Does the Risk Assessment and Prediction Tool predict discharge disposition after joint replacement?

Area of Science:

• Orthopedics
• Health Services Research
• Predictive Analytics

Background:

• Cost containment is a priority for healthcare payers and policymakers.
• Early discharge planning is crucial for reducing hospital length of stay and improving financial outcomes.
• Predictive tools for discharge disposition can aid in efficient healthcare resource allocation.

Purpose of the Study:

• To evaluate the predictive accuracy of the Risk Assessment and Prediction Tool (RAPT) in a US population undergoing total hip and knee arthroplasty (THA/TKA).
• To assess the predictive accuracy of individual RAPT scores (ranging from 1-12).

Main Methods:

• Prospective data collection of RAPT scores and discharge disposition for 3213 patients (THA/TKA) between June 2006 and December 2011.
• Utilized a secure database to store RAPT scores and clinical data, queried by nursing case managers.
• Employed binary logistic regression analysis to determine the predictive accuracy of RAPT scores.

Main Results:

• The RAPT demonstrated an overall predictive accuracy of 78% for discharge disposition.
• RAPT scores below 6 (>90% accuracy) predicted inpatient rehabilitation, while scores above 10 (>90% accuracy) predicted discharge home.
• Predictive accuracy was lowest (65.2%) for intermediate scores (7-10), a range encompassing nearly 50% of patients.

Conclusions:

• The RAPT is effective in predicting discharge disposition for high- and low-risk patients following total joint arthroplasty.
• Intermediate-risk patients are identified by RAPT scores of 7-10, suggesting a need for targeted interventions.
• Refining the RAPT with additional factors could enhance predictive accuracy for intermediate-risk patients, optimizing preoperative care planning.