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
Hip fractures are a common pathology treated by Orthopaedic surgeons. The Comprehensive Care for Joint Replacement (CJR) model utilizes risk stratification to set target prices for these patients undergoing hemiarthroplasty or total hip arthroplasty (THA). We hypothesized that sub-specialty arthroplasty surgeons would be able to treat patients at a lower cost compared to surgeons of other specialties during cases performed while on call. Patients with hemiarthroplasty or THA for hip fractures were retrospectively collected from June, 2013, to May, 2017, from a single tertiary referral center. Demographic information and outcomes based on length of stay (LOS), net payment, and target payment were collected. Patients were then stratified by surgeon subspecialty (arthroplasty trained vs. other specialty). Univariable and multivariable analysis for payment based on treating surgeon was then performed.Introduction
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