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Spatial risk adjustment between health insurances: using GWR in risk adjustment models to conserve incentives for
1Wissenschaftliches Institut für Gesundheitsökonomie und Gesundheitssystemforschung (WIG2 GmbH), Markt 8, 04109, Leipzig, Germany. danny.wende@wig2.de.
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.
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