Social Determinants Of Health Domains Research Articles

Context Matters: Assessing the Association Between Area Deprivation and the Severity of Injury and Types of Domestic Violence Victimization Among Women.

To analyze the association between social determinants of health (SDOH), as measured by the Area Deprivation Index (ADI), and the severity of injury and types of domestic violence (DV) victimization among women (≥18years of age) in Milwaukee, Wisconsin. Neighborhood ADI data from the American Community Survey (2014-2018) were merged with Milwaukee Police Department DV data (2013-2017). ADI included multiple SDOH domains (education, employment, income/poverty, and housing quality). Types of DV were classified using an adaptation of the FBI-Uniform Crime Reporting-Hierarchy Rule, including Crimes Against Persons (homicide/negligent manslaughter, sexual assault/rape, and aggravated battery/assault). Chi-square, Anova tests, and logistic regression analyses were performed using Stata v.14.2; p-values ≤ .05 were considered statistically significant. Except for aggravated battery/assault (OR: 1.003, 95% CI: 1.001-1.010), there was no statistically significant relationship between neighborhood disadvantage and DV victimization in 21,095 DV incidents between 2013 and 2017. Adjusted model results indicate that with each increase in neighborhood disadvantage (by ADI), there was a 1.003 increase in the likelihood for aggravated battery/assault (OR: 1.003, 95% CI: 1.001-1.005). Severity of DV injury was not significantly associated with ADI (OR: 1.002, 95% CI: 0.999-1.004). However, non-Hispanic Black women were 1.3 times more likely than non-Hispanic Whites to be victims of aggravated battery/assault (OR: 1.321, 95% CI: 1.189-1.469). Hispanic women were more likely than non-Hispanic Whites to sustain a more severe injury (OR: 0.841, 95% CI: 0.732-0.970]). The likelihood of DV-aggravated battery/assault increased with neighborhood deprivation, and significant associations (and highly lopsided prevalence) were found in types of DV victimization by race/ethnicity, with non-Hispanic Black women experiencing higher prevalence than others. This study adds to the body of knowledge by looking at how macro-level neighborhood-SDOH characteristics influence women's exposure to various forms of DV victimization and demonstrated the feasibility of linking law enforcement DV data to SDOH metrics, providing context for law enforcement DV victimizations.

Abstract PO-002: Sourcing real-world data to build the Determinants of Health Ontology of Mappable Elements (DHOME)

Abstract It is widely accepted that social determinants of health (SDOH) play a significant role in the determination of health outcomes. There are several external factors in the natural, built, and social environment beyond the control of the individual which affect their health, and disproportionalities in the burdens of these elements perpetuate health and healthcare disparities. However, there is still no centralized repository that links geographic locations and entities to specific aspects of determinants of health. Moreover, there is not a comprehensive understanding of the spatial and conceptual relationships between them. Ontologies are widely used in health and biomedical research as a means of increasing interoperability between datasets and connecting them to predictable, subsequent health outcomes. Recent projects have also sought to include and expand upon SDOH domains to standardize SDOH vocabulary and make it more accessible in patient care (Dieterle, 2021; Jani et al., 2020; Brenas et al., 2019). However, there have been no ontologies found to date that consider mappable geographical elements for determination of spatial relationships between SDOH domains and health outcome data. The purpose of this study was to source real-world data on South Carolina SDOH elements from public domains, process and manipulate them to highlight relevant attributes and geographies, and compile them into a single repository to allow for proximity and accessibility analyses from geographic coordinate inputs. This methodology resulted in the creation of the `dhomer` R-package which enables the user to perform these analyses via simple coding functions within the R programming language. The package integrates several datasets of factors within the natural, built, and social environment at varying geographic granularities. While the purpose of this package is to assist in a larger study on colorectal cancer pathology and disparities, the capabilities of this repository to increase the ease of spatial analyses and eliminate the time normally relegated to data-sourcing extend well beyond the scope of that study and can be applied to any geographic study considering determinants of health and health disparities. By classifying the datasets into categories of SDOH within the repository as well, this project also prepares mappable data for easy integration to a new SDOH ontology and linkage to existing ontologies regarding SDOH and health outcomes. By creating a centralized repository for all SDOH data, rather than categorizing them independently, this project has the potential to revolutionize the way we conceptualize the relationships between elements of an individual's environment and their synergistic effects on human health. Furthermore, by considering all of the data concurrently, we can now better visualize disparities in the natural, built, and social environment and identify exacerbations of these disparities due to the compounding of several adverse elements that are otherwise invisible when considering the data separately. Citation Format: Lauren Cuppy, Tami Crawford, Alexander V. Alekseyenko. Sourcing real-world data to build the Determinants of Health Ontology of Mappable Elements (DHOME) [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-002.

