Improving Orthopedic Patient Outcomes: A Model to Predict 30-Day and 90-Day Readmission Rates Following Total Joint Arthroplasty

Background: Over the next 10-15 years, there is expected to be an exponential increase in the number of total joint arthroplasties in the American population. This, combined with rising costs of total joint arthroplasty and more recent changes to the reimbursement payment models, increases the demand to perform quality, cost-effective total joint arthroplasties. The purpose of this study is to build models that could be used to estimate the 30-day and 90-day readmission rates for patients undergoing total joint arthroplasty. Methods: A retrospective review of patients admitted to a single hospital, over the course of 56 months, for total joint arthroplasty was performed. The goal is to identify patients with readmission in a 30-day or 90-day period following discharge from the hospital. Binary logistic regression was used to build predictive models that estimate the likelihood of readmission based on a patient's risk factors. Results: Of 5732 patients identified for this study, 237 were readmitted within 30 days, while 547 were readmitted within 90 days. Age, body mass index, gender, discharge disposition, occurrence of cardiac dysrhythmias and heart failure, emergency department visits, psychiatric diagnoses, and medication counts were all found to be associated with 30-day admission rates. Similar associations were found at 90 days, with the exclusion of age and psychiatric drug use, and the inclusion of intravenous drug abuse, narcotic medications, and total joint arthroplasty within 12 months. Conclusion: There are patient variables, or risk factors, that serve to predict the likelihood of readmission following total joint arthroplasty. (C) 2019 Elsevier Inc. All rights reserved.