Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery · 2023
Monitoring performance in laparoscopic gastric bypass surgery using risk-adjusted cumulative sum at 2 high-volume centers.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод в очереди
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Blackburn Kyle W, Turrentine Florence E, Schirmer Bruce D, Hallowell Peter T, Kubicki Natalia S, Hu Yinin, Kligman Mark D
Аннотация
BACKGROUND: Traditional surgical outcomes are measured retrospectively and intermittently, limiting opportunities for early intervention.
OBJECTIVES: The objective of this study was to use risk-adjusted cumulative sum (RA-CUSUM) to track perioperative surgical outcomes for laparoscopic gastric bypass. We hypothesized that RA-CUSUM could identify performance variations between surgeons.
SETTING: Two mid-Atlantic quaternary care academic centers.
METHODS: Patient-level data from the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) were abstracted for laparoscopic gastric bypasses performed by 3 surgeons at 2 high-volume centers from 2014 to 2021. Estimated probabilities of serious complications, reoperation, and readmission were derived from the MBSAQIP risk calculator. RA-CUSUM curves were generated to signal observed-to-expected odds ratios (ORs) of 1.5 (poor performance) and .5 (superior performance). Control limits were set based on a false positive rate of 5% (α = .05).
RESULTS: We included 1192 patients: Surgeon A = 767, Surgeon B = 188, and Surgeon C = 237. Overall rates of serious complications, 30-day reoperations, and 30-day readmissions were 3.9%, 2.5%, and 5.2% respectively, with expected rates of 4.7%, 2.2%, and 5.8%. RA-CUSUM signaled lower-than-expected (OR < .5) rates of readmission and serious complication in Surgeon A, and higher-than-expected (OR > 1.5) readmission rate in Surgeon C. Surgeon A further demonstrated an early period of higher-than-expected (OR > 1.5) reoperation rate before April 2015, followed by superior performance thereafter (OR < .5). Surgeon B's performance generally reflected expected standards throughout the study period.
CONCLUSIONS: RA-CUSUM adjusts for clinical risk factors and identifies performance outliers in real-time. This approach to analyzing surgical outcomes is applicable to quality improvement, root-cause analysis, and surgeon incentivization.
OBJECTIVES: The objective of this study was to use risk-adjusted cumulative sum (RA-CUSUM) to track perioperative surgical outcomes for laparoscopic gastric bypass. We hypothesized that RA-CUSUM could identify performance variations between surgeons.
SETTING: Two mid-Atlantic quaternary care academic centers.
METHODS: Patient-level data from the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) were abstracted for laparoscopic gastric bypasses performed by 3 surgeons at 2 high-volume centers from 2014 to 2021. Estimated probabilities of serious complications, reoperation, and readmission were derived from the MBSAQIP risk calculator. RA-CUSUM curves were generated to signal observed-to-expected odds ratios (ORs) of 1.5 (poor performance) and .5 (superior performance). Control limits were set based on a false positive rate of 5% (α = .05).
RESULTS: We included 1192 patients: Surgeon A = 767, Surgeon B = 188, and Surgeon C = 237. Overall rates of serious complications, 30-day reoperations, and 30-day readmissions were 3.9%, 2.5%, and 5.2% respectively, with expected rates of 4.7%, 2.2%, and 5.8%. RA-CUSUM signaled lower-than-expected (OR < .5) rates of readmission and serious complication in Surgeon A, and higher-than-expected (OR > 1.5) readmission rate in Surgeon C. Surgeon A further demonstrated an early period of higher-than-expected (OR > 1.5) reoperation rate before April 2015, followed by superior performance thereafter (OR < .5). Surgeon B's performance generally reflected expected standards throughout the study period.
CONCLUSIONS: RA-CUSUM adjusts for clinical risk factors and identifies performance outliers in real-time. This approach to analyzing surgical outcomes is applicable to quality improvement, root-cause analysis, and surgeon incentivization.