Race, Racism, and Cardiovascular Health: Applying a Social Determinants of Health Framework to Racial/Ethnic Disparities in Cardiovascular Disease.

Health care in the United States has seen many great innovations and successes in the past decades. However, to this day, the color of a person's skin determines-to a considerable degree-his/her prospects of wellness; risk of disease, and death; and the quality of care received. Disparities in cardiovascular disease (CVD)-the leading cause of morbidity and mortality globally-are one of the starkest reminders of social injustices, and racial inequities, which continue to plague our society. People of color-including Black, Hispanic, American Indian, Asian, and others-experience varying degrees of social disadvantage that puts these groups at increased risk of CVD and poor disease outcomes, including mortality. Racial/ethnic disparities in CVD, while documented extensively, have not been examined from a broad, upstream, social determinants of health lens. In this review, we apply a comprehensive social determinants of health framework to better understand how structural racism increases individual and cumulative social determinants of health burden for historically underserved racial and ethnic groups, and increases their risk of CVD. We analyze the link between race, racism, and CVD, including major pathways and structural barriers to cardiovascular health, using 5 distinct social determinants of health domains: economic stability; neighborhood and physical environment; education; community and social context; and healthcare system. We conclude with a set of research and policy recommendations to inform future work in the field, and move a step closer to health equity.

Ethnicity, Social Determinants of Health, and Pediatric Primary Care During the COVID-19 Pandemic.

This study assessed the relationship between ethnicity, social determinants of health (SDH), and measures of health outcomes for children during the COVID-19 pandemic. This retrospective study reviewed electronic medical records of 1234 in-person well child visits (WCVs for age <18 years) at a single academic primary care clinic in a Chicago suburb for the results of SDH screening in the domains of food, financial, and transportation insecurity. The association between ethnicity, unmet SDH domains, routine medical care delay, vaccine delays, and utilization of acute and emergency department (ED) visits were evaluated. Patients with unmet SDH were more likely to be non-White (P < .001), ≥3 years of age (P < .001) and have Medicaid coverage (P < .001). Unmet social needs were also associated with more acute visits (P < .001), ED visits (P < .001), and WCV delays (P < .001). The results suggest that the COVID-19 pandemic has disproportionately affected patients with unmet SDH in obtaining routine pediatric well child care.

Evaluation of a social determinants of health screening questionnaire and workflow pilot within an adult ambulatory clinic

BackgroundThere is increased recognition in clinical settings of the importance of documenting, understanding, and addressing patients’ social determinants of health (SDOH) to improve health and address health inequities. This study evaluated a pilot of a standardized SDOH screening questionnaire and workflow in an ambulatory clinic within a large integrated health network in Northern California.MethodsThe pilot screened for SDOH needs using an 11-question Epic-compatible paper questionnaire assessing eight SDOH and health behavior domains: financial resource, transportation, stress, depression, intimate partner violence, social connections, physical activity, and alcohol consumption. Eligible patients for the pilot receiving a Medicare wellness, adult annual, or new patient visits during a five-week period (February-March, 2020), and a comparison group from the same time period in 2019 were identified. Sociodemographic data (age, sex, race/ethnicity, and payment type), visit type, length of visit, and responses to SDOH questions were extracted from electronic health records, and a staff experience survey was administered. The evaluation was guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework.ResultsTwo-hundred eighty-nine patients were eligible for SDOH screening. Responsiveness by domain ranged from 55 to 67%, except for depression. Half of patients had at least one identified social need, the most common being stress (33%), physical activity (22%), alcohol (12%), and social connections (6%). Physical activity needs were identified more in females (81% vs. 19% in males, p < .01) and at new patient/transfer visits (48% vs. 13% at Medicare wellness and 38% at adult wellness visits, p < .05). Average length of visit was 39.8 min, which was 1.7 min longer than that in 2019. Visit lengths were longer among patients 65+ (43.4 min) and patients having public insurance (43.6 min). Most staff agreed that collecting SDOH data was relevant and accepted the SDOH questionnaire and workflow but highlighted opportunities for improvement in training and connecting patients to resources.ConclusionUse of evidence-based SDOH screening questions and associated workflow was effective in gathering patient SDOH information and identifying social needs in an ambulatory setting. Future studies should use qualitative data to understand patient and staff experiences with collecting SDOH information in healthcare settings.

