Risk Adjustment for Dually Eligible Beneficiaries Using Long-Term Care

Area of Science:

• Health Services Research
• Medical Economics
• Gerontology

Background:

• Accurate risk adjustment is crucial for managing healthcare costs in vulnerable populations.
• Dual-eligible beneficiaries with chronic long-term care needs present unique challenges for existing risk adjustment models.
• Principal Inpatient Diagnostic Cost Groups (PIPDCG) and Hierarchical Coexisting Conditions (HCC) are common risk adjustment methodologies.

Purpose of the Study:

• To evaluate the predictive accuracy of PIPDCG and HCC risk adjustment models for dually eligible beneficiaries in long-term care (LTC).
• To assess the impact of incorporating functional status and other variables on the predictive power of these models.

Main Methods:

• Comparative analysis of PIPDCG and HCC models.
• Risk adjustment methodology applied to a population of dually eligible beneficiaries receiving chronic LTC.
• Inclusion of functional status measures and placement data to evaluate their impact on predictive accuracy.

Main Results:

• PIPDCG models showed similar predictive accuracy for the LTC population compared to the total Medicare population.
• HCC models demonstrated somewhat smaller predictive accuracy for the LTC population.
• Incorporating functional status marginally increased R-squared for Medicare expenditures but more significantly for total expenditures.
• Addition of variables like placement substantially improved predictive power.

Conclusions:

• PIPDCG and HCC methodologies have varying predictive performance for dually eligible LTC populations.
• Functional status and placement are important predictors that can enhance risk adjustment models for this demographic.
• Further refinement of risk adjustment models is needed to accurately capture the complexity of care for LTC beneficiaries.