Davutyan, Nurhan and Bilsel, Murat and Tarcan, Menderes (2012): Risk-Adjusted Mortality, varieties of congestion and patient satisfaction in Turkish provincial general hospitals.
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Abstract: We analyze the operational performance of 330 Turkish provincial general hospitals. To help improve performance on both input and output space, we adopt a directional distance approach. We treat a mortality based variable as “bad output”. Congested hospitals are those for whom the switch from strong to weak disposability of mortality is costly. Thus we are able to address the “quality or adequacy of care” issue. We identify congested hospitals using 3 different direction vectors and derive the associated congestion inefficiency scores. For each case, we show these scores are negatively related to patient satisfaction. We separate congested hospitals into two groups: (i) those requiring uniform sacrifice of good outputs and/or extra inputs in order to reduce mortality, and (ii) those that do not. The latter ones free up some inputs in addition to requiring extra amounts of other inputs and/or produce more of some outputs but less of others as the price of reducing mortality. The first group can be said to operate at “capacity” whereas the latter can be said to display “negative marginal productivity”. Patient dissatisfaction is demonstrably higher in the latter group of hospitals, whereas mortality reduction is positively related to patient satisfaction in “capacity constrained” hospitals. The first group is more likely to be located in emigrating whereas the second one in immigrating regions.
|Item Type:||MPRA Paper|
|Original Title:||Risk-Adjusted Mortality, varieties of congestion and patient satisfaction in Turkish provincial general hospitals|
|English Title:||Risk-Adjusted Mortality, varieties of congestion and patient satisfaction in Turkish provincial general hospitals|
|Keywords:||Directional distance, bad outputs, hospital quality|
|Subjects:||D - Microeconomics > D2 - Production and Organizations > D21 - Firm Behavior: Theory
I - Health, Education, and Welfare > I1 - Health > I11 - Analysis of Health Care Markets
|Depositing User:||Nurhan Davutyan|
|Date Deposited:||14. May 2012 09:50|
|Last Modified:||13. Feb 2013 09:06|
Arocena, P and A.G. Prado (2007). “Accounting for quality in the measurement of hospital performance: evidence from Costa Rica”, Health Economics. 16: 667-685.
Balakrishnan, R. and N.S. Soderstrom. “The cost of system congestion:Evidence from the health care sector”, Journal of Management Accounting Research 12:97-114.
Chung, Y. Fare, R. and S. Grosskopf (1997). “Productivity and undesirable outputs: a directional distance function approach”, Journal of Environmental Management, 51: 229-240.
Cooper, W.W., Honghui D., Seiford L.M., and J. Zhu (2011). “Congestion: Its identification and management with DEA”, in Handbook on Data Envelopment Analysis, W.W. Cooper, L.M. Seiford and J. Zhu eds, Springer, New York.
Dismuke, C.E. and V. Sena (2001). “Is there a trade-off between quality and productivity? The Case of diagnostic technologies in Portugal”, Annals of Operations Research, 107:101-116.
Ersoy, K., Kavuncubasi S., Ozcan Y. and J. Harris (1997). “Technical efficiencies of Turkish Hospitals: DEA approach”, Journal of Medical Systems, 21(2): 67-74.
Fare, R. and S. Grosskopf, (2004). New Directions: Efficiency and Productivity. Springer, New York.
Fare, E., Grosskopf, S., and D. Margaritis (2008) “Efficiency and Productivity: Malmquist and More”, in The Measurement of Productive Efficiency and Productivity Growth, H. Fried, C.A. Knox Lovell and S. S. Schmidt eds. Oxford University Press, New York.
Forsund, F. (2008): “Good Modelling of Bad Outputs: Pollution and Multiple-Output Production”, WP No: 0809-8786, Dept. of Economics, University of Oslo.
HABERTÜRK (2012). http://video.haberturk.com/haber/video/recep-akdag-basin-kulubunde-1/58389
Hollingsworth, B., (2008). “The measurement of efficiency and productivity of health care delivery”, Health Economics, 17:1107-1128
Hollingsworth, B. and J. Spinks (2009). “Cross-country comparisons of technical efficiency of health production: a demonstration of pitfalls”, Applied Economics, 41: 417–427
Hua, Z. and Y, Bian (2007). “DEA with undesirable factors” in Data Irregularities and Structural Complexities in DEA, W. Cook and J. Zhu eds. Springer, New York.
Jacobs, R., Smith P.C., and A. Street (2006). Measuring Efficiency in Health Care. Cambridge University Press, New York.
Liu, W.B., Meng, W., Li X.X. and D.Q. Zhang (2010). “DEA models with undesirable inputs and outputs”, Annals of Operations Research, 173: 177-194.
Ministry of Health. website: http://www.saglik.gov.tr
Murty, S. and. R. Russell (2010): “On modeling pollution-generating technologies”, WP No: 931, Dept. of Economics, University of Warwick.
Nunamaker, T.R. and A. Y. Lewin (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
OECD (2008). OECD Review of Health Systems: TURKEY. Paris. OECD/World Bank.
OECD (2009). OECD Health Data 2009 http://www.oecd.org/health/healthdata
OECD (2011). OECD Health Data 2011 - Frequently Requested Data
O’Neill, L., Rauner M., Heidelberger K. and M. Kraus (2008). “A cross national comparison and taxonomy of DEA based hospital efficiency studies”, Socio-Economic Planning Sciences, 42:158-189.
Ozcan, Y. (2008). Health Care Benchmarking and Performance Evaluation: an assessment using data envelopment analysis, Springer Publishing, New York.
Pastor, J. T (1996). “Translation invariance in data envelopment analysis: A generalization”, Annals of Operations Research, 66: 93-102
Picazo-Tadeo, A. J. and D. Prior. (2005). “Efficiency and environmental regulation: A ‘complex’ situation”, WP 2005/2, Universidad Autonoma de Barcelona.
Ray, S. (2012): “Technical Efficiency Based on Directional Distance Function”, 13’th Barcelona_Istanbul Lectures on Efficiency and Productivity.
Ray, S. (2004). Data Envelopment Analysis: Theory and Techniques for Economics and Operations Research, Cambridge University Press, Cambridge UK.
Sahin, I, Ozcan, Y and H. Ozgen. (2011). “Assessment of hospital efficiency under health transformation program in Turkey”, Central European Journal of Operations Research, 19:19-37.
Sahin, I. and Y. Ozcan. (2000). “Public sector hospital efficiency for provincial markets in Turkey”, Journal of Medical Systems, 24(6): 307-320.
Sahin, I (2009). “Total factor productivity analysis of Turkish Social Security hospitals that were transferred to the Health Ministry” (in Turkish), Iktisat Isletme ve Finans, 24: 9-40.
Scheel, H. (2001). “Undesirable outputs in efficiency evaluations”, European Journal of Operational Research, 132(2): 400-410.
Seiford, L. and J. Zhu (2002). “Modeling undesirable factors in efficiency evaluation”, European Journal of Operational Research, 142: 16–20.
Sherman, H.D. (1984). “Hospital efficiency measurement and evaluation: empirical test of a new technique”, Medical Care, 22 (10):922-938
Thanassoulis, E., Portela, M.C.S., and O. Despic (2008) “DEA: the mathematical programming approach to efficiency analysis”, in The Measurement of Productive Efficiency and Productivity Growth, H. Fried, C.A. Knox Lovell and S. S. Schmidt eds. Oxford University Press, New York.
Turkstat (2012). website: http://www.turkstat.gov.tr.
World Bank (2003). Turkey: Reforming the Health Sector for Improved Access and Efficiency, IBRD, Vol. 1 and 2. Washington D.C.