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Errors in survey based quality evaluation variables in efficiency models of primary care physicians

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  • Kjoeserud,G.G.
  • Kvamme,O.J.
  • Kittelsen,S.A.C.

    (University of Oslo, Department of Economics)

Abstract

Efficiency analyses in the health care sector are often criticised for not incorporating quality variables. The definition of quality of primary health care has many aspects, and it is inevitably also a question of the patients’ perception of the services received. This paper uses variables derived from patient evaluation surveys as measures of the quality of the production of health care services. It uses statistical tests to judge if such measures have a significant impact on the use of resources in various Data Envelopment Analysis (DEA) models. As the use of survey data implies that the quality variables are measured with error, the assumptions underlying a DEA model are not strictly fulfilled. This paper focuses on ways of correcting for biases that might result from the violation of selected assumptions. Firstly, any selection bias in the patient mix of each physician is controlled for by regressing the patient evaluation responses on the patient characteristics. The corrected quality evaluation variables are entered as outputs in the DEA model, and model specification tests indicate that out of 25 different quality variables, only waiting time has a systematic impact on the efficiency results. Secondly, the effect on the efficiency estimates of the remaining sampling error in the patient sample for each physician is accounted for by constructing confidence intervals based on resampling. Finally, as an alternative approach to including the quality variables in the DEA model, a regression model finds different variables significant, but not always with a trade-of between quality and quantity.

(This abstract was borrowed from another version of this item.)

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File URL: http://www.sv.uio.no/econ/english/research/unpublished-works/working-papers/pdf-files/2001/Memo-24-2001.pdf
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Bibliographic Info

Paper provided by Oslo University, Department of Economics in its series Memorandum with number 24/2001.

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Date of creation: 2001
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Handle: RePEc:hhs:osloec:2001_024

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Postal: Department of Economics, University of Oslo, P.O Box 1095 Blindern, N-0317 Oslo, Norway
Phone: 22 85 51 27
Fax: 22 85 50 35
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Web page: http://www.oekonomi.uio.no/indexe.html
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Keywords: data envelopment analysis;

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References

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  1. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
  2. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
  3. Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
  4. KNEIP, Alois & PARK, Byeong U. & SIMAR, Léopold, 1996. "A Note on the Convergence of Nonparametric DEA Efficiency Measures," CORE Discussion Papers 1996039, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  5. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
  6. SIMAR , Léopold, 1995. "Aspects of Statistical Analysis in DEA-Type Frontier Models," CORE Discussion Papers 1995061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  7. Kittelsen,S.A.C., 1999. "Monte Carlo simulations of DEA efficiency measures and hypothesis tests," Memorandum 09/1999, Oslo University, Department of Economics.
  8. repec:fth:louvco:9639 is not listed on IDEAS
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