PhD defence M. (Michel) Oskam

Below is a brief summary of the dissertation:

Health insurance systems with regulated competition aim to ensure affordable access to health care while encouraging insurers to compete on the quality and efficiency of contracted health services. However, if insurers are mandated to charge the same premium for people with different expected health needs - and therefore costs - financial incentives arise for insurers to engage in strategic selection of their enrollees. The resulting actions can threaten solidarity, equitable access to high-quality health care, and fair competition.

Risk equalization seeks to reduce the incentives for such risk selection by compensating insurers for predictable differences in health care spending of individuals. Although the econometric risk equalization models have become increasingly sophisticated, important undercompensations remain, particularly for individuals with chronic conditions.

This dissertation examines how risk equalization can be better evaluated and improved to reduce incentives for risk selection. It introduces new methods to assess selection incentives using large-scale health data, providing fresh insights into the performance of current risk equalization models. It also investigates and empirically tests different strategies to further reduce selection incentives. These range from adjustments to the model itself to innovative solutions investigating both risk sharing between insurers and the relaxation of premium rate restrictions.

The central conclusion is that reducing incentives for risk selection requires a continuous combination of evaluation, further development of risk equalization, and complementary policy instruments. In this way, regulated competition can better contribute to a health insurance market in which solidarity and efficiency are kept in balance.