Reconceptualizing high-quality emergency general surgery care: Non-mortality-based quality metrics enable meaningful and consistent assessment

被引:3
作者
Zogg, Cheryl K. [1 ]
Staudenmayer, Kristan L. [2 ]
Kodadek, Lisa M. [1 ]
Davis, Kimberly A. [1 ]
机构
[1] Yale Sch Med, Dept Surg, 67 Cedar St,Room 316 ESH, New Haven, CT 06510 USA
[2] Stanford Univ Hosp, Dept Surg, Stanford, CA 94305 USA
关键词
Emergency general surgery; quality; benchmarking; morbidity; readmission; PROFILING HOSPITAL PERFORMANCE; CAUSE READMISSION RATES; AMERICAN ASSOCIATION; SURGICAL QUALITY; IMPROVEMENT; OUTCOMES; OPERATIONS; CENTERS; VOLUMES; BURDEN;
D O I
10.1097/TA.0000000000003818
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
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 (5x) and EGS conditions (16x). 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.
引用
收藏
页码:68 / 77
页数:10
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