The Comprehensive Care for Joint Replacement (CJR) model for total hip arthroplasty (THA) involves a target reimbursement set by the Center for Medicare and Medicaid Services (CMS). Many patients exceed these targets, but predicting risk for incurring these excess costs remains challenging, and we hypothesized that select patient characteristics would adequately predict CJR cost overruns. Demographic factors and comorbidities were retrospectively reviewed in 863 primary unilateral CJR THAs performed between 2013 and 2017 at a single institution. A predictive model was built from 31 validated comorbidities and a base set of 5 patient factors (age, gender, BMI, ASA, marital status). A multivariable logistic regression model was refined to include only parameters predictive of exceeding the target reimbursement level. These were then assigned weights relative to the weakest parameter in the model.Introduction
Methods