Health Care Professionals' Perspectives on Universal Screening of Social Determinants of Health: A Mixed-Methods Study.

Social determinants of health (SDH) contribute to nearly 50% of health outcomes; however, SDH data collection is inconsistent in clinical practice. This study used mixed methods to evaluate health care professionals' perceptions of universal SDH screening at an academic medical center by surveying physicians, advanced practice providers, nurses, social workers, case managers, pharmacists, and administrators. An electronic survey assessed SDH screening practices, prioritization of SDH domains, disciplines to perform screening, and attitudes and barriers to universal screening. Likert-scale responses were dichotomized and compared disciplines with proportions tests. Qualitative interviews identified themes and elaborated survey findings. Participant discipline was the primary predictor variable. Of 193 survey participants (62.5% response rate), most were physicians (31%) or social workers (22%). Participants overwhelmingly reported using SDH information in patient care (93%), and social workers as the most appropriate role for screening (95%). Most respondents (75%) believed health literacy is important, but 40% reported routine assessment. Housing status (73% vs. 53%) and financial strain (62% vs. 48%) followed similar patterns. SDH screening barriers included lacking resources to address identified needs (51%), time to ask (45%), support staff to ask (33%), and training in responding to identified needs (28%). Social workers cited barriers less often than non-social workers (P < 0.001). Qualitative interviews (n = 16) supported survey findings and described barriers including lack of time, resources, standardized approaches, and professional burnout. Health care professionals support universal SDH screening while highlighting the need to address implementation barriers. Strategies should leverage social work expertise and optimize SDH data accessibility for all providers.

Lessons Learned: Social Determinants of Health Screening Pilot in 2 Urology Clinics.

Unmet social needs lead to adverse health outcomes and contribute to health inequities. Efforts to screen for social determinants of health (SDOH) have occurred primarily within primary care. Here, we describe the feasibility of implementing a workflow for SDOH screening within 2 urology clinics in Charlotte, North Carolina. Our pilot was adapted from the WE CARE Model, which integrates a referral to community resources for patients identified with social needs and an optional followup with a navigator for additional assistance. Patients were screened with the validated Healthy Opportunities SDOH tool to assess food, housing, utilities, transportation and physical safety needs; 40 patients were screened at 2 urology clinics, totaling 80 patients. Surveys were sent to 16 clinicians and staff who participated in the pilot to assess feasibility of implementation. In all, 24/80 patients (30%) were screened for 1 or more social needs, with food and housing being the most frequent; 20/24 patients with social need (83%) successfully received a community resource guide, and 13 of those patients also requested a referral. All survey respondents either agreed or strongly agreed that screening was valuable and allowed them to better understand the needs of their patients. They also felt that understanding SDOH aligns with departmental goals and mission. Our results suggest that SDOH screening within a urological setting is feasible, and dedicated support staff should be available to ensure adequate followup for patients with unmet needs. Future work is needed to expand resources for patients and optimize workflow for clinicians.

Social Determinants of Health and Delirium Occurrence and Duration in Critically Ill Adults.

