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Measuring technical efficiency in primary health care: the effect of exogenous variables on results.

Journal of medical systems·2010
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Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care
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Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Published on: February 16, 2011

Technical efficiency in primary health care: does quality matter?

Luis R Murillo-Zamorano1, Carmelo Petraglia

  • 1Department of Economics, University of Extremadura, Avenida de Elvas s/n, 06071, Badajoz, Spain. lmurillo@unex.es

The European Journal of Health Economics : HEPAC : Health Economics in Prevention and Care
|March 23, 2010
PubMed
Summary

Measuring healthcare output accurately is crucial. Accounting for service quality in primary health care efficiency analysis significantly alters results, revealing lower average efficiency and higher dispersion among centers.

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Last Updated: Jun 14, 2026

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care
14:32

Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care

Published on: February 16, 2011

Area of Science:

  • Health Services Research
  • Healthcare Management
  • Health Economics

Background:

  • Empirical research on primary health care efficiency often overlooks accurate output measurement.
  • The quality of healthcare services is a critical but under-addressed factor in efficiency studies.

Purpose of the Study:

  • To investigate the impact of incorporating service quality into output measurement on primary care efficiency analysis.
  • To assess the effects of quality-adjusted output on efficiency metrics and rankings.

Main Methods:

  • Utilized a novel database (APEX06) for the Extremadura region, Spain.
  • Developed synthetic measures of primary care output considering both quantity and quality of services.
  • Analyzed efficiency for 85 primary care centers (PCCs) in 2006.

Main Results:

  • Neglecting service quality in output measurement can lead to misleading efficiency results.
  • Adjusting for quality revealed that inefficiency explains more deviation from potential output.
  • Average technical efficiency decreased, while dispersion among PCCs increased significantly.
  • The ranking of primary care centers based on efficiency was substantially altered.

Conclusions:

  • Accurate measurement of healthcare output, including quality, is essential for reliable efficiency analysis.
  • Quality-adjusted efficiency metrics provide a more accurate picture of primary care performance.
  • Failure to account for quality can misrepresent the relative efficiency of healthcare providers.