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Exploration of using constrained regression in Germany's morbidity-based risk adjustment
Florian Renker1, Dennis Häckl2, Amelie Wuppermann3
1SBK Siemens-Betriebskrankenkasse, Munich, Germany. Florian.Renker@SBK.org.
Summary
Constrained regression can improve German health insurance risk adjustment by reducing under- and overcompensation for specific enrollee groups. Partial elimination of these compensation issues shows promise for better model fit.
Area of Science:
- Health economics
- Insurance mathematics
- Statistical modeling
Background:
- Risk adjustment schemes aim to equitably compensate health plans for enrollee healthcare costs.
- Current schemes often result in significant under- or overcompensation for certain enrollee populations.
- Some enrollee groups cannot be directly included in risk adjustment due to unobserved status.
Purpose of the Study:
- To explore the application of constrained regression in the German morbidity-based risk adjustment scheme.
- To assess the potential of constrained regression to mitigate under-/overcompensation issues.
- To evaluate the impact of partial versus full constraint elimination on model performance.
Main Methods:
- Application of constrained regression techniques to the German risk adjustment model.
- Analysis of technical feasibility and performance improvements.
- Comparison of different constraint levels for addressing under-/overcompensation.
Main Results:
- Constrained regression is technically feasible within the German risk adjustment system.
- The method shows potential to improve overall under-/overcompensation compared to the current base model.
- Partial elimination of under-/overcompensation through constraints may enhance individual model fit.
Conclusions:
- Constrained regression offers a viable approach to refine the German risk adjustment scheme.
- The effectiveness of constrained regression is particularly noted when aiming for partial rather than full compensation adjustments.
- Further policy discussions are necessary regarding the inclusion criteria for groups in the overall compensation measure.
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