OBJECTIVES:Social determinants of health may affect ICU outcome, but the association between social determinants of health and delirium remains unclear. We evaluated the association between three social determinants of health and delirium occurrence and duration in critically ill adults.DESIGN:Secondary, subgroup analysis of a cohort study.SETTING:Single, 36-bed mixed medical-surgical ICU in the Netherlands.PATIENTS:Nine hundred fifty-six adults consecutively admitted from July 2016 to February 2020. Patients admitted after elective surgery, residing in a nursing home, or not expected to survive greater than or equal to 48 hours were excluded.INTERVENTION:None.MEASUREMENTS AND MAIN RESULTS:Four factors related to three Center for Disease Control social determinants of health domains (social/community context [ethnicity], education access/quality [educational level], and economic stability [employment status and monthly income]) were collected at ICU admission from patients (or families). Well-trained ICU nurses evaluated patients without coma (Richmond Agitation Sedation Scale, –4, –5) and with the Confusion Assessment Method-ICU and/or a delirium day was defined by greater than or equal to 1 + Confusion Assessment Method-ICU and/or scheduled antipsychotic use. Multivariable logistic regression models controlling for ICU days and 10 delirium risk variables (before-ICU: age, Charlson, cognitive impairment, any antidepressant, antipsychotic, or benzodiazepine use; ICU baseline: Acute Physiology and Chronic Health Evaluation IV and admission type; daily ICU: Sequential Organ Failure Assessment, restraint use, coma, benzodiazepine, or opioid use) evaluated associations between each social determinant of health factor and both ICU delirium occurrence and duration. Delirium occurred in 393/956 patients (45.4%) for 2 days (1–5 d). Patients with low (vs high) income had more ICU delirium (p = 0.05). Multivariate analyses revealed no social determinants of health to be significantly associated with increased delirium occurrence or duration. Low (vs high) income was weakly associated with increased delirium occurrence (adjusted odds ratio, 1.83; 95% CI, 0.91–3.89). Low (vs high) education (adjusted relative risk, 1.21; 95% CI, 0.97–1.53) was weakly associated with a longer delirium duration.CONCLUSIONS:Social determinants of health did not affect ICU delirium in one Dutch region. Additional research across different countries/regions and where additional social determinants of health are considered is needed to define the association between social determinants of health and ICU delirium.

Abstract P134: Selected Social Determinants Of Health And Hypertension For Patients Of An Urban Community Primary Care Clinic

Background: Hypertension (HTN) is the most potent cardiovascular disease worldwide and a major public health concern in the U.S. Although Social Determinants of Health (SDoH) are associated with HTN, it is unclear whether these indicators are routinely captured in the primary care setting. We sought to examine the prevalence of any HTN and its association with captured SDoH for new patients (pts) presenting to an urban community primary care clinic for 2019 and 2020. Methods and Results: We identified a cohort-based, cross-sectional sample of 2,577 new pts ≥ 18 years of age in a community clinic in Atlanta, GA, between Jan 2019 and Dec 2020. Electronic health records were reviewed to determine the rate of selected SDoH indicators (financial strain, transportation, medical transportation, and food insecurity) captured at any time and the presenting blood pressure for all new patients. Blood pressure was classified as follows: normal, systolic BP/diastolic BP (SBP/DBP) ≤120/80 mmHg, elevated SBP 120-129mmHg and DBP&lt;80mm, stage 1 SBP 130-139mmHg or DBP 80-90mmHg, and stage 2 SBP ≥ 140mmHg+ or DBP 90mmHg+. Likelihood-ratio Chi-square tests were analyzed to detect an association between SDOH and stages of HTN. Of the 2,577 pts seen, 93% were African American, 72% were female, 59% were single, 77% had BMI ≥ 25, and 85% were insured. Only 41% (n=1062) pts had information of at least one SDoH measure in the entire cohort. Of the SDoH domains evaluated, financial strain and food insecurity were more likely in new pts with stage 1 HTN or higher (χ2= 16.0, df=8, p=0.04; χ2= 27.7, df=12, p=0.006). Conclusion: Routine assessments of SDoH for African American pts presenting for new pt visits are suboptimal in the primary care setting. However, financial strain and food insecurity are significantly associated with stage 1 and 2 HTN in this population. Standardization of intake processes is essential to increase the collection of SDoH indicators and may ultimately guide secondary prevention strategies for HTN interventions.

Racial Disparities in Incidence of Legionnaires' Disease and Social Determinants of Health: A Narrative Review.

