POS0285\u2005ARE RACIAL DISPARITIES IN REVISION TKA OUTCOMES ASSOCIATED WITH HOSPITAL OR SURGEON VOLUME?

Abstract

Total knee arthroplasty (TKA) outcomes are linked to surgical volume,1 despite the increase in TKA utilization, racial disparities in TKA outcomes persist. Blacks in the US are at a higher risk of aseptic revision of TKA (R-TKA) when compared to Whites, yet the reasons for this are not understood.The objective of this study is to examine the relationship between hospital and surgeon annual TKA volume and R-TKA outcomes by race.This is an observational cohort study. New York Statewide Planning and Research Cooperative System data for 2004 – 2013 was used to identify patients who underwent primary TKA. Data through 2015 was used to identify R-TKA within 2 years of the index TKA. Hospital characteristics were obtained from the AHA Annual Survey. Surgeon data was collected from New York State Education Department and New York State Physician Profile. Surgeon annual TKA volume was categorized based on cutoffs established by Wilson et al1 as </=12, 13-59, 60-145 or >/= 146, and hospital TKA volume as </=89, 90-235, 236-644 and >/=645. We calculated the odds of R-TKA in Whites and Blacks separately and generated crude odds ratios (OR) comparing Blacks to Whites to examine trends across volume categories. A multivariable logistic regression model adjusted for known R-TKA risk factors was also performed.A total of 163,576 patients were included. Mean (SD) age was 66.4 (10.4) years, 107,233 (65.6%) were female, 124,277 (76.6%) were White and 15,990 (9.8%) were Black. 2925 patients underwent aseptic R-TKA. In logistic regression analysis, Blacks had a higher risk of R-TKA (OR 1.42, 95%CI 1.26-1.6) (Table 1). Risk of R-TKA was also higher when surgeon annual volume was </=12 (OR 1.5, 95%CI 1.25-1.8) or 13-59 (OR 1.16, 95%CI 1.04-1.29) TKA compared to the highest volume surgeons (>/=146). Patients who had surgery at a hospital with annual volume of 236-634 TKA were less likely to undergo R-TKA compared to the highest volume hospitals (>/=645) (OR 0.88, 95%CI 0.79-0.98). Other risk factors for R-TKA were younger age and worker’s compensation, while patients with inflammatory arthritis had a lower risk. Figures 1A and 1B show the odds of R-TKA in Whites and Blacks, respectively, by hospital and surgeon volume. Figure 1C shows the crude OR for Blacks to Whites for each category pair. The OR ranged from 0.9 to 2.5, with the largest disparity found in patients who have TKA performed by surgeons with 60-145 annual TKA volume at the highest volume hospitals (>/=645).Patients having TKA by a surgeon performing <60 TKA per year have higher risk of R-TKA. Racial disparities in R-TKA risk are highest for TKA by surgeons performing 60-145 TKA per year at hospitals performing >/=645 TKA per year. Future studies should examine factors, such as whether trainees are involved the surgery, that may vary based on social determines of health, such as patient race and payor.[1]Wilson S. et al Meaningful thresholds for the volume-outcome relationship in total knee arthroplasty. Journal of bone and joint surgery. 2016;98:1683Table 1.Logistic regression of risk for R-TKAVariable (reference)LevelOdds ratio95% CIp-valueAge--0.950.94-0.95<.001Sex (female)Male1.070.99-1.150.108Race (whiteAsian0.650.42-0.960.031Black1.421.26-1.6<.001Unknown0.810.64-1.020.07Other1.050.92-1.210.446Insurance (Medicare)Medicaid0.890.75-1.060.193Other0.890.7-1.130.331Private0.820.74-0.91<.001Work compensation1.561.35-1.8<.001Surgeon volume (>/=146)</=121.51.25-1.8<.00113-591.161.04-1.290.00660-1451.00.91-1.110.957Hospital volume (>/=645)</= 890.980.84-1.150.84890-2350.990.88-1.120.869236-6440.880.79-0.980.018Hospital bed size (>400 beds)6-1991.131.02-1.250.024200-3991.060.96-1.170.262Other variables in model: diabetes, obesity, renal disease, COPD, osteoarthritis, osteonecrosis, dislocation, inflammatory arthritis, surgical complication, infection, no college, poverty >20%, years since residency, US/Canada medical school, orthopedic board certified, AHA control, teaching, rural hospitalSerene Mirza: None declared, Susan Goodman: None declared, Yi Zhang: None declared, Huong Do: None declared, Bella Mehta: None declared, Stephen Lyman: None declared, Lisa A. Mandl: None declared, Mark Figgie: None declared, Michael Parks Consultant of: Zimmer biomet, Grant/research support from: Zimmer biomet, Linda Russell: None declared, Anne Bass: None declared