Adjusting Population Risk for Functional Health Status

Area of Science:

• Health Services Research
• Medical Informatics
• Public Health

Background:

• Risk adjustment is crucial for managed care, preventing biased performance reporting.
• Functional health status is often excluded but vital for complex patients.
• Current risk adjustment methods may not fully capture patient complexity.

Purpose of the Study:

• To develop and validate a functional health status module for Medicare risk adjustment.
• To assess the impact of incorporating functional health on risk adjustment model accuracy.
• To explore the potential for improved resource allocation through enhanced risk adjustment.

Main Methods:

• Created a standardized functional health measure from three Medicare assessment instruments.
• Developed a 9-group functional health classification model based on self-care, mobility, incontinence, and cognition.
• Integrated the functional health module with the Clinical Risk Groups (CRGs) classification system.
• Validated the augmented model using 2010-2011 Medicare claims data.

Main Results:

• The functional health module improved the R-squared statistic (model fit) by 5% across all Medicare enrollees.
• Complex, nonlinear interactions were observed across functional health domains.
• The augmented model demonstrated enhanced accuracy in predicting enrollee costs.

Conclusions:

• Incorporating functional health status significantly improves Medicare risk adjustment.
• Careful handling of functional health data is essential due to complex interactions.
• This approach offers potential for more equitable resource allocation in healthcare financing.