Racial and socioeconomic disparities in the incidence of Legionnaires' disease have been documented for the past 2 decades; however, the social determinants of health (SDH) that contribute to these disparities are not well studied. The objective of this narrative review was to characterize SDH to inform efforts to reduce disparities in the incidence of Legionnaires' disease. We conducted a narrative review of articles published from January 1979 through October 2019 that focused on disparities in the incidence of Legionnaires' disease and pneumonia (inclusive of bacterial pneumonia and/or community-acquired pneumonia) among adults and children (excluding articles that were limited to people aged <18 years). We identified 220 articles, of which 19 met our criteria: original research, published in English, and examined Legionnaires' disease or pneumonia, health disparities, and SDH. We organized findings using the Healthy People 2030 SDH domains: economic stability, education access and quality, social and community context, health care access and quality, and neighborhood and built environment. Of the 19 articles reviewed, multiple articles examined disparities in incidence of Legionnaires' disease and pneumonia related to economic stability/income (n = 13) and comorbidities (n = 10), and fewer articles incorporated SDH variables related to education (n = 3), social support (none), health care access (n = 1), and neighborhood and built environment (n = 6) in their analyses. Neighborhood and built-environment factors such as housing, drinking water infrastructure, and pollutant exposures represent critical partnership and research opportunities. More research that incorporates SDH and multilevel, cross-sector interventions is needed to address disparities in Legionnaires' disease incidence.

Emergency department-based interventions affecting social determinants of health in the United States: A scoping review.

Social determinants of health (SDoH) have significant implications for health outcomes in the United States. Emergency departments (EDs) function as the safety nets of the American health care system, caring for many vulnerable populations. ED-based interventions to assess social risk and mitigate social needs have been reported in the literature. However, the breadth and scope of these interventions have not been evaluated. As the field of social emergency medicine (SEM) expands, a mapping and categorization of previous interventions may help shape future research. We sought to identify, summarize, and characterize ED-based interventions aimed at mitigating negative SDoH. We conducted a scoping review to identify and characterize peer-reviewed research articles that report ED-based interventions to address or impact SDoH in the United States. We designed and conducted a search in Medline, CINAHL, and Cochrane CENTRAL databases. Abstracts and, subsequently, full articles were reviewed independently by two reviewers to identify potentially relevant articles. Included articles were categorized by type of intervention and primary SDoH domain. Reported outcomes were also categorized by type and efficacy. A total of 10,856 abstracts were identified and reviewed, and 596 potentially relevant studies were identified. Full article review identified 135 articles for inclusion. These articles were further subdivided into three intervention types: a) provider educational intervention (18%), b) disease modification with SDoH focus (26%), and c) direct SDoH intervention (60%), with 4% including two "types." Articles were subsequently further grouped into seven SDoH domains: 1) access to care (33%), 2) discrimination/group disparities (7%), 3) exposure to violence/crime (34%), 4) food insecurity (2%), 5) housing issues/homelessness (3%), 6) language/literacy/health literacy (12%), 7) socioeconomic disparities/poverty (10%). The majority of articles reported that the intervention studied was effective for the primary outcome identified (78%). Emergency department-based interventions that address seven different SDoH domains have been reported in the peer-reviewed literature over the past 30 years, utilizing a variety of approaches including provider education and direct and indirect focus on social risk and need. Characterization and understanding of previous interventions may help identify opportunities for future interventions as well as guide a SEM research agenda.

Workforce Models to Screen for and Address Patients' Unmet Social Needs in the Clinic Setting: A Scoping Review.

ObjectivesWhile healthcare organizations increasingly aim to address the social determinants of health (SDOH) in the clinic setting, there is little guidance on which staff are best equipped to assume this role. The present study is a scoping review of the peer-reviewed literature to characterize workforce models used to screen for and respond to patients’ unmet social needs in ambulatory settings.MethodsFour online databases were used to identify papers published until February 2021. Eligible articles were original research studies or systematic reviews that described the implementation of a standardized assessment for multiple SDOH domains and resulting activities to respond to individual patient needs (eg, referral to community resources) in ambulatory care settings.ResultsOf the 1569 articles identified, 65 met study eligibility criteria. Majority of studies had observational study designs (11% were randomized control trials). For screening-related activities, more articles reported using traditional healthcare staff (51%), such as medical providers, medical assistants, and front-desk staff, than social care staff (32%), such as social workers and student volunteers. In contrast, for response-related activities, more articles reported using social care staff (88%) than traditional healthcare staff (60%). While we found wide variations in specific team configurations and training for the roles, social care staff generally provided more intensive forms of assistance than traditional healthcare staff.ConclusionWhile this review demonstrates the breadth of models for building or deploying a workforce to integrate health and social care, it also identifies the need for rigorous research on workforce development, implementation, and effectiveness.

