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Health insurance markets with community‐rated premiums typically include risk adjustment (RA) to mitigate selection problems. Over the past decades, RA systems have evolved from simple demographic models to sophisticated morbidity‐based models. Even the most sophisticated models, however, tend to overcompensate people with persistently low spending and undercompensate those with persistently high spending. This paper compares three methods that exploit spending‐level persistence for improving health plan payment systems: (1) implementation of spending‐based risk adjustors, (2) implementation of high‐risk pooling for people with multiple‐year high spending, and (3) indirect use of spending persistence via constrained regression. Based on incentive measures for risk selection and cost control, we conclude that a combination of the last two options can substantially outperform the first, which is currently used in the health plan payment system in the Netherlands.

How to deal with persistently low/high spenders in health plan payment systems?