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Measuring Performance in Primary Care: Econometric Analysis and DEA

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  • Antonio Giuffrida
  • Hugh Gravelle

Abstract

We use data from the Health Service Indicators database to compare different methods of measuring the performance of English Family Health Services Authorities (FHSAs) in providing primary care. A variety of regression and data envelopment analysis methods are compared as summary efficiency measures of individual FHSA performance. The correlation of the rankings of FHSAs across DEA and regression methods, across two years of data and across three different specifications of the technology of primary care are examined. Efficiency scores are highly correlated within variants of the two methods, and across years for a given method. Inter method correlations are smaller and correlations across different specifications of the primary care production process are negligible and sometime negative.

Suggested Citation

  • Antonio Giuffrida & Hugh Gravelle, "undated". "Measuring Performance in Primary Care: Econometric Analysis and DEA," Discussion Papers 99/36, Department of Economics, University of York.
  • Handle: RePEc:yor:yorken:99/36
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    References listed on IDEAS

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    1. Giuffrida, Antonio & Gravelle, Hugh & Sutton, Matthew, 2000. "Efficiency and administrative costs in primary care," Journal of Health Economics, Elsevier, vol. 19(6), pages 983-1006, November.
    2. David Whynes & Darrin Baines & Keith Tolley, 1997. "Prescribing costs in UK general practice: the impact of hard budget constraints," Applied Economics, Taylor & Francis Journals, vol. 29(3), pages 393-399.
    3. Bruce Hollingsworth & P.J. Dawson & N. Maniadakis, 1999. "Efficiency measurement of health care: a review of non‐parametric methods and applications," Health Care Management Science, Springer, vol. 2(3), pages 161-172, July.
    4. Henry Tulkens & Philippe Eeckaut, 2006. "Nonparametric Efficiency, Progress and Regress Measures For Panel Data: Methodological Aspects," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 395-429, Springer.
    5. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 1993. "The Measurement of Productive Efficiency: Techniques and Applications," OUP Catalogue, Oxford University Press, number 9780195072181.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    8. Vinod, H. D., 1976. "Canonical ridge and econometrics of joint production," Journal of Econometrics, Elsevier, vol. 4(2), pages 147-166, May.
    9. Peter Smith, 1997. "Model misspecification in Data Envelopment Analysis," Annals of Operations Research, Springer, vol. 73(0), pages 233-252, October.
    10. Yasar Ozcan, 1998. "Physician benchmarking: measuring variation in practice behavior in treatment of otitis media," Health Care Management Science, Springer, vol. 1(1), pages 5-17, September.
    11. Antonio Giuffrida & Hugh Gravelle & Martin Rowland, 1998. "Performance indicators for primary care management in the NHS," Working Papers 160chedp, Centre for Health Economics, University of York.
    12. Miika Linna, 1998. "Measuring hospital cost efficiency with panel data models," Health Economics, John Wiley & Sons, Ltd., vol. 7(5), pages 415-427, August.
    13. Banker, Rajiv D. & Gadh, Vandana M. & Gorr, Wilpen L., 1993. "A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 67(3), pages 332-343, June.
    14. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    15. Thanassoulis, E. & Boussofiane, A. & Dyson, R. G., 1996. "A comparison of data envelopment analysis and ratio analysis as tools for performance assessment," Omega, Elsevier, vol. 24(3), pages 229-244, June.
    16. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    17. Jon Chilingerian & H. David Sherman, 1997. "DEA and primary care physician report cards: Deriving preferred practice cones from managed care service concepts and operating strategies," Annals of Operations Research, Springer, vol. 73(0), pages 35-66, October.
    18. Peter Smith, 1990. "The Use of Performance Indicators in the Public Sector," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 153(1), pages 53-72, January.
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    More about this item

    Keywords

    primary care; efficiency measurement; DEA; stochastic frontier.;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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