“Engaging stakeholders in integrating social determinants of health into electronic health records: a scoping review”

ABSTRACT Social, environmental, and behavioural factors impact human health. Integrating these social determinants of health (SDOH) into electronic health records (EHR) may improve individual and population health. But how these data are collectedand their use in clinical settings remain unclear. We reviewed efforts to integrate SDOH into EHR in the U.S. and Canada, especially how this implementation serves Indigenous peoples. We followed an established scoping review process, performing iterative keyword searches in subject-appropriate databases, reviewing identified works’ bibliographies, and soliciting recommendations from subject-matter experts. We reviewed 20 articles from an initial set of 2,459. Most discussed multiple SDOH indicator standards, with the National Academy of Medicine’s (NAM) the most frequently cited (n = 10). Common SDOH domains were demographics, economics, education, environment, housing, psychosocial factors, and health behaviours. Twelve articles discussed project acceptability and feasibility; eight mentioned stakeholder engagement (none specifically discussed engaging ethnic or social minorities); and six adapted SDOH measures to local cultures . Linking SDOH data to EHR as related to Indigenous communities warrants further exploration, especially how to best align cultural strengths and community expectations with clinical priorities. Integrating SDOH data into EHR appears feasible and acceptable may improve patient care, patient-provider relationships, and health outcomes.

Abstract 16752: Cumulative Social Determinant of Health Risk Score and Prevalent Atherosclerotic CVD Among National Representative Adult Population in US

Introduction: Social determinants of health (SDOH) are contextual factors and shared experiences that impact an individual’s life and health. Unfavorable SDOH are recognized as a major source of excess cardiovascular disease (CVD) risk; however, prior studies have focused on restricted sets of SDOH domains. We aimed to assess the burden of multiple unfavorable SDOH at the population level, and the association between increasing cumulative burden of unfavorable SDOH features and atherosclerotic CVD (ASCVD) prevalence. Methods: Using a nationally-representative sample of 164,696 adults from the National Health Interview Survey (2013-17) we identified 39 parameters (classified as favorable or unfavorable) from the Healthy People 2020SDOH domains: Economic stability, Education, Food access, Neighborhood conditions, Social context, Health systems. An aggregate score of these features ranging 0-36 was then divided into quartiles-- the most unfavorable scores in the highest quartile. ASCVD was ascertained via self-report. Results: 15,758 individuals (8%), representing ~19.6 million Americans, had ASCVD and were more likely to experience economic instability, adverse neighborhood and social cohesion, psychologic distress, food scarcity, and significant cost and non-cost-related healthcare barriers than those without ASCVD. The age adjusted mean (SD) SDOH risk score among ASCVD vs non-ASCVD participants was 12.5 (0.13) vs 0.9 (0.03) respectively. We observed a graded increase in ASCVD prevalence with higher SDOH quartiles (Figure). In multivariate analyses, adults with highest SDOH scores had 2-fold higher odds of having ASCVD compared to those with lowest scores (Figure). Conclusions: In the US, aggregate SDOH risk significantly discriminate risk of prevalent ASCVD among US adults. Standardized SDOH risk scores have the potential to inform risk stratification models at the individual level for addressing avoidable social inequities in health status.

Social determinants of health in electronic health records and their impact on analysis and risk prediction: A systematic review.

