Mortality index is more accurate than volume in predicting outcome and failure to rescue in Medicare beneficiaries undergoing robotic right upper lobectomy

Abstract

BackgroundSurgical volume is known to influence failure to rescue (FTR), defined as death following a complication. Robotic lung surgery continues to expand and there is variability in outcomes among hospitals. We sought to estimate the contribution of hospital-based factors on outcomes and FTR following robotic right upper lobectomy (RRUL). MethodsUsing the Centers for Medicare and Medicaid Services inpatient claims database, we evaluated all patients age ≥65 years with a diagnosis of lung cancer who underwent RRUL between January 2018 and December 2020. We excluded patients who had undergone segmentectomy, sublobar, wedge, or bronchoplastic resection; had metastatic or nonmalignant disease; or had a history of neoadjuvant chemotherapy. Primary outcomes included FTR rate, length of stay (LOS), readmissions, conversion to open surgery, complications, and costs. We analyzed hospitals by tertiles of volume and Medicare Mortality Index (MMI). Defined as the institutional number of deaths per number of survivors, MMI is a marker of overall hospital performance and quality. Propensity score models were adjusted for confounding using goodness of fit. ResultsData for 4317 patients who underwent robotic right upper lobectomy were analyzed. Hospitals were categorized by volume of cases (low, <9; medium, 9-20; high, >20) and MMI (low, <0.04; medium, 0.04-0.13; high, >0.13). After propensity score balancing, patients from tertiles of lowest volume and highest MMI had higher costs ($34,222 vs $30,316; P = .006), as well as higher mortality (odds ratio, 7.46; 95% confidence interval, 2.67-28.2; P < .001). Compared to high-volume centers, low-volume centers had higher rates of conversion to open surgery, respiratory failure, hemorrhagic anemia, and death; longer LOS; and greater cost (P < .001 for all). The C-statistic for volume as a predictor of overall mortality was 0.6, and the FTR was 0.8. Hospitals in the highest tertile of MMI had the highest rates of conversion to open surgery (P = .01), pneumothorax (P = .02), and respiratory failure (P < .001). They also had the highest mortality and rate of readmission, longest LOS, and greatest costs (P < .001 for all) and the shortest survival (P < .001). The C-statistic for MMI as a predictor of overall mortality was 0.8, and FTR was 0.9. ConclusionsThe MMI incorporates hospital-based factors in the adjudication of outcomes and is a more sensitive predictor of FTR rates than volume alone. Combining MMI and volume may provide a metric that can guide quality improvement and cost-effectiveness measures in hospitals seeking to implement robotic lung surgery programs.