LAUSR

Non #mortality-based #quality metrics enable meaningful, consistent benchmarking of EGS applicable to all EGS patients. New #AAST2022 study out in @JTraumAcuteSurg by @CherylZoggPhD Kristan Staudenmayer @LisaKodadek @kadtraumamd from @YaleSurgery @StanfordGenSurg @traumadoctors. BACKGROUND Ongoing efforts to promote quality-improvement in emergency general surgery (EGS) have made substantial strides but lack clear definitions of what constitutes “high-quality” EGS care. To address this concern, we developed a novel set of five non–mortality-based quality metrics broadly applicable to the care of all EGS patients and sought to discern whether (1) they can be used to identify groups of best-performing EGS hospitals, (2) results are similar for simple versus complex EGS severity in both adult (18–64 years) and older adult (≥65 years) populations, and (3) best performance is associated with differences in hospital-level factors. METHODS Patients hospitalized with 1-of-16 American Association for the Surgery of Trauma–defined EGS conditions were identified in the 2019 Nationwide Readmissions Database. They were stratified by age/severity into four cohorts: simple adults, complex adults, simple older adults, complex older adults. Within each cohort, risk-adjusted hierarchical models were used to calculate condition-specific risk-standardized quality metrics. K-means cluster analysis identified hospitals with similar performance, and multinomial regression identified predictors of resultant “best/average/worst” EGS care. RESULTS A total of 1,130,496 admissions from 984 hospitals were included (40.6% simple adults, 13.5% complex adults, 39.5% simple older adults, and 6.4% complex older adults). Within each cohort, K-means cluster analysis identified three groups (“best/average/worst”). Cluster assignment was highly conserved with 95.3% of hospitals assigned to the same cluster in each cohort. It was associated with consistently best/average/worst performance across differences in outcomes (5×) and EGS conditions (16×). When examined for associations with hospital-level factors, best-performing hospitals were those with the largest EGS volume, greatest extent of patient frailty, and most complicated underlying patient case-mix. CONCLUSION Use of non–mortality-based quality metrics appears to offer a needed promising means of evaluating high-quality EGS care. The results underscore the importance of accounting for outcomes applicable to all EGS patients when designing quality-improvement initiatives and suggest that, given the consistency of best-performing hospitals, natural EGS centers-of-excellence could exist. LEVEL OF EVIDENCE Prognostic and Epidemiological; Level III.