This integrative review identifies and analyzes the extant literature to examine the integration of social determinants of health (SDoH) domains into electronic health records (EHRs), their impact on risk prediction, and the specific outcomes and SDoH domains that have been tracked. In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted a literature search in the PubMed, CINAHL, Cochrane, EMBASE, and PsycINFO databases for English language studies published until March 2020 that examined SDoH domains in the context of EHRs. Our search strategy identified 71 unique studies that are directly related to the research questions. 75% of the included studies were published since 2017, and 68% were U.S.-based. 79% of the reviewed articles integrated SDoH information from external data sources into EHRs, and the rest of them extracted SDoH information from unstructured clinical notes in the EHRs. We found that all but 1 study using external area-level SDoH data reported minimum contribution to performance improvement in the predictive models. In contrast, studies that incorporated individual-level SDoH data reported improved predictive performance of various outcomes such as service referrals, medication adherence, and risk of 30-day readmission. We also found little consensus on the SDoH measures used in the literature and current screening tools. The literature provides early and rapidly growing evidence that integrating individual-level SDoH into EHRs can assist in risk assessment and predicting healthcare utilization and health outcomes, which further motivates efforts to collect and standardize patient-level SDoH information.

Social determinants of health score: does it help identify those at higher cardiovascular risk?

Cardiovascular disease (CVD) continues to disproportionately affect disadvantaged populations, leading to calls to address social determinants of health (SDOH) as a preventive strategy. Our aim is to create a weighed SDOH score and to test the impact of each SDOH factor on the Framingham risk score (FRS) and on individual traditional CVD risk factors. We conducted a retrospective cohort study. We included patients seen at a primary care clinic at UHealth/University of Miami Health System who answered a SDOH survey between September 16, 2016, and September 10, 2017. The survey included SDOH domains recommended by the American Heart Association position statement and by the National Academy of Medicine. We selected the FRS as well as all traditional CVD risk factors as our outcome metrics. We included 2876 patients. The mean (SD) age of our cohort was 53.8 (15.8) years, 61% were female, 9% were Black, 38% were Hispanic, and 87% reported speaking English. The statistically significant β coefficients in the FRS model corresponded to being born outside of the United States, being a racial minority, living alone, having a high social isolation score, and having a low geocoded median household income (P < .01). Increasing quartile of SDOH score was significantly associated with higher systolic blood pressure, FRS, glycated hemoglobin, and smoking pack-years (P < .05). It was also associated with fewer minutes spent exercising weekly (P < .01). The addition of self-reported SDOH data has a dose effect on CVD risk factors. Future studies should address how to intervene to address social factors.

Assessing the Impact of Social Needs and Social Determinants of Health on Health Care Utilization: Using Patient- and Community-Level Data.

As the US health care system moves to expand access to and quality of medical care, the importance of addressing patient-level social needs and community-level social determinants of health (SDOH) is increasingly being recognized. This study evaluates individual- and community-level needs of housing (one of the SDOH domains) across the patient population of an academic medical center and explores how the level of housing needs impacts health care utilization. The authors performed a descriptive analysis of housing issues identified in both structured and unstructured (eg, clinical notes) data extracted from the electronic health record (EHR) and compared this to community-level characteristics of patients' neighborhood as measured by the Area Deprivation Index. Multivariate analyses were performed to assess the association between these and other factors on the frequency of service encounters. Among the 1,034,683 study participants, 59,703 (5.8%) had at least 1 housing issue identified in their EHR from structured or unstructured data combined. After adjusting for other factors, patients with housing instability and homelessness had 49% and 34% more encounters with the health care system compared to patients without housing issues (P < 0.00001). Patients living in the most disadvantaged neighborhoods had 55% more encounters with the health care system compared to those living in the most advantaged neighborhoods (P < 0.00001). This data collection approach and findings can inform health care systems aiming to make use of their EHRs and community-level SDOH information to provide a full assessment of patients' social needs and challenges.

