OBJECTIVE: Higher hospital surgical volumes have been associated with lower complication rates following total knee replacement. The objective of this study is to identify the characteristics of patients who undergo total knee replacement at high-volume hospitals and their differences from those who receive care at low-volume hospitals. METHODS: Discharge data from patients undergoing total knee replacement in California from 1991-2001 were analyzed. Hospitals were classified into three tiers of low, intermediate or high surgical volume. The relationship between race/ethnicity and insurance status and the utilization of low-volume and high-volume hospitals were examined by creating separate logistic regression models that corrected for covariates, including age, gender and comorbidity. RESULTS: This study analyzed 222,684 primary total knee replacements during the study period. Patients of non-Caucasian race/ethnicity had higher relative risk ratios for being treated at a low-volume center, including black patients [relative risk ratio (RRR) = 1.73, 95% confidence Interval (CI): 1.09-2.76, p = 0.02]; Hispanic patients (RRR = 3.13, 95% CI: 2.31-4.23, p < 0.001) and Asian/Pacific Islanders (RRR = 2.95, 95% CI: 1.89-4.62, p < 0.001). Medicaid insurance was also an independent predictor of treatment at low-volume hospitals. Age and comorbidity were not statistically significant predictors for receiving care at low-volume centers. CONCLUSIONS: There are substantial disparities in the characteristics of patients receiving care at hospitals performing a high volume of total knee replacements. Black, Hispanic and Asian race/ethnicity as well as Medicaid insurance were predictors of utilization of a low-volume hospital. This study supports the need to consider racial and socioeconomic disparities in efforts to improve the quality of care of patients undergoing total knee replacement at lower-volume hospitals.
OBJECTIVE: Higher hospital surgical volumes have been associated with lower complication rates following total knee replacement. The objective of this study is to identify the characteristics of patients who undergo total knee replacement at high-volume hospitals and their differences from those who receive care at low-volume hospitals. METHODS: Discharge data from patients undergoing total knee replacement in California from 1991-2001 were analyzed. Hospitals were classified into three tiers of low, intermediate or high surgical volume. The relationship between race/ethnicity and insurance status and the utilization of low-volume and high-volume hospitals were examined by creating separate logistic regression models that corrected for covariates, including age, gender and comorbidity. RESULTS: This study analyzed 222,684 primary total knee replacements during the study period. Patients of non-Caucasian race/ethnicity had higher relative risk ratios for being treated at a low-volume center, including black patients [relative risk ratio (RRR) = 1.73, 95% confidence Interval (CI): 1.09-2.76, p = 0.02]; Hispanic patients (RRR = 3.13, 95% CI: 2.31-4.23, p < 0.001) and Asian/Pacific Islanders (RRR = 2.95, 95% CI: 1.89-4.62, p < 0.001). Medicaid insurance was also an independent predictor of treatment at low-volume hospitals. Age and comorbidity were not statistically significant predictors for receiving care at low-volume centers. CONCLUSIONS: There are substantial disparities in the characteristics of patients receiving care at hospitals performing a high volume of total knee replacements. Black, Hispanic and Asian race/ethnicity as well as Medicaid insurance were predictors of utilization of a low-volume hospital. This study supports the need to consider racial and socioeconomic disparities in efforts to improve the quality of care of patients undergoing total knee replacement at lower-volume hospitals.
Authors: Susan M Goodman; Lisa A Mandl; Michael L Parks; Meng Zhang; Kelly R McHugh; Yuo-Yu Lee; Joseph T Nguyen; Linda A Russell; Margaret H Bogardus; Mark P Figgie; Anne R Bass Journal: Clin Orthop Relat Res Date: 2016-06-08 Impact factor: 4.176
Authors: Stephan R Maman; Michael H Andreae; Licia K Gaber-Baylis; Zachary A Turnbull; Robert S White Journal: J Comp Eff Res Date: 2019-10-23 Impact factor: 1.744
Authors: Erin C Hall; Chaoyi Zheng; Russell C Langan; Lynt B Johnson; Nawar Shara; Waddah B Al-Refaie Journal: Am J Surg Date: 2016-01-06 Impact factor: 2.565