Predicting Patient Discharge Disposition After Total Joint Arthroplasty in the United States

Abstract

The purpose of this study was to develop an easily administered tool to preoperatively predict patient discharge disposition after total joint arthroplasty in the United States. Data were collected in a retrospective review of 517 medical charts and analyzed using logistic regression to develop a model for predicting the likelihood that a patient will not be discharged directly home. The resulting regression model was the basis for the nomogram, named the Predicting Location after Arthroplasty Nomogram. This model demonstrated a bootstrap-corrected concordance index of 0.867, excellent calibration, and external validation as demonstrated by a concordance index of 0.861. Preoperative knowledge that a patient is likely to require an extended care facility allows the clinical care team to make appropriate arrangements and avoid potential delays in patient discharge.