1493-P: The Impact of Adverse Social Determinants on Health Care Utilization and Expenditures among U.S. Adults with DKD

Introduction: This study examined whether adverse social determinants of health (SDOH) are associated with higher health care utilization and out of pocket (OOP) expenditures in U.S. adults with diabetic kidney disease (DKD). Methods: Data from 458 adults with self-reported DKD age ≥50 from the Health and Retirement Study 2008-2012 was analyzed. Primary outcomes were number of hospital overnight stays (HOS), number of physician visits (PV) and OOP expenditures. Primary independent variables were nine adverse SDOH factors clustered around three SDOH domains: psychosocial (depression, perceived social support and discrimination); financial hardship (difficulty paying bills, food insecurity, medication cost non-adherence); neighborhood (neighborhood social cohesion, social participation and physical disorder). Two variables were created, a continuous 0-9 and a categorical variable of 0, 1-2, 3+. We used negative binomial regression and marginalized two-part models to determine the impact of adverse SDOH on outcomes. Results: In the unadjusted model, compared to adults with no adverse SDOH, adults with 3+ adverse SDOH had 3% lower likelihood of PV (95%CI 0.72-1.29), 75% (95%CI 1.10-2.79) and 87% (95%CI 1.31-2.65) higher likelihood of HOS and OOP expenditures respectively. In the adjusted model, having 3+ adverse SDOH was not significantly associated with PV (Ratio 0.94 95%CI 0.69-1.29) or HOS (Ratio 1.53 95%CI 0.93-2.49) but was associated with a 2-fold higher likelihood of OOP expenditures (95% CI 1.60-3.31). Adverse neighborhood factors were associated with 63% higher likelihood of HOS (adjusted 95% CI 1.19-2.24) and financial hardship factors were associated with 85% higher likelihood of OOP expenditures (adjusted 95% CI 1.42-2.41). Conclusions: Our findings suggest having 3+ adverse SDOH especially financial hardship impacts OOP expenditures in adults with DKD. Interventions targeting adults with 3+ adverse SDOH may significantly decrease OOP expenditures in DKD. Disclosure M.N. Ozieh: None. E. Garacci: None. R.J. Walker: None. L.E. Egede: None. Funding American Diabetes Association (1-19-JDF-075 to R.J.W.); Advancing Healthier Wisconsin/Clinical and Translational Science (UL1TR001436, KL2TR001438); National Institutes of Health (K24DK093699, R01DK118038, R01DK120861, R01MD013826)

An Integrative Review of Social Determinants of Health Screenings used in Primary Care Settings.

There is limited evidence on how to implement social determinants of health (SDH) screenings. To synthesize recent evidence investigating the implementation of SDH screening in primary care settings. Electronic strategies were used to find articles published between September 2008 and 2018. Articles in the review (N = 15) varied in study design and methodologic rigor, complicating the analysis. Many articles lacked specification on who administered the screening, where the screening was administered, and resource referral rates. The majority of the screenings were administered during the clinic visit by a medical provider. The four primary SDH domains assessed were income, housing stability, education, and employment status. More specific implementation research is needed on the best way for providers to screen for SDH in addition to how screening practices influence resource referrals, resource utilization, and health improvements.

Variation in Electronic Health Record Documentation of Social Determinants of Health Across a National Network of Community Health Centers

This paper describes the adoption of an electronic health record-based social determinants of health screening tool in a national network of more than 100 community health centers. In 2016, a screening tool with questions on 7 social determinants of health domains was developed and deployed in the electronic health record, with technical instructions on how to use the tool and suggested clinical workflows. To understand adoption patterns, the study team extracted electronic health record data for any patient with a community health center visit between June 2016 and May 2018. Patients were considered "screened" if a response to at least 1 social determinants of health domain was documented in the electronic health record tool. A total of 31,549 patients (2% of those with a visit in the study period) had a documented social determinants of health screening. The number of screenings increased over time, time; 71 community health centers (67%) conducted at least one screening, but almost 50% took place in only 4 community health centers. Over half (55%) of screenings only included responses for only 1 domain. Screening was most likely to occur during an office visit with an established patient and documented in the electronic health record by a medical assistant. Screening documentation patterns varied widely across the network of community health centers. Despite the growing national emphasis on the importance of screening for social determinants of health, these findings suggest that simply activating electronic health record tools for social determinants of health screening does not lead to widespread adoption. Potential barriers to screening adoption and implementation should be explored further. This article is part of a supplement entitled Identifying and Intervening on Social Needs in Clinical Settings: Evidence and Evidence Gaps, which is sponsored by the Agency for Healthcare Research and Quality of the U.S. Department of Health and Human Services, Kaiser Permanente, and the Robert Wood Johnson Foundation.