The Impact of Technical Change on Healthcare Production and Efficiency
Year 2018,
Volume: 21 Issue: 4, 641 - 653, 29.12.2018
Can Bekaroglu
,
Dennis Heffley
Abstract
This article measures the technical efficiency of healthcare production and estimates the impact of technical change on healthcare across OECD countries between 2000 and 2011, based on a 34 country panel data set, extending the study by Fare et al. (1997). The study adopted a DEA (Data Envelopment Analysis) based output-oriented efficiency measure to obtain the productive efficiency of each country for all given years, and used the Malmquist Index to determine the productivity growth and decompose the technical change from efficiency changes over the years. It is found that the production frontier shifted up around 0.8% annually between 2000 and 2011, with a cumulative 8.5% technical and 7.2% productivity increase over the period. Technological progress seems to be stable over time, while most of the fluctuations in productivity growth come from changes in efficiency due to utilization of new technologies.
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55–72.
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Journal of Operational Research 111(3): 461-469.
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Do Little to Contain Costs. Health Affairs 13: 224-238.
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Of A New Technique. Medical Care 22(10): 922–938.
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Year 2018,
Volume: 21 Issue: 4, 641 - 653, 29.12.2018
Can Bekaroglu
,
Dennis Heffley
References
- 1. Aaron H. J. (1991) Serious And Unstable Condition: Financing America's Health
Care Washington: The Brookings Institution.
2. Banker R. D., Charnes A. and Cooper W. W. (1984) Some Models For
Estimatingtechnical And Scale İnefficiencies İn Data Envelopment Analysis.
Management Science 30(9): 1078–92.
3. Caves D. W., Christensen L. R. and Diewert W. E. (1982) The Economic Theory Of
İndex Numbers And The Measurement Of İnput, Output And Productivity.
Econometrica 50(6): 1393.
4. Charnes A., Cooper W. W. and Rhodes E. (1978) Measuring The Efficiency Of Decision
Making Units. European Journal of Operational Research 2(6): 429–44.
5. Deb A. and Ray S., (2013) Economic Reforms and Total Factor Productivity Growth
of Indian Manufacturing: An Inter-State Analysis. Working papers 2013-04,
University of Connecticut, Department of Economics revised Apr 2013.
6. Färe R., Grosskopf S., Lindgren B. and Roos P. (1989) Productivity Developments İn
Swedish Hospitals: A Malmquist Output İndex Approach. Discussion paper 89-3.
Carbondale, IL: Southern Illinois University.
7. Färe R. and Grosskopf S. (1992) Malmquist Productivity Indexes and Fisher Ideal
Indexes. The Economic Journal 102(410): 158-160.
8. Färe R., Grosskopf S., Norris M. and Zhang Z. (1994) Productivity Growth, Technical
Progress, and Efficiency Change in Industrialized Countries. American Economic
Review 84(1): 66-83.
9. Färe R., Grosskopf S., Lindgren B. and Poullier J. P. (1997) Productivity Growth İn
Health Care Delivery. Medical Care 35(4): 354–366.
10. Farrell M. J. (1957) The Measurement Of Productive Efficiency. Journal of Royal
Statistical Society (Series A) 120(3): 253–281.
11. Hollingsworth B. (2008). The Measurement Of Efficiency and Productivity of Health
Care Delivery. Health Economics 17(10): 1107–1128.
12. Malmquist S. (1953) Index Numbers and Indifference Curves. Trab Estat 4(2): 209-
242.
13. Moscone F., Tosetti E., Costantini M. and Ali M. (2013) The Impact of Scientific
Research on Health Care: Evidence From The OECD Countries. Economic Modelling
32: 325-332.
14. Muñiz M., Paradi J., Ruggiero J. and Yang Z. (2006) Evaluating Alternative DEA
Models Used To Control For Non-Discretionary İnputs. Computers and Operations
Research 33(5): 1173-1183
15. Newhouse J. P. (1993) An Iconoclastic View of Health Cost Containment. Health
Affairs 12: 152-171.
16. Nishimuzu M. and Page J. M. (1982) Total Factor Productivity Growth, Technological
Progress And Technical Efficiency Change: Dimensions Of Productivity Change İn
Yugoslavia 1965–1978. Economics Journal 92(368): 920–936.
17. Nunamaker T. R. and Lewin A. Y. (1983) Measuring Routine Nursing Efficiency: A
Comparison Of Cost Per Patient Day And Data Envelopment Analysis
Models/Comment. Health Services Research 18(2): 183–208.
18. O’Neill L., Rauner M., Heidelberger K. and Kraus M. (2008) A Cross National
Comparison And Taxonomy Of DEA Based Hospital Efficiency Studies. Socio-
Economic Planning Sciences 42(3): 158–189.
19. Ozcan Y. A. (2008) Health Care Benchmarking And Performance Evaluation An
Assessment Using Data Envelopment Analysis (DEA). Springer, Newton.
20. Ray S. (2004) Data Envelopment Analysis: Theory And Techniques For Economics
And Operations Research. Cambridge: Cambridge University Press.
21. Retzlaff-Roberts D., Chang C. F. and Rubin R. M. (2004) Technical Efficiency in The
Use of Health Care Resources: A Comparison of OECD Countries. Health Policy 69(1):
55–72.
22. Ruggiero J. (1998) Non-Discretionary Inputs in Data Envelopment Analysis. European
Journal of Operational Research 111(3): 461-469.
23. Schwartz W. B. and Mendelson D. N. (1994) Eliminating Waste and Inefficiency Can
Do Little to Contain Costs. Health Affairs 13: 224-238.
24. Sherman H. D. (1984) Hospital Efficiency Measurement And Evaluation: Empirical Test
Of A New Technique. Medical Care 22(10): 922–938.
25. Wang J., Jamison D. T., Bos E., Preker A. and Peaboy J. (1999) Measuring Country
Performance on Health: Selected Indicators For 115 Countries. Human
Development Network, Health, Nutrition and Population Studies. Washington, DC:
World Bank.
26. World Health Organisation (2000) World Health Report: Health Systems: Improving
Performance. Geneva: WHO.
27. Global Health Observatory Data Repository, retrieved in Fall 2015,
http://apps.who.int/gho/data/node.main.NCD56?lang=en
28. OECD Health Statistics 2013 - Frequently Requested Data, retrived in Fall 2015,
http://www.oecd.org/health/oecdhealthdata2013-frequentlyrequesteddata.htm