ArticleThe European journal of health economics : HEPAC : health economics in prevention and care2019
Spatial risk adjustment between health insurances: using GWR in risk adjustment models to conserve incentives for service optimisation and reduce MAUP.
Article in The European journal of health economics : HEPAC : health economics in prevention and care, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Deprivation as a fundamental cause of morbidity and reduced life expectancy: an observational study using German statutory health insurance data.International journal of health economics and management · 2024Observational
- Beyond Usual Geographical Scales of Analysis: Implications for Healthcare Management and Urban Planning.Portuguese journal of public health · 2023Article
- Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China.PloS one · 2021Article
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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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