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Spatial risk adjustment between health insurances: using GWR in risk adjustment models to conserve incentives for service optimisation and reduce MAUP

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  • Danny Wende

    (Wissenschaftliches Institut für Gesundheitsökonomie und Gesundheitssystemforschung (WIG2 GmbH))

Abstract

This paper presents a new approach to deal with spatial inequalities in risk adjustment between health insurances. The shortcomings of non-spatial and spatial fixed effects in risk adjustment models are analysed and opposed against spatial kernel estimators. Theoretical and empirical evidence suggests that a reasonable choice of the spatial kernel could limit the spatial uncertainty of the modifiable area unit problem under heavy-tailed claims data, leading to more precise predictions and economically positive incentives on the healthcare market. A case study of the German risk adjustment shows a spatial risk spread of 86 Euro p.c., leading to incentives for spatial risk selection. The proposed estimator eliminates this issue and conserves incentives for services optimisation.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:eujhec:v:20:y:2019:i:7:d:10.1007_s10198-019-01079-6
    DOI: 10.1007/s10198-019-01079-6
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    More about this item

    Keywords

    Health insurance; Health care utilisation; Risk adjustment; Geographic variations; Germany;
    All these keywords.

    JEL classification:

    • H5 - Public Economics - - National Government Expenditures and Related Policies
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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