• J Hunter Mehaffey, Robert B Hawkins, Eric J Charles, Florence E Turrentine, Peter T Hallowell, Charles Friel, R Scott Jones, and Megan C Tracci.
• Department of Surgery, University of Virginia, Charlottesville, VA.
• Ann. Surg. 2020 Mar 1; 271 (3): 470-474.

ObjectiveWe hypothesize the Distressed Communities Index (DCI), a composite socioeconomic ranking by ZIP code, will predict risk-adjusted outcomes after surgery.Summary Of Background DataSocioeconomic status affects surgical outcomes; however, the American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) database does not account for these factors.MethodsAll ACS NSQIP patients (17,228) undergoing surgery (2005 to 2015) at a large academic institution were paired with the DCI, which accounts for unemployment, education level, poverty rate, median income, business growth, and housing vacancies. Developed by the Economic Innovation Group, DCI scores range from 0 (no distress) to 100 (severe distress). Multivariable regressions were used to evaluate ACS NSQIP predicted risk-adjusted effect of DCI on outcomes and inflation-adjusted hospital cost.ResultsA total of 4522 (26.2%) patients came from severely distressed communities (top quartile). These patients had higher rates of medical comorbidities, transfer from outside hospital, emergency status, and higher ACS NSQIP predicted risk scores (all P < 0.05). In addition, these patients had greater resource utilization, increased postoperative complications, and higher short- and long-term mortality (all P < 0.05). Risk-adjustment with multivariate regression demonstrated that DCI independently predicts postoperative complications (odds ratio 1.1, P = 0.01) even after accounting for ACS NSQIP predicted risk score. Furthermore, DCI independently predicted inflation-adjusted cost (+$978/quartile, P < 0.0001) after risk adjustment.ConclusionsThe DCI, an established metric for socioeconomic distress, improves ACS NSQIP risk-adjustment to predict outcomes and hospital cost. These findings highlight the impact of socioeconomic status on surgical outcomes and should be integrated into ACS NSQIP risk models.

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