Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
The European Journal of Health Economics
Published in: The European Journal of Health Economics 2/2013

01-04-2013 | Original Paper

Determinants of healthcare system’s efficiency in OECD countries

Authors: Sharon Hadad, Yossi Hadad, Tzahit Simon-Tuval

Published in: The European Journal of Health Economics | Issue 2/2013

Login to get access

Abstract

Objective

Firstly, to compare healthcare systems’ efficiency (HSE) using two models: one incorporating mostly inputs that are considered to be within the discretionary control of the healthcare system (i.e., physicians’ density, inpatient bed density, and health expenditure), and another, including mostly inputs beyond healthcare systems’ control (i.e., GDP, fruit and vegetables consumption, and health expenditure). Secondly, analyze whether institutional arrangements, population behavior, and socioeconomic or environmental determinants are associated with HSE.

Design

Data envelopment analysis (DEA) was utilized to calculate OECD countries’ HSE. Life expectancy and infant survival rate were considered as outputs in both models. Healthcare systems’ rankings according to the super-efficiency and the cross-efficiency ranking methods were used to analyze determinants associated with efficiency.

Results

(1) Healthcare systems in nine countries with large and stable economies were defined as efficient in model I, but were found to be inefficient in model II; (2) Gatekeeping and the presence of multiple insurers were associated with a lower efficiency; and (3) The association between socioeconomic and environmental indicators was found to be ambiguous.

Conclusions

Countries striving to improve their HSE should aim to impact population behavior and welfare rather than only ensure adequate medical care. In addition, they may consider avoiding specific institutional arrangements, namely gatekeeping and the presence of multiple insurers. Finally, the ambiguous association found between socioeconomic and environmental indicators, and a country’s HSE necessitates caution when interpreting different ranking techniques in a cross-country efficiency evaluation and needs further exploration.
Appendix
Available only for authorised users
Footnotes
1
Calculated as the average of countries’ data in 1975 and 2008. Source: OECD Health Data 2010 [2].
 
