It's time for CMS to utilize functional assessment as a key quality component.

Area of Science:

• Geriatric Medicine
• Health Services Research
• Rehabilitation Medicine

Background:

• Current risk stratification for hospital readmissions, particularly for Core Measure Conditions, relies heavily on nonmodifiable factors like age, gender, and comorbidities.
• Recent research indicates that validated functional assessments are powerful statistical predictors of hospital readmission.
• The Fitness Index Measure (FIM) is a validated functional assessment tool.

Purpose of the Study:

• To review a study analyzing the Fitness Index Measure (FIM) for predicting hospital readmissions in unilateral hip fractures.
• To advocate for the integration of functional assessment into risk stratification models for hospital readmissions.
• To discuss the broader applicability of functional assessment in evaluating various medical conditions.

Main Methods:

• Analysis of a statistical prediction model using the Fitness Index Measure (FIM) for hospital readmission in unilateral hip fractures.
• Review of existing literature demonstrating the predictive power of functional assessments for hospital readmissions.
• Discussion of the current Centers for Medicare & Medicaid Services (CMS) risk stratification methods.

Main Results:

• The Fitness Index Measure (FIM) shows potential as a statistical predictor for hospital readmissions in unilateral hip fractures.
• Functional assessment, as demonstrated by FIM, offers a more dynamic and potentially modifiable risk factor compared to traditional metrics.
• Evidence suggests functional status is a significant predictor of readmission across various conditions.

Conclusions:

• Functional assessment tools, like the FIM, should be incorporated into risk prediction models for hospital readmissions.
• The Centers for Medicare & Medicaid Services (CMS) should consider utilizing functional assessment data within its Value-Based Purchasing Program.
• Implementing functional assessments can lead to more accurate risk stratification and improved patient outcomes.