Abstract

156 Background: Racial inequities in lung cancer surgical quality are well documented yet understanding the variation in racial inequities across healthcare systems remain limited. Therefore, in this study the variation in racial disparities mortality across healthcare systems was evaluated. Methods: Using 100% Medicare fee-for-service claims, we analyzed data on Medicare beneficiaries between the ages of 65- and 99-years old undergoing resection for lung cancer. All patients undergoing resection for lung cancer between 2014 and 2018 were included. Clinical risk-adjusted 30-day post-operative mortality rates for an overall health care systems as well as rates for non-Hispanic Black and non-Hispanic white patients within each of system were evaluated using multivariate logistic regression. The variation across all healthcare systems performing at least 5 operations for each racial group was performed. A total of 216 healthcare systems were included. Results: Overall, 82,978 patients were included with mean (SD) age of 73.7(5.5) years and racial composition of 7,124 Black patients (8.6%) and 75,854 White patients (91.7%). Of these 216 systems, 90 (41.7%) had significant disparities with the worst mortality in Black beneficiaries. Of these systems with significant worst mortality for Black patients undergoing resection for lung cancer, the odds of mortality of Black compared to White patients ranged from OR 1.04 (95% CI 1.01-1.08; P < 0.001) to OR 2.9 (95% CI 2.6-3.2; P < 0.001). There was weak but statistically significant association between system overall mortality and the Black-White difference in mortality (R = 0.14; P < 0.04). Conclusions: Our findings provide justification for system- level interventions to address disparities in surgical care for Black patients undergoing resection for lung cancer. Moreover, our findings suggest that quality improvement efforts to improve overall quality of surgical care that do not focus on the care of Black patients may be insufficient for reduction of disparities.[Table: see text]

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call