2
For a detailed description of the two methods see “Appendix”.
 
3
Only Slovak Republic was defined as inefficient according to model I but as efficient according to model II.
 
Literature
1.
Martín, J.J.M., del Amo González, M.P.L., García, M.D.C.: Review of the literature on the determinants of healthcare expenditure. Appl. Econ. 43, 19–46 (2011)CrossRef
2.
OECD. OECD Health Data: health expenditure and financing, OECD Health Statistics (database). (2010)
3.
Duncan, G.J., Daly, M.C., McDonough, P., Williams, D.R.: Optimal indicators of socioeconomic status for health research. Am. J. Public Health 92, 1151–1157 (2002)PubMedCrossRef
4.
Lahelma, E., Martikainen, P., Laaksonen, M., Aittomäki, A.: Pathways between socioeconomic determinants of health. J. Epidemiol. Community Health 58, 327–332 (2004)PubMedCrossRef
5.
Spinks, J., Hollingsworth, B.: Cross-country comparisons of technical efficiency of health production: a demonstration of pitfalls. Appl. Econ. 41, 417–427 (2009)CrossRef
6.
Williams, A.: Science or marketing at WHO? A commentary on ‘World Health 2000’. Health Econ. 10, 93–100 (2001)PubMedCrossRef
7.
Richardson, J., Wildman, J., Robertson, I.K.: A critique of the World Health Organisation’s evaluation of health system performance. Health Econ. 12, 355–366 (2003)PubMedCrossRef
8.
Smith, P.C., Street, A.: Measuring the efficiency of public services: the limits of analysis. J. R. Stat. Soc. A Stat. 168, 401–417 (2005)CrossRef
9.
Simpson, H.: Productivity in public services. J Econ Surv 23, 250–276 (2009)CrossRef
10.
Hollingsworth, B.: The measurement of efficiency and productivity of health care delivery. Health Econ. 17, 1107–1128 (2008)PubMedCrossRef
11.
Hollingsworth, B.: Non-parametric and parametric applications measuring efficiency in health care. Health Care Manag. Sci. 6, 203–218 (2003)PubMedCrossRef
12.
Hadad, Y., Ben-Yair, A., Friedman, L., Sinuany-Stern, Z.: Measuring efficiency of hospitals using the data envelopment analysis model: an application for ranking Israeli hospitals. Commun Dependability Qual. Manag. 9, 22–31 (2006)
13.
Barros, C.P., Gomes de Menezes, A., Peypoch, N., Solonandrasana, B., Vieira, J.C.: An analysis of hospital efficiency and productivity growth using the Luenberger indicator. Health Care Manag. Sci. 11, 373–381 (2008)PubMedCrossRef
14.
Chernichovsky, D., Friedman, L., Sinuany-Stern, Z., Hadad, Y.: The efficiency of general hospitals in Israel according Data Envelope Analysis. Econ. Q. 56, 119–139 (2009)
15.
16.
Schwellnus, C.: Achieving higher performance: enhancing spending efficiency in health and education in Mexico. OECD Economics Department Working Papers, No. 732. (2009). doi:10.​1787/​220731242856
17.
Economou, C., Giorno, C.: Improving the performance of the public health care system in Greece. OECD Economics Department Working Papers, No. 722. (2009). doi:10.​1787/​221250170007
18.
Retzlaff-Roberts, D., Chang, C.F., Rubin, R.M.: Technical efficiency in the use of health care resources: a comparison of OECD countries. Health Policy 69, 55–72 (2004)PubMedCrossRef
19.
Bhat, V.N.: Institutional arrangements and efficiency of health care delivery systems. Eur. J. Health Econ. 6, 215–222 (2005)PubMedCrossRef
20.
Afonso, A., St Aubyn, M.: Non-parametric approaches to education and health efficiency in OECD countries. J. Appl. Econ. 8, 227–246 (2005)
21.
Farrell, M.J.: The measurement of productive efficiency. J. R. Stat. Soc. A Stat. 120, 253–290 (1957)CrossRef
22.
Cooper, W.W., Tone, K.: Measures of inefficiency in data envelopment analysis and stochastic frontier estimation. Eur. J. Oper. Res. 99, 72–88 (1997)CrossRef
23.
Charnes, A., Cooper, W., Rhodes, E.: Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2, 429–444 (1978)CrossRef
24.
Seiford, L.M., Thrall, R.M.: Recent developments in DEA: the mathematical programming approach to frontier analysis. J. Econ. 46, 7–38 (1990)
25.
Banker, R.D., Charnes, A., Cooper, W.W.: Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage. Sci. 30, 1078–1092 (1984)CrossRef
26.
Culyer, A.J., Wagstaff, A.: Equity and equality in health and health care. J. Health Econ. 12, 431–457 (1993)PubMedCrossRef
27.
Hollingsworth, B., Wildman, J.: The efficiency of health production: re‐estimating the WHO panel data using parametric and non‐parametric approaches to provide additional information. Health Econ. 12, 493–504 (2003)PubMedCrossRef
28.
Sueyoshi, T.: DEA-discriminant analysis in the view of goal programming. Eur. J. Oper. Res. 115, 564–582 (1999)CrossRef
29.
