Eric J Charles1, J Hunter Mehaffey1, Robert B Hawkins1, Clifford E Fonner2, Leora T Yarboro3, Mohammed A Quader4, Andy C Kiser5, Jeffrey B Rich6, Alan M Speir7, Irving L Kron3, Margaret C Tracci8, Gorav Ailawadi9. 1. Department of Surgery, University of Virginia, Charlottesville, Virginia; Virginia Cardiac Services Quality Initiative, Virginia Beach, Virginia; Center for Health Policy, University of Virginia, Charlottesville, Virginia. 2. Virginia Cardiac Services Quality Initiative, Virginia Beach, Virginia. 3. Department of Surgery, University of Virginia, Charlottesville, Virginia; Virginia Cardiac Services Quality Initiative, Virginia Beach, Virginia. 4. Virginia Cardiac Services Quality Initiative, Virginia Beach, Virginia; Department of Surgery, Virginia Commonwealth University, Richmond, Virginia. 5. Virginia Cardiac Services Quality Initiative, Virginia Beach, Virginia; Department of Cardiovascular Sciences, East Carolina University, Greenville, North Carolina. 6. Virginia Cardiac Services Quality Initiative, Virginia Beach, Virginia; Miller Family Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio. 7. Virginia Cardiac Services Quality Initiative, Virginia Beach, Virginia; Department of Cardiac Surgery, Inova Heart and Vascular Institute, Falls Church, Virginia. 8. Department of Surgery, University of Virginia, Charlottesville, Virginia; Center for Health Policy, University of Virginia, Charlottesville, Virginia. 9. Department of Surgery, University of Virginia, Charlottesville, Virginia; Virginia Cardiac Services Quality Initiative, Virginia Beach, Virginia. Electronic address: gorav@virginia.edu.
Abstract
BACKGROUND: The effects of socioeconomic factors other than insurance status and race on outcomes after cardiac operations are not well understood. We hypothesized that the Distressed Communities Index (DCI), a comprehensive socioeconomic ranking by zip code, would predict operative mortality after coronary artery bypass grafting (CABG). METHODS: All patients who underwent isolated CABG (2010 to 2017) in the Virginia Cardiac Services Quality Initiative database were analyzed. The DCI accounts for unemployment, education level, poverty rate, median income, business growth, and housing vacancies, with scores ranging from 0 (no distress) to 100 (severe distress). Patients were stratified by DCI quartiles (I: 0 to 24.9, II: 25 to 49.9, III: 50 to 74.9, IV: 75 to 100) and compared. Hierarchical linear regression modeled the association between the DCI and mortality. RESULTS: A total of 19,756 CABG patients were analyzed, with mean predicted risk of mortality of 2.0% ± 3.5%. Higher DCI scores were associated with increasing predicted risk of mortality. Overall operative mortality was 2.1% (n = 424) and increased with increasing DCI quartile (I: 1.6% [n = 95], II: 2.1% [n = 77], III: 2.4% [n = 114], IV: 2.6% [n = 138]; p = 0.0009). The observed-to-expected ratio for mortality increased as level of socioeconomic distress increased. After risk adjustment for The Society of Thoracic Surgeons predicted risk of mortality, year of surgical procedure, and hospital, the DCI remained predictive of operative mortality after CABG (odds ratio, 1.14 for each 25-point increase in DCI; 95% confidence interval 1.04 to 1.26; p = 0.007). CONCLUSIONS: The DCI independently predicts risk-adjusted operative mortality after CABG. Socioeconomic status, although not part of traditional risk calculators, should be considered when building risk models, evaluating resource utilization, and comparing hospitals.
BACKGROUND: The effects of socioeconomic factors other than insurance status and race on outcomes after cardiac operations are not well understood. We hypothesized that the Distressed Communities Index (DCI), a comprehensive socioeconomic ranking by zip code, would predict operative mortality after coronary artery bypass grafting (CABG). METHODS: All patients who underwent isolated CABG (2010 to 2017) in the Virginia Cardiac Services Quality Initiative database were analyzed. The DCI accounts for unemployment, education level, poverty rate, median income, business growth, and housing vacancies, with scores ranging from 0 (no distress) to 100 (severe distress). Patients were stratified by DCI quartiles (I: 0 to 24.9, II: 25 to 49.9, III: 50 to 74.9, IV: 75 to 100) and compared. Hierarchical linear regression modeled the association between the DCI and mortality. RESULTS: A total of 19,756 CABG patients were analyzed, with mean predicted risk of mortality of 2.0% ± 3.5%. Higher DCI scores were associated with increasing predicted risk of mortality. Overall operative mortality was 2.1% (n = 424) and increased with increasing DCI quartile (I: 1.6% [n = 95], II: 2.1% [n = 77], III: 2.4% [n = 114], IV: 2.6% [n = 138]; p = 0.0009). The observed-to-expected ratio for mortality increased as level of socioeconomic distress increased. After risk adjustment for The Society of Thoracic Surgeons predicted risk of mortality, year of surgical procedure, and hospital, the DCI remained predictive of operative mortality after CABG (odds ratio, 1.14 for each 25-point increase in DCI; 95% confidence interval 1.04 to 1.26; p = 0.007). CONCLUSIONS: The DCI independently predicts risk-adjusted operative mortality after CABG. Socioeconomic status, although not part of traditional risk calculators, should be considered when building risk models, evaluating resource utilization, and comparing hospitals.
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