Social determinants of health (SDoH) such as inequity in care access and systemic bias are associated with operative and longitudinal mortality after congenital heart surgery, new research suggests. A newly published study reveals that these measures of SDoH explain as much or more variability in operative and longitudinal mortality compared with clinical comorbidities or prior cardiac surgery. The U.S.-based team adds that “thoughtful” inclusion of appropriate SDoH could enhance centers’ understanding of their performance and advance equitable care. “Providing both adjusted and unadjusted outcomes, outcomes stratified by social determinants, or even performance-tracking dashboards would be beneficial to centers,” said the authors of the paper, led by Sarah Crook, PhD, from the Icahn School of Medicine at Mount Sinai, New York. “Identification of relevant social determinants that are not directly within the scope of care can also reveal opportunities for hospital-community partnerships and/or multidisciplinary interventions to advance health equity.” Main findings The investigation, which was published Monday online and in the June 18 issue of the Journal of the American College of Cardiology, analyzed 14,173 total index operations from locally held Society of Thoracic Surgeons Congenital Heart Surgery Database (STS-CHSD) data across New York state, of which 12,321 cases, representing 10,271 patients at eight centers, had zip codes for linkage to the American Community Survey. A total of 327 (2.7%) patients died in the hospital or before 30 days, and 314 children died by Dec. 31, 2021 (total n=641; 6.2%). The team revealed that the inclusion of social determinants minimally improved models’ predictive performance (operative: 0.834-0.844; longitudinal 0.808-0.811) but significantly improved model discrimination. Here, 10.0% more survivors and 4.8% more mortalities were appropriately risk classified with inclusion. Further analysis revealed that wide variation in reclassification was observed by site, resulting in changes in the center performance classification category for 2 of 8 centers. “The impact on clinical decision making should be thoroughly investigated before inclusion of social determinants in risk models, particularly when the goal is to inform resource allocation, because inclusion may drive inequitable treatment,” the paper’s authors said. “Social determinants are just one part of a complex interplay between clinical, demographic, behavioral, cultural, and political influences on health.” Equitable health care Discussing how best to implement equitable health care for children, Meena Nathan, MD, MPH, from Boston Children’s Hospital and Harvard Medical School, in Boston, Emily Bucholz, MD, MPH, PhD, from the University of Colorado in Denver, and Katie M. Moynihan, MBBS, from Boston Children’s Hospital and Harvard Medical School, described the issue as, “the next horizon of change.” “The fact that SDoH minimally improved model discrimination in the study by Crook et al underscores the nuanced relationships between SDoH and outcomes and the challenges studying them,” the experts said in their accompanying editorial comment. “Further, the use of retrospective registry and administrative data has inherent limitations related to missingness and variable data quality (especially for SDoH) and the types and complexity of data fields collected.” Delving deeper into the study’s findings, the commentators highlight the limited number of clinical variables included in the risk model as a limitation of the paper’s approach. Although the paper contributes to the body of evidence suggesting that under-resourced and underserved children have adverse health outcomes, the commentators urged the field to move beyond identifying disparities and focus on exploring mechanisms. They suggested a number of methods such as mediation analyses, interaction terms, sequential models, and calculated E values that could offer mechanistic insights into how and why SDoH influence outcomes. The methods could also help determine systematic ways to attenuate/eliminate such inequities by guiding targeted interventions. Influencing health outcomes The commentators went on to conclude that ideally, SDoH and social risk factors should not influence patient health outcomes. “Inclusion of SDoH in patient-level risk adjustment models is controversial and challenged by concerns that such adjustment would conceal inequities or treatment/judgement biases,” they said. “We caution against indiscriminate inclusion of SDoH in predictive models designed to guide patient decision-making because they may drive inequitable treatment, exacerbating inequities. … “Investigations of SDoH and patient outcomes are essential to understand drivers of disparity and to guide interventions to advance health equity; however, social risk factors should not govern how we make decisions for individual patients.” Study methodology Demographic and clinical data were obtained for all congenital heart surgeries (2006-2021) from locally held Congenital Heart Surgery Collaborative for Longitudinal Outcomes and Utilization of Resources Society of Thoracic Surgeons Congenital Heart Surgery Database data. Neighborhood-level American Community Survey and composite sociodemographic measures were linked by zip code. The baseline clinical characteristics of each individual include the age categories of all index operations (n=12,321). These were neonate (n=2,318 [18.8%]); infant (n=3,820 [31.0%]); child 4,516 [36.7%]) and adult (n=1,666 [13.5%]). Model prediction, discrimination and impact on quality assessment were assessed before and after inclusion of social determinants in models based on the 2020 Society of Thoracic Surgeons Congenital Heart Surgery Database Mortality Risk Model. Primary outcomes were operative and longitudinal mortality. Sources: Crook S, Dragan K, Woo JL, et al. Impact of Social Determinants of Health on Predictive Models for Outcomes After Congenital Heart Surgery. J Am Coll Cardiol. 2023;83:2440–2454. Nathan M, Bucholz E, Moynihan KM. Equitable Health Care for Children: The Next Horizon of Change. J Am Coll Cardiol. 2023;83:2455–2457. 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