Distressed communities are associated with worse outcomes after coronary artery bypass surgery

Objectives: Although low socioeconomic status has been associated with increased risk of complications after cardiac surgery, analyses have typically focused on insurance status, race, or median income. We sought to determine if the Distressed Communities Index, a composite socioeconomic metric, could predict operative mortality after coronary artery bypass grafting. Methods: All patients who underwent isolated coronary artery bypass grafting (2011-2018) in the National Society of Thoracic Surgeons adult cardiac surgery database were analyzed. Clinical data were paired with the Distressed Communities Index, which accounts for unemployment, education level, poverty rate, median income, business growth, and housing vacancies by ZIP code. Developed by the Economic Innovation Group, Distressed Communities Index scores range from 0 (no distress) to 100 (severe distress). A distressed community was defined as one having a Distressed Communities Index of 75 or greater for univariate analyses. Results: Of the 575,900 patients undergoing coronary artery bypass grafting with a Distressed Communities Index score, the median age was 65 years. The operative mortality rate was 2.0%, and the composite morbidity or mortality rate was 11.5%. Distressed communities were associated with increased Society of Thoracic Surgeons predicted risk of mortality (1.97% vs 1.85%, P <.0001) and risk of composite morbidity or mortality (12.8% vs 11.7%, P<.0001). After adjusting for Society of Thoracic Surgeons risk model, the Distressed Communities Index remained significantly associated with mortality (odds ratio, 1.12; P<.0001) and composite morbidity and mortality (odds ratio, 1.03; P = .002). Conclusions: Patients from distressed communities are at increased risk for adverse events and death after coronary artery bypass grafting. The Distressed Communities Index is a useful, holistic measure of socioeconomic status that may help identify high-risk patients for quality improvement and should be considered when building risk models or comparing hospitals.