4.6 Article

Can We Predict Discharge Status After Total Joint Arthroplasty? A Calculator to Predict Home Discharge

Journal

JOURNAL OF ARTHROPLASTY
Volume 31, Issue 12, Pages 2705-2709

Publisher

CHURCHILL LIVINGSTONE INC MEDICAL PUBLISHERS
DOI: 10.1016/j.arth.2016.08.010

Keywords

total hip arthroplasty; total knee arthroplasty; total joint arthroplasty; skilled nursing facility; discharge status; calculator

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Background: Postoperative discharge to a skilled nursing facility after total joint arthroplasty (TJA) is associated with increased costs, complications, and readmission. The purpose of this study was to identify the risk factors for discharge to a location other than home to build a calculator to predict discharge disposition after TJA. Methods: The American College of Surgeons National Surgical Quality Improvement Program database was queried from 2011 to 2013 to identify patients who underwent primary total hip or total knee arthroplasty. Risk factors were compared between patients discharging home vs a facility. Predictors of facility discharge were converted to discrete values to develop a simple numerical calculator. Results: After primary TJA, patients discharged to a facility were typically older (70.9 vs 64.3, P <.001), female (69.5% vs 55.7%, P <.001), had an elevated American Society of Anesthesiologist (ASA) class, and were more likely to be functionally dependent before surgery (3.8% vs 1.1%, P <.001). Patient age, preoperative functional status, nonelective THA for hip fracture, and ASA class were most predictive of facility discharge. After development of a predictive model, scores exceeding 40 and 80 points resulted in a facility discharge probability of 75% and 99%, respectively. Conclusion: In patients undergoing TJA, advanced age, elevated ASA class, and functionally dependent status before surgery strongly predicted facility discharge. Given that facility discharge imposes a significant cost and morbidity burden after TJA, patients, surgeons, and hospitals may use this simple calculator to target this susceptible patient population. (C) 2016 Elsevier Inc. All rights reserved.

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