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Related Experiment Video

Updated: May 22, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

[Health-based risk adjustment. Effects and side effects].

R Jahn¹, S Schillo, J Wasem

¹Alfried Krupp von Bohlen und Halbach Stiftungslehrstuhl für Medizinmanagement, Universität Duisburg-Essen, Universitätsstr. 2, 45141, Essen, Deutschland.

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz

|April 25, 2012

Summary

German health insurance now uses health status for risk adjustment, significantly improving accuracy over older demographic methods. This enhances fair competition and incentivizes better chronic care investment.

Related Experiment Videos

Last Updated: May 22, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Area of Science:

Health economics
Social health insurance

Background:

Health systems use competition and risk adjustment to balance plan incentives.
Risk adjustment aims to reduce risk selection and encourage chronic care investment.

Purpose of the Study:

Evaluate the performance of health status-based risk adjustment in German social health insurance.
Compare health-based risk adjustment with previous demographic-based methods.

Main Methods:

Analysis of the first year of health-based risk adjustment data (diagnoses, drug prescriptions) alongside demographic information.
Comparison of performance metrics (R², CPM, MAPE) between old and new risk adjustment formulas.

Main Results:

Health status-based risk adjustment (R² 20.2%, CPM 22.5%, MAPE €1,817) significantly outperformed demographic-based adjustment (R² 5.8%, CPM 10.4%, MAPE €2,226).
The new system demonstrated superior explanatory power and reduced prediction errors.

Conclusions:

Health status-based risk adjustment is a superior mechanism for resource allocation in social health insurance.
Further instruments are needed for health plans to act as prudent buyers to optimize healthcare quality and efficiency.