This study of the public health landscape in New York City investigated the interplay between social determinants of health (SDOH), chronic health conditions, and inequities in social factors, with a focus on cardiovascular disease (CVD).
Incorporating data on social determinants of health (SDOH) for solutions to increase health equity in cardiovascular disease (CVD) continues to hit barriers in the public health sector, with new research calling for additional investigation into how to best implement data-driven solutions.
CVD was the top cause of death among New York City residents as recently as 2019—with the CVD-related death rate twice as high in poverty areas and higher rates of adverse outcomes seen among persons with low education levels—according to the study findings published recently in AJPM Focus of an investigation focused on outcomes in New York City. The study authors highlighted that although ample data exist on the impact SDOH can have, few analyses have examined just how to optimally use the data to increase health equity. They conducted 11 interviews from June to July 2022 with key stakeholders from health departments, health care delivery systems, and community-based organization within New York City’s public health landscape. The investigators found they were able to categorize responses as priorities related to SDOH, current and potential uses of data, and challenges to using data.
“There is growing recognition of the importance of addressing SDOH in efforts to improve health equity. In dense urban environments like New York City, disparities in chronic health conditions (eg, CVD) closely mimic inequities in social factors such as income, education, and housing,” the authors wrote. “We focused on CVD because it is the main cause of death of NYC residents and its determinants are multifactorial.” For example, in Brownsville, Brooklyn, the average life expectancy is 75.1 years and the median household income is $32,940 vs 85.9 years and $141,090 for the Upper East Side of Manhattan.
The study authors saw much overlap in the SDOH priorities that interviewees cited as having an impact on cardiovascular health: stable housing, dietary and water intake, grocery purchases and food insecurity, the ongoing digital divide, health service access and use, family communication, and low levels of physical activity/mobility. According to the interview findings, these SDOH are “the root causes of health inequity in NYC,” which they say are linked to redlining and a lack of investment in low-resourced communities.
Also according to the interviewees, they currently use SDOH data to identify disparities in care, provide tailored services and resources to patients, and monitor and evaluate health care outcomes. Sources of these data include self-reports from patients via International Classification of Diseases, 10th Revision, codes and New York City Community Health surveys. Another potential resource of SDOH data, the study authors noted, could be the entitlement programs for which patients are eligible and that may be included in their electronic health record (EHR). Using data from several sources (eg, social services, meal delivery services, Medicaid, Supplemental Nutrition Assistance Program) could help facilitate identification of disparities in care access, outcomes, and experiences, such as medication nonadherence, housing assistance, and care utilization, and referral to community health workers or additional public assistance programs.
Another current use of multifaceted SDOH data, according to the interview findings, is “to obtain awards and certifications, which are then used to obtain higher reimbursement rates from insurers, and to assess whether care improved following medical-home certification.”
Potential future uses of SDOH data include transferring and aggregating data between organization and using that for resource mobilization. However, according to the study authors, this only serves to underscore the need for more comprehensive sources and ranges of SDOH data.
Barriers to the collection, sharing, and use of more comprehensive and updated SDOH data include manual data entry; unanswered screening questions on race, ethnicity, and housing status; lack of standardization in data collection; and outdated data, with the investigators pointing to most systems’ reliance on patient self-reporting of SDOH, the laborious process of reaching out to patients on an individual basis, and lack of interoperability between HER systems as hindrances.
“Future research on this topic should focus on mitigating the barriers to using SDOH data, which includes incorporating SDOH data from other sectors,” the study authors concluded. “There is also a need to assess how data-driven solutions can be implemented within and across communities and organizations.”
Lindenfeld Z, Pagán JA, Silver D, et al. Stakeholder perspectives on data-driven solutions to address cardiovascular disease and health equity in New York City. AJPM Focus.Published online March 23, 2023. doi:10.1016/j.focus.2023.100093