Sueyoshi, T., Goto, M.: Slack-adjusted DEA for time series analysis: Performance measurement of Japanese electric power generation industry in 1984–1993. Eur. J. Oper. Res. 133, 232–259 (2001)CrossRef
30.
Andersen, P., Petersen, N.C.: A procedure for ranking efficient units in data envelopment analysis. Manage. Sci. 39, 1261–1264 (1993)CrossRef
31.
Sexton, T.R., Silkman, R.H., Hogan, A.J.: Data envelopment analysis: critique and extensions. In: Silkman, R.H. (ed.) Measuring Efficiency: An Assessment of Data Envelopment Analysis, pp. 73–105. Jossey-Bass, San Francisco (1986)
32.
33.
Starfield, B.: Health services research: a working model. N. Engl. J. Med. 289(2), 132–136 (1973)PubMedCrossRef
34.
35.
36.
OECD. OECD Health Data: Health status, OECD Health Statistics (database). (2010)
37.
38.
OECD. OECD Health Data: Health care resources, OECD Health Statistics (database). (2010)
39.
OECD. OECD Health Data: economic references, OECD Health Statistics (database). (2010)
40.
OECD. OECD Health Data: non-medical determinants of health, OECD Health Statistics (database). (2010)
41.
OECD. OECD Factbook Statistics 2010: Country Indicators, OECD Factbook Statistics (database). (2010)
42.
43.
Yale Center for Environmental Law and Policy (YCELP) and Center for International Earth Science Information Network (CIESIN), Columbia University, with the World Economic Forum, and Joint Research Centre (JRC) of the European Commission: 2008 Environmental Performance Index. Available at http://​sedac.​ciesin.​columbia.​edu/​es/​epi/​ (2008). Accessed 20 February 2011
44.
45.
46.
House, J.S., Williams, D.R.: Understanding and reducing socioeconomic and racial/ethnic disparities in health. In: Smedley, B.D., Syme, S.L. (eds.) Promoting Health: Intervention Strategies From Social and Behavioral Research, pp. 81–124. National Academy Press, Washington (2000)
47.
Robert, S.A., House, J.S.: Socioeconomic inequalities in health: Integrating individual-, community-, and societal-level theory and research. In: Albrecht, G., Fitzpatrick, R., Scrimshaw, S. (eds.) Handbook of Social Studies in Health and Medicine, pp. 115–135. Sage Publications Ltd, London (2000)CrossRef
48.
Ezzati, M., Lopez, A.D., Rodgers, A., Vander Hoon, S., Murray, C.J.L.: Selected major risk factors and global and regional burden of disease. Lancet 360, 1347–1360 (2002)PubMedCrossRef
49.
Rosner, B.: Fundamentals of Biostatistics. Books/Cole, Boston (2010)
50.
Kujala, U.M., Kaprio, J., Koskenvuo, M.: Modifiable risk factors as predictors of all-cause mortality: the roles of genetics and childhood environment. Am. J. Epidemiol. 156, 985–993 (2002)PubMedCrossRef
51.
Laaksonen, M., Mcalister, A.L., Laatikainen, T., Drygas, W., Morava, E., Nūssel, E., Oganov, R., Pardell, H., Uhanov, M., Puska, P.: Do health behaviour and psychosocial risk factors explain the European East-West gap in health status? Eur J Public Health 11, 65–73 (2001)PubMedCrossRef
52.
Isaacs, S.L., Schroeder, S.A.: Class—the ignored determinant of the nation’s health. N. Engl. J. Med. 351, 1137–1142 (2004)PubMedCrossRef
53.
Hollingsworth, B., Peacock, S.: Efficiency Measurement in Health and Health Care. Routledge, New York (2008)
54.
Adler, N., Friedman, L., Sinuany-Stern, Z.: Review of ranking methods in the data envelopment analysis context. Eur. J. Oper. Res. 140, 249–265 (2002)CrossRef
55.
Hurley, J.: An overview of the normative economics of the health sector. In: Culyer, A.J., Newhouse, J.P. (eds.) Handbook of health economics, pp. 55–118. Elsevier, New-York (2000)
Metadata
Title
Determinants of healthcare system’s efficiency in OECD countries
Authors
Sharon Hadad
Yossi Hadad
Tzahit Simon-Tuval
Publication date
01-04-2013
Publisher
Springer-Verlag
Published in
The European Journal of Health Economics / Issue 2/2013
Print ISSN: 1618-7598
Electronic ISSN: 1618-7601
DOI
https://doi.org/10.1007/s10198-011-0366-3

Other articles of this Issue 2/2013

The European Journal of Health Economics 2/2013 Go to the issue

Original Paper

Economic evaluation of URMEL-ICE, a school-based overweight prevention programme comprising metabolism, exercise and lifestyle intervention in children

Original Paper

Trends in social class inequalities in the use of health care services within the Spanish National Health System, 1993–2006

Original Paper

The influence of social deprivation on length of hospitalisation

Original Paper

An analysis of the influence of framework aspects on the study design of health economic modeling evaluations

Commentary

The Grossman model after 40 years: a reply to Peter Zweifel

Original Paper

Using respondents’ uncertainty scores to mitigate hypothetical bias in community-based health insurance studies