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The contribution of locational factors to regional variations in office-based physicians in Germany

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  • Vogt, Verena

Abstract

There is considerable literature showing that regional variation in the number of office-based physicians is rather explained by factors such as financial attractiveness of a region or employment opportunities for spouses than by health care needs of the population. It remains unclear, however, how much of the variation is explained by each of these determinants. The aim of the present study is to estimate the percentage contribution of a variety of determinants to the measured variation in Germany. Physician density is regressed on a well-defined set of explanatory variables that were identified as determinants of physician location. Regression-based decomposition was applied to decompose the variation in physician density into the percentage contribution of each of the determinants. The results show that varying health care needs of the population explained less than 5.2% of the variation in physician density. Percentage of population with private health insurance explained 14% of the variation in GP density and between 2% and 6% of the variation in specialists’ density. For specialists, a higher share of variance was attributable to the variables measuring sociocultural amenities of a region compared to GPs.

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  • Vogt, Verena, 2016. "The contribution of locational factors to regional variations in office-based physicians in Germany," Health Policy, Elsevier, vol. 120(2), pages 198-204.
    • Handle: RePEc:eee:hepoli:v:120:y:2016:i:2:p:198-204
    DOI: 10.1016/j.healthpol.2016.01.006
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    References listed on IDEAS

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    Cited by:

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    2. Kuhn, Michael & Ochsen, Carsten, 2019. "Population change and the regional distribution of physicians," The Journal of the Economics of Ageing, Elsevier, vol. 14(C).
    3. Wende, Danny & Kopetsch, Thomas & Richter, Wolfram F., 2020. "Planning health care capacities with a gravity equation," Ruhr Economic Papers 888, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    4. Danny Wende, 2019. "Spatial risk adjustment between health insurances: using GWR in risk adjustment models to conserve incentives for service optimisation and reduce MAUP," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(7), pages 1079-1091, September.

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