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Factors affecting primary health care centers’ economic and production efficiency

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Abstract

Little is known about the efficiency of health centers, despite their central role in primary health care strategy for several countries. This study evaluates the health centers in Greece, and identifies factors impeding the achievement of efficiency, with the aim of determining how their efficiency could be improved. Two alternative conceptual models are used to ensure the consistency of the efficiency results: one model is focusing on production efficiency and the other on economic efficiency. Subsequently a second stage analysis is performed to account for the impact of explanatory variables on efficiency. The use of DEA models alongside with bootstrap techniques allows calculating more accurately the efficiency scores that can reflect the performance of health centers more properly. The main drivers of health centers’ technical efficiency for both conceptual models were the location characteristics, the population growth, the mortality rate and the competition. The scale efficiency of health centers in production model is reflected by the size of their respective covered populations, the location characteristics and the mortality rate while the economic model is affected by their size, the location characteristics and the percentage of population working in agriculture. Determining how these variables influence on efficiency is essential for determining performance improvement strategies.

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Notes

  1. For a comparative analysis of the Stochastic Frontier Approach, i.e. the main parametric method and DEA see Coelli et al. (2005).

  2. Simar and Wilson (2007) in their paper proved that the currently, until then, method of Tobit regression was inappropriate for the estimation of technical efficiency scores. They proposed the use of truncates regression with bootstrap.

  3. It is well known that DEA analysis is sensitive to variable selection. Furthermore, as the number of inputs increases the ability to discriminate between the DMUs decreases. The more variables are added the greater becomes the chance that some inefficient unit dominates in the added dimension and becomes efficient.

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Acknowledgments

This research has been co-funded by the European Union (European Social Fund) and Greek national resources under the framework of the ‘Archimedes III’ project of the ‘Education and Lifelong Learning’ Operational Programme.

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Authors and Affiliations

  1. Department of Business Administration, Technological Educational Institute of Western Greece, 26500, Patras, Greece

    Panagiotis Mitropoulos & Ioannis Mitropoulos

  2. Department of Economics, University of Patras, 26334, Patras, Greece

    Kostas Kounetas

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  1. Panagiotis Mitropoulos
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  2. Kostas Kounetas
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  3. Ioannis Mitropoulos
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Correspondence to Panagiotis Mitropoulos.

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Mitropoulos, P., Kounetas, K. & Mitropoulos, I. Factors affecting primary health care centers’ economic and production efficiency. Ann Oper Res 247, 807–822 (2016). https://doi.org/10.1007/s10479-015-2056-5

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