The Netherlands relies on risk equalization to compensate competing health insurers for predictable variation in individual medical expenses. Without accurate risk equalization insurers are confronted with incentives for risk selection. The goal of this study is to evaluate the improvement in predictive accuracy of the Dutch risk equalization model since its introduction in 1993. Based on individual-level claims data (n = 15.6 million), we estimate the risk equalization models that have been successively applied in The Netherlands since 1993. Using individual-level survey data (n = 8735), we examine the average under-/overcompensation by these models for several relevant subgroups in the population. We find that in the course of years, the risk equalization model has been substantially improved. Even the current model (2012), however, does not eliminate incentives for risk selection completely. To achieve the public objectives, further improvement of the Dutch risk equalization model is crucial.

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State-of-the-art risk equalization models undercompensate some risk groups and overcompensate others, leaving systematic incentives for risk selection. A natural approach to reducing the under- or overcompensation for a particular group is enriching the risk equalization model with risk adjustor variables that indicate membership in that group. For some groups, however, appropriate risk adjustor variables may not (yet) be available. For these situations, this paper proposes an alternative approach to reducing under- or overcompensation: constraining the estimated coefficients of the risk equalization model such that the under- or overcompensation for a group of interest equals a fixed amount. We show that, compared to ordinary least-squares, constrained regressions can reduce under/overcompensation for some groups but increase under/overcompensation for others. In order to quantify this trade-off two fundamental questions need to be answered: “Which groups are relevant in terms of risk selection actions?” and “What is the relative importance of under- and overcompensation for these groups?” By making assumptions on these aspects we empirically evaluate a particular set of constraints using individual-level data from the Netherlands (N = 16.5 million). We find that the benefits of introducing constraints in terms of reduced under/overcompensations for some groups can be worth the costs in terms of increased under/overcompensations for others. Constrained regressions add a tool for developing risk equalization models that can improve the overall economic performance of health plan payment schemes.

Experience in European health insurance exchanges indicates that even with the best risk-adjustment formulas, insurers have substantial incentives to engage in risk selection. The potentially most worrisome form of risk selection is skimping on the quality of care for underpriced high-cost patients--that is, patients for whom insurers are compensated at a rate lower than the predicted health care expenses of these patients. In this article we draw lessons for the United States from twenty years of experience with health insurance exchanges in Europe, where risk selection is a serious problem. Mistakes by European legislators and inadequate evaluation criteria for risk selection incentives are discussed, as well as strategies to reduce risk selection and the complex trade-off among selection (through quality skimping), efficiency, and affordability. Recommended improvements to the risk-adjustment process in the United States include considering the adoption of risk adjusters used in Europe, investing in the collection of data, using a permanent form of risk sharing, and replacing the current premium "band" restrictions with more flexible restrictions. Policy makers need to understand the complexities of regulating competitive health insurance markets and to prevent risk selection that threatens the provision of good-quality care for underpriced high-cost patients.

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This article analyzes selection incentives for insurers in the Dutch basic health insurance market, which operates with community-rated premiums and sophisticated risk adjustment. Selection incentives result from the interplay of three market characteristics: possible actions by insurers, consumer response to these actions, and predictable variation in profitability of insurance contracts. After a qualitative analysis of the first two characteristics our primary objective is to identify the third. Using a combination of claims data (N = 16.8 million) and survey information (N = 387,195), we find substantial predictable variation in profitability. On average, people in good health are profitable, while those in poor health are unprofitable. We conclude that Dutch insurers indeed face selection incentives. A complete measure of selection incentives, however, captures the correlation between individual-level profitability and consumer response to insurer-actions. Obtaining insight in this correlation is an important direction for further research.

for comments on a previous draft. We gratefully acknowledge the Dutch Ministry of Health and the Association of Health Insurers for providing access to the administrative data. The authors are solely responsible for the analyses and conclusions. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.