Using the Stratum-Specific Likelihood Ratio Method to Derive Outcome-Based Hospital Volume Categories for Total Knee Replacement

Abstract

Background: Evidence of higher hospital volume being associated with improved outcomes for patients undergoing total knee replacement (TKR) is mostly based on arbitrary distribution-based thresholds. Objective: We aimed to define outcome-based volume thresholds using data from a national database. Methods: We used the MedPAR Limited Data Set inpatient data from 2010-2015 to identify patients who had undergone primary TKR. Surgical and TKR specific complications occurring within the index hospitalization and all-cause readmission within 90 days were considered adverse events. We derived an average annual TKR case volume for each hospital and applied the stratum-specific likelihood ratio method to determine volume categories indicative of a similar likelihood of 90-day post-operative complications. Hierarchical multivariable logistic regression with a random intercept for hospital nested within study year and adjusted for patient and hospital characteristics was performed to determine if these volume thresholds were still associated with the odds of 90-day readmission for complications after adjustment. Results: SSLR analysis yielded 4 hospital volume categories based on the likelihood of 90-day postoperative complications: 1–31 (low), 32–127 (medium), 128–248 (high), and 429+ (very high) TKRs performed per year. The results of the hierarchical multivariable logistic regression showed significantly increased odds of 90-day complications at lower volume categories. Sensitivity analyses confirmed our main findings. Conclusions: This study is the first to provide national-level volume categories that are evidence-based. Publicizing these thresholds may enhance quality measures available to patients, providers, and payors.