Institutional members access full text with Ovid®

A Novel Risk Calculator Predicts 90-Day Readmission Following Total Joint Arthroplasty

Goltz, Daniel E., MD, MBA1; Ryan, Sean P., MD1; Hopkins, Thomas J., MD, MBA1; Howell, Claire B., BS1; Attarian, David E., MD1; Bolognesi, Michael P., MD1; Seyler, Thorsten M., MD, PhD1

doi: 10.2106/JBJS.18.00843
Scientific Articles
Buy
Disclosures

Background: A reliable prediction tool for 90-day adverse events not only would provide patients with valuable estimates of their individual risk perioperatively, but would also give health-care systems a method to enable them to anticipate and potentially mitigate postoperative complications. Predictive accuracy, however, has been challenging to achieve. We hypothesized that a broad range of patient and procedure characteristics could adequately predict 90-day readmission after total joint arthroplasty (TJA).

Methods: The electronic medical records on 10,155 primary unilateral total hip (4,585, 45%) and knee (5,570, 55%) arthroplasties performed at a single institution from June 2013 to January 2018 were retrospectively reviewed. In addition to 90-day readmission status, >50 candidate predictor variables were extracted from these records with use of structured query language (SQL). These variables included a wide variety of preoperative demographic/social factors, intraoperative metrics, postoperative laboratory results, and the 30 standardized Elixhauser comorbidity variables. The patient cohort was randomly divided into derivation (80%) and validation (20%) cohorts, and backward stepwise elimination identified important factors for subsequent inclusion in a multivariable logistic regression model.

Results: Overall, subsequent 90-day readmission was recorded for 503 cases (5.0%), and parameter selection identified 17 variables for inclusion in a multivariable logistic regression model on the basis of their predictive ability. These included 5 preoperative parameters (American Society of Anesthesiologists [ASA] score, age, operatively treated joint, insurance type, and smoking status), duration of surgery, 2 postoperative laboratory results (hemoglobin and blood-urea-nitrogen [BUN] level), and 9 Elixhauser comorbidities. The regression model demonstrated adequate predictive discrimination for 90-day readmission after TJA (area under the curve [AUC]: 0.7047) and was incorporated into static and dynamic nomograms for interactive visualization of patient risk in a clinical or administrative setting.

Conclusions: A novel risk calculator incorporating a broad range of patient factors adequately predicts the likelihood of 90-day readmission following TJA. Identifying at-risk patients will allow providers to anticipate adverse outcomes and modulate postoperative care accordingly prior to discharge.

Level of Evidence: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

1Department of Orthopaedic Surgery (D.E.G., S.P.R., D.E.A., M.P.B., and T.M.S.), Department of Anesthesiology (T.J.H.), and Performance Services (C.B.H.), Duke University Medical Center, Durham, North Carolina

Investigation performed at Duke University Medical Center, Durham, North Carolina

Disclosure: There was no outside source of funding for this study. On the Disclosure of Potential Conflicts of Interest forms, which are provided with the online version of the article, one or more of the authors checked “yes” to indicate that the author had a relevant financial relationship in the biomedical arena outside the submitted work (http://links.lww.com/JBJS/F93).

Copyright © 2019 by The Journal of Bone and Joint Surgery, Incorporated
You currently do not have access to this article

To access this article: