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Cost and technical efficiency of physician practices: a stochastic frontier approach using panel data

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  • Mareike Heimeshoff
  • Jonas Schreyögg
  • Lukas Kwietniewski

Abstract

This is the first study to use stochastic frontier analysis to estimate both the technical and cost efficiency of physician practices. The analysis is based on panel data from 3,126 physician practices for the years 2006 through 2008. We specified the technical and cost frontiers as translog function, using the one-step approach of Battese and Coelli to detect factors that influence the efficiency of general practitioners and specialists. Variables that were not analyzed previously in this context (e.g., the degree of practice specialization) and a range of control variables such as a patients’ case-mix were included in the estimation. Our results suggest that it is important to investigate both technical and cost efficiency, as results may depend on the type of efficiency analyzed. For example, the technical efficiency of group practices was significantly higher than that of solo practices, whereas the results for cost efficiency differed. This may be due to indivisibilities in expensive technical equipment, which can lead to different types of health care services being provided by different practice types (i.e., with group practices using more expensive inputs, leading to higher costs per case despite these practices being technically more efficient). Other practice characteristics such as participation in disease management programs show the same impact throughout both cost and technical efficiency: participation in disease management programs led to an increase in both, technical and cost efficiency, and may also have had positive effects on the quality of care. Future studies should take quality-related issues into account. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Mareike Heimeshoff & Jonas Schreyögg & Lukas Kwietniewski, 2014. "Cost and technical efficiency of physician practices: a stochastic frontier approach using panel data," Health Care Management Science, Springer, vol. 17(2), pages 150-161, June.
    • Handle: RePEc:kap:hcarem:v:17:y:2014:i:2:p:150-161
    DOI: 10.1007/s10729-013-9260-0
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