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Related Experiment Videos

Risk adjustment methods can affect perceptions of outcomes

L I Iezzoni1, M Shwartz, A S Ash

  • 1Department of Medicine, Harvard Medical School, Beth Israel Hospital, Boston, MA 02215.

American Journal of Medical Quality : the Official Journal of the American College of Medical Quality
|January 1, 1994
PubMed
Summary

Patient risk adjustment is crucial for comparing medical care outcomes. Different severity measures significantly alter outcome perceptions, impacting subgroup analyses and payer assessments.

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Area of Science:

  • Health Services Research
  • Medical Informatics
  • Health Outcomes

Background:

  • Accurate comparison of medical care outcomes necessitates adjusting for patient risk, particularly illness severity.
  • Existing severity measures vary, potentially leading to divergent perceptions of patient outcomes.
  • The choice of severity assessment method can influence the interpretation of comparative effectiveness.

Purpose of the Study:

  • To demonstrate how different patient severity adjustment approaches can dramatically alter comparisons of healthcare outcomes across patient subgroups.
  • To evaluate the impact of two distinct severity measurement models on outcome expectations for different payer groups.

Main Methods:

  • Two patient severity adjustment models were employed: Model 1 utilized the admission MedisGroups score.

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  • Model 2 was derived from patient age and 12 chronic conditions identified via diagnosis codes.
  • Model performance was assessed using R-squared and C statistics for predicting in-hospital death.

    • Main Results:

    • Despite Model 1 showing superior predictive performance (R-squared, C-statistic) for in-hospital death, Model 2 yielded more accurate subgroup expectations.
    • Severity adjustment using Model 1 indicated Medicare patients fared worse than expected and Medicaid patients better.
    • Conversely, Model 2 suggested Medicare patients performed as expected, while Medicaid patients had poorer outcomes than anticipated.

    Conclusions:

    • The selection of a patient severity adjustment methodology significantly impacts the assessment of healthcare outcomes across different patient populations.
    • Standard performance metrics may not fully capture the accuracy of severity models for subgroup analyses.
    • Careful consideration of the chosen severity measure is essential for reliable healthcare quality comparisons and policy implications.