 3.9 4.3 3.8 4.1 n.a. n.a. 53 46 n.a. n.a. n.a. n.a. n.a. Estonia 4.5 b 5.9 6.1 6.0 5.9 6.5 5.9 5.5 58 68 70 70 69 75 68 Latvia 2.5 4.2 4.5 4.5 4.1 5.2 4.8 4.8 32 48 51 52 48 60 55 Lithuania 3.3 5.2 5.4 6.0 6.3 6.1 6.0 5.7 43 60 62 70 74 70 69 Malta n.a. n.a. n.a. n.a. n.a. 8.3 8.8 8.9 n.a. n.a. n.a. n.a. n.a. 96 101 Poland 5.3 6.0 6.4 6.1 6.4 6.2 n.a. n.a. 69 69 73 71 75 71 n.a. Romania 2.8 3.2 3.4 3.1 4.1 4.5 n.a. n.a. 36 37 39 36 48 52 n.a. Slovakia 5.4 6.2 7.4 7.4 7.0 6.7 6.5 n.a. 69 71 85 86 82 77 74 Slovenia 5.6 7.8 7.8 7.7 7.8 7.7 8.0 8.2 73 90 89 89 91 89 92 Czech Republic 5.0 7.3 7.1 7.1 7.1 7.2 7.2 7.4 65 84 81 83 83 83 82 Turkey 3.6 3.4 3.9 4.2 4.8 3.9 4.3 n.a. 47 39 45 49 56 45 49 Hungary 6.1 7.5 7.2 7.0 6.9 6.8 6.7 5.7 79 86 82 81 81 78 77 Cyprus 4.3 a 4.5 c n.a. n.a. n.a. n.a. n.a. n.a. 55 52 n.a. n.a. n.a. n.a. n.a.

Accession 13* 4.4 5.0 5.3 5.3 5.7 5.4 n.a. n.a. 56 58 61 62 66 63 n.a. CEEC 10* 4.6 5.8 6.0 5.9 6.1 6.1 n.a. n.a. 60 67 68 68 72 71 n.a. * GDP weighted a 1991, b 1992, c 1993 Sources: WHO Health for all Database, January 2003, Statistik Austria for Austria from 1997, OECD Health Data 2002 for the USA and Germany 1990, World Development Indicators 2002 for Bulgaria and Cyprus, IHS HealthEcon calculations 2003.


Table A4: Public health expenditure in percent of total health expenditure

Index EU15=100 1990 1995 1996 1997 1998 1999 2000 2001 1990 1995 1996 1997 1998 1999 2000

Austria 73.5 71.8 70.6 70.4 70.5 69.7 68.5 67.3 94 95 94 95 95 94 92 Belgium 88.9 69.6 71.8 70.5 70.6 71.1 71.2 n.a. 114 92 95 95 95 96 96 Denmark 82.7 82.5 82.4 82.3 81.9 82.2 82.1 82.0 106 109 110 110 110 111 110 Germany 76.2 76.7 76.8 75.3 74.8 74.8 75.1 n.a. 98 102 102 101 101 101 101 Finland 80.9 75.5 75.8 76.1 76.3 75.4 75.1 n.a. 104 100 101 102 103 102 101 France 76.6 76.1 76.1 76.2 76.0 76.1 76.0 n.a. 98 101 101 102 102 103 102 Greece 62.7 54.5 55.2 55.1 54.4 54.3 55.5 55.2 80 72 73 74 73 73 74 Ireland 73.1 73.8 73.3 76.0 76.2 76.3 75.8 n.a. 94 98 97 102 103 103 102 Italy 79.3 72.2 71.8 72.2 72.0 72.3 73.7 75.4 102 96 95 97 97 98 99 Luxembourg 93.1 92.4 92.8 92.5 92.4 92.9 n.a. n.a. 119 122 123 124 124 125 n.a. Netherlands 67.1 71.0 66.2 67.8 67.8 66.5 67.5 n.a. 86 94 88 91 91 90 91 Portugal 65.5 61.7 64.7 64.8 67.5 70.7 71.2 n.a. 84 82 86 87 91 95 96 Sweden 89.9 85.2 84.8 84.3 83.8 n.a. n.a. n.a. 115 113 113 113 113 n.a. n.a. Spain 78.7 70.9 71.1 71.1 70.5 70.2 69.9 n.a. 101 94 95 95 95 95 94 United Kingdom 83.6 83.9 82.9 79.9 79.9 80.1 81.0 n.a. 107 111 110 107 108 108 109

EU15* 78.1 75.4 75.2 74.5 74.2 74.1 74.5 n.a. 100 100 100 100 100 100 100 EU12* 76.7 73.8 73.6 73.2 73.0 73.0 73.3 n.a. 98 98 98 98 98 99 98

Switzerland 66.4 53.8 54.7 55.2 54.9 55.3 55.6 n.a. 85 71 73 74 74 75 75 United States 39.6 45.3 45.5 45.2 44.5 44.3 44.3 n.a. 51 60 60 61 60 60 59

Bulgaria 100.0 100.0 a n.a. n.a. n.a. n.a. n.a. n.a. 128 133 n.a. n.a. n.a. n.a. n.a. Estonia n.a. n.a. 88.0 87.0 86.3 80.4 76.7 77.7 n.a. n.a. 117 117 116 109 103 Latvia 100.0 95.0 88.0 85.0 79.3 79.6 73.7 71.2 128 126 117 114 107 107 99 Lithuania 90.0 86.3 77.1 77.6 76.7 75.2 72.4 71.7 115 114 102 104 103 101 97 Malta n.a. n.a. n.a. n.a. n.a. 50.8 53.5 65.7 n.a. n.a. n.a. n.a. n.a. 69 72 Poland 91.7 72.9 73.4 72.0 65.4 75.1 n.a. n.a. 117 97 98 97 88 101 n.a. Romania 100.0 100.0 100.0 100.0 100.0 100.0 n.a. n.a. 128 133 133 134 135 135 n.a. Slovakia 100.0 94.8 94.2 91.2 91.4 88.9 90.3 n.a. 128 126 125 122 123 120 121 Slovenia 100.0 89.7 89.1 88.3 88.0 87.5 86.6 86.7 128 119 118 119 119 118 116 Czech Republic 96.2 92.7 92.5 91.7 91.9 91.5 91.4 91.4 123 123 123 123 124 123 123 Turkey 61.0 70.3 69.2 71.6 71.9 80.0 80.0 n.a. 78 93 92 96 97 108 107 Hungary 100.0 84.0 81.6 81.3 79.4 78.1 75.5 74.0 128 111 108 109 107 105 101 Cyprus n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

Accession 13* 87.3 81.6 79.9 79.2 77.3 82.1 82.1 n.a. 112 108 106 106 104 111 110 CEEC 10* 96.1 84.7 83.5 82.1 79.3 82.9 84.2 n.a. 123 112 111 110 107 112 113 * weighted at the total health care spending, a 1994 Sources: WHO Health for all Database, January 2003, Statistik Austria for Austria from 1997 on, OECD Health Data 2002 for the USA and Germany 1990, IHS HealthEcon calculations 2003.

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Health expenditure in the EU: Comparability is ailing Focus: Forecast of health ... · 2017-03-27 · Health expenditure in the EU: Comparability is ailing In an international comparison