Surgeon Characteristics Supersede Hospital Characteristics in Mortality After Urgent Colectomy

Abstract

BackgroundUrgent colectomy is a common procedure with a high mortality rate that is performed by a variety of surgeons and hospitals. We investigated patient, surgeon, and hospital characteristics that predicted mortality after urgent colectomy. MethodsThe University HealthSystem Consortium was queried for adults undergoing urgent or emergent colectomy between 2009 and 2013 (n = 50,707). Hospitals were grouped into quartiles according to risk-adjusted observed-to-expected (O/E) mortality ratios and compared using the 2013 American Hospital Association Annual Survey. Multiple logistic regression was used to determine patient and provider characteristics associated with in-hospital mortality. ResultsThe overall mortality rate after urgent colectomy was 9 %. Mortality rates were higher for patients with extreme severity of illness (27.6 %), lowest socioeconomic status (10.6 %), weekend admissions (10.7 %), and open (10.5 %) and total (15.8 %) colectomies. Hospitals with the lowest O/E ratios were smaller and had lower volume and less teaching intensity, but there were no significant trends with regard to financial (expenses, payroll, capital expenditures per bed) or personnel characteristics (physicians, nurses, technicians per bed). On multivariate analysis, mortality was associated with patient age (10 years: OR 1.31, p < 0.01), severity of illness (extreme: OR 34.68, p < 0.01), insurance status (Medicaid: OR 1.24, p < 0.01; uninsured: OR 1.40, p < 0.01), and weekend admission (OR 1.09, p = 0.04). Surgeon volume was associated with reduced mortality (per 10 cases: OR 0.99, p < 0.01), but hospital volume was not (per case: OR 1.00, p = 0.84). ConclusionsMortality is common after urgent colectomy and is associated with patient characteristics. Surgeon volume and practice patterns predicted differences in mortality, whereas hospital factors did not. These data suggest that policies focusing solely on hospital volume ignore other more important predictors of patient outcomes.