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. 2019 Jan;228(1):21-28.e7.
doi: 10.1016/j.jamcollsurg.2018.07.664. Epub 2018 Oct 22.

Acute Care Surgery Model and Outcomes in Emergency General Surgery

Collaborators, Affiliations

Acute Care Surgery Model and Outcomes in Emergency General Surgery

Kathleen B To et al. J Am Coll Surg. 2019 Jan.

Abstract

Background: Annually, more than 2 million patients are admitted with emergency general surgery (EGS) conditions. Emergency general surgery cases comprise 11% of all general surgery operations, yet account for 47% of mortalities and 28% of complications. Using the statewide general surgery Michigan Surgical Quality Collaborative (MSQC) data, we previously confirmed that wide variations in EGS outcomes were unrelated to case volume/complexity. We assessed whether patient care model (PCM) affected EGS outcomes.

Study design: There were 34 hospitals that provided data for PCM, resources, surgeon practice patterns, and comprehensive MSQC patient data from January 1, 2008 to December 31, 2016 (general surgery cases = 126,494; EGS cases = 39,023). Risk and reliability adjusted outcomes were determined using hierarchical multivariable logistic regression analysis with multiple clinical covariates and PCM.

Results: The general surgery service (GSS) model was more common (73%) than acute care surgery (ACS, 27%). Emergency general surgery 30-day mortality was 4.1% (intestinal resections 11.6%). The ACS model was associated with a reduction of 31% in mortality (odds ratio [OR] 0.69; 95% CI 0.52-0.92] for EGS cases, related to decreased mortality in the intestinal resection cohort (8.5% ACS vs 12% GSS, p < 0.0001). Morbidity in EGS was 17.4% (9.7% elective); highest (40%) in intestinal resection, and PCM did not affect morbidity. We identified specific variables for an optimal EGS risk adjustment model.

Conclusions: This is the first multi-institutional study to identify that an ACS model is associated with a significant 31% mortality reduction in EGS using prospectively collected, clinically obtained, research-quality collaborative data. We identified that new risk adjustment models are necessary for EGS outcomes evaluations.

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