Overpaying morbidity adjusters in risk equalization models.

Area of Science:

• Health Economics
• Social Health Insurance
• Risk Management

Background:

• Competitive social health insurance markets utilize risk equalization to manage healthcare expense variations.
• Existing risk equalization models, even with advanced morbidity adjusters, often undercompensate insurers for high-risk individuals.
• This undercompensation, coupled with premium regulation, creates incentives for risk selection among consumers and insurers.

Purpose of the Study:

• To propose a method to reduce risk selection incentives in social health insurance.
• To address the undercompensation of high-risk individuals by modifying existing risk equalization mechanisms.
• To explore the potential of 'overpaying' morbidity adjusters within risk equalization models.

Main Methods:

• The study proposes overpaying morbidity adjusters already incorporated into the risk equalization model.
• The concept is illustrated by merging morbidity adjuster data, healthcare expenses, and health survey information.
• Three preconditions for the meaningful application of this 'overpaying' strategy are derived.

Main Results:

• The proposed method aims to mitigate undercompensation for specific high-risk groups.
• Merging diverse datasets provides a basis for evaluating the proposed adjustment.
• The findings suggest that 'overpaying' may be particularly effective for pharmacy-based cost groups.

Conclusions:

• Overpaying existing morbidity adjusters is a potential strategy to reduce risk selection in social health insurance.
• The effectiveness of this approach depends on specific preconditions related to data and model application.
• Pharmacy-based cost groups represent a promising area for the implementation of this 'overpaying' strategy.