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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

Danny Wende ()
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Danny Wende: Wissenschaftliches Institut für Gesundheitsökonomie und Gesundheitssystemforschung (WIG2 GmbH)

The European Journal of Health Economics, 2019, vol. 20, issue 7, No 10, 1079-1091

Abstract: 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.

Keywords: Health insurance; Health care utilisation; Risk adjustment; Geographic variations; Germany (search for similar items in EconPapers)
JEL-codes: H5 I18 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10198-019-01079-6

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