Health expenditure in the EU: Comparability is ailing Focus: Forecast of health ... ·...
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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.
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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
EU/accession countries:
Czech Republic, Finland, Poland,
Spain, Turkey
Other OECD countries:
Mexico, New Zealand
Calculation of health expenditure does not
entirely follow the OECD/SHA definition
Group 3:
Low level of
comparability
EU/accession countries:
Austria*, Greece, Ireland, Italy,
Luxembourg*, Portugal, Slovakia,
Sweden
Other OECD countries:
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
EU/accession countries:
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.
HEALTH SYSTEM WATCH I/2003 3
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
HEALTH SYSTEM WATCH I/2003 4
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.
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...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 SYSTEM WATCH I/2003 6
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
HEALTH SYSTEM WATCH I/2003 7
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.
HEALTH SYSTEM WATCH I/2003 8
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
HEALTH SYSTEM WATCH I/2003 9
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
HEALTH SYSTEM WATCH I/2003 10
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
HEALTH SYSTEM WATCH I/2003 11
…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.
HEALTH SYSTEM WATCH I/2003 12
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
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Mal
ta
Tur
ky
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uani
a
Pol
and
Bul
garia
Hun
gary
Est
onia
Slo
veni
a
Slo
vaki
a
Cze
ch R
epub
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19952000
EU15 2000AC13 2000
HEALTH SYSTEM WATCH I/2003 13
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.
HEALTH SYSTEM WATCH I/2003 14
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.
HEALTH SYSTEM WATCH I/2003 15
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.
HEALTH SYSTEM WATCH I/2003 16
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.
HEALTH SYSTEM WATCH I/2003 17
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.
HEALTH SYSTEM WATCH I/2003 18
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.
HEALTH SYSTEM WATCH I/2003 19
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.
HEALTH SYSTEM WATCH I/2003 20
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
HEALTH SYSTEM WATCH I/2003 21
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.
HEALTH SYSTEM WATCH I/2003 22
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.
HEALTH SYSTEM WATCH I/2003 23
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.
HEALTH SYSTEM WATCH I/2003 24
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.
HEALTH SYSTEM WATCH I/2003 25
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.