Social Determinants Of Health Domains Research Articles

EPH186 What Do We Know about Utilization of Z Codes in the Pediatric Population? Exploring Variation in Z Code Use and Social Determinants of Health in a U.S. Hospital-Based, All-Payer Database

Social determinants of health (SDoH) are important nonmedical factors that can impact health outcomes. Despite the availability of Z codes to document SDoH, their use during patient encounters is very low, but can improve delivery of health care. There is a paucity of research on utilization of Z codes and only a handful of these studies have been conducted in the pediatric population (age <18 years). This study documented Z code use and examined the association between patient, clinical, and hospital characteristics and SDoH domains within a pediatric population.

Automatic extraction of social determinants of health from medical notes of chronic lower back pain patients.

We applied natural language processing and inference methods to extract social determinants of health (SDoH) information from clinical notes of patients with chronic low back pain (cLBP) to enhance future analyses of the associations between SDoH disparities and cLBP outcomes. Clinical notes for patients with cLBP were annotated for 7 SDoH domains, as well as depression, anxiety, and pain scores, resulting in 626 notes with at least one annotated entity for 364 patients. We used a 2-tier taxonomy with these 10 first-level classes (domains) and 52 second-level classes. We developed and validated named entity recognition (NER) systems based on both rule-based and machine learning approaches and validated an entailment model. Annotators achieved a high interrater agreement (Cohen's kappa of 95.3% at document level). A rule-based system (cTAKES), RoBERTa NER, and a hybrid model (combining rules and logistic regression) achieved performance of F1 = 47.1%, 84.4%, and 80.3%, respectively, for first-level classes. While the hybrid model had a lower F1 performance, it matched or outperformed RoBERTa NER model in terms of recall and had lower computational requirements. Applying an untuned RoBERTa entailment model, we detected many challenging wordings missed by NER systems. Still, the entailment model may be sensitive to hypothesis wording. This study developed a corpus of annotated clinical notes covering a broad spectrum of SDoH classes. This corpus provides a basis for training machine learning models and serves as a benchmark for predictive models for NER for SDoH and knowledge extraction from clinical texts.

Bridging the health gap: Measuring the unmet social needs of patients within a dental school clinic.

As safety-net clinics, dental school clinics are uniquely positioned to evaluate the unmet social need. There is evidence that patients treated in a safety-net type clinic, such as dental schools, report experiencing one or more of the determinants of health. However, there is limited evidence describing screening for Social Determinants of Health (SDOH) in dental clinics. The purpose of this study is to gain knowledge of the types of social determinants of health that exist in a dental school clinic and how it is reflected in the geographic region of the school. This cross-sectional prospective study used a 20-item questionnaire assessed unmet social needs in a predoctoral clinic. The questionnaire contained multiple choice and binary yes/no questions, organized under SDOH domains: housing, food, transportation, utilities, childcare, employment, education, finances, and personal safety. Socioeconomic and demographic information was captured. The questionnaire was administered via iPad using Qualtrics XM. The data were descriptively and quantitatively analyzed at a significance level of p ≤ 0.05. There were 175 respondents with a 93.6% response rate, males (49.7%), females (49.1%), and 1.1% nonbinary. Overall, 135 (77.1%) respondents reported having at least one unmet social need. The greatest number of unmet needs was in the domains of employment and finances, with 44% and 41.7% respectively. Respondents who were unable to work stated they often or sometimes worried about running out of food before getting money to buy more, (p=0.0002), and or the food didn't last before there was money to get more (p=0.00007). A comparison of annual incomes of respondents earning less than $40K with those earning $40K or more, demonstrated statistically significant differences in unmet social needs for housing (p<0.0001), food (p=0.0003, p<0.0001), utilities (p=0.0484), employment (p=0.0016), education (p<0.0001), and finances (p<0.0001). Screening patients in the dental clinic was an efficient way to uncover the level of unmet social needs. Annual household income was a predominant driver of unmet social needs: with the greatest number of unmet needs existing in the domains of employment and finances. The results suggest that screening for social determinants of health dental school clinics could be incorporated into routine patient data collection.

Social determinants of health among family caregiver centered outcomes in lung cancer: a systematic review.

Lung cancer is the leading cause of cancer death globally. Both lung cancer patients and family caregivers (FCGs) have unmet quality of life (QOL) needs. An understudied topic in lung cancer research is the role of social determinants of health (SDOH) on QOL outcomes for this population. The purpose of this review was to explore the state of research on SDOH FCGs centered outcomes in lung cancer. The databases PubMed/MEDLINE, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature, and American Psychological Association (APA) PsycInfo were searched for peer-reviewed manuscripts evaluating defined SDOH domains on FCGs published within the last ten years. The information extracted using Covidence included patients, FCGs and study characteristics. Level of evidence and quality of articles were assessed using the Johns Hopkins Nursing Evidence-Based Practice Rating Scale. Of the 344 full-text articles assessed, 19 were included in this review. The social and community context domain focused on caregiving stressors and interventions to reduce its effects. The health care access and quality domain showed barriers and underuse of psychosocial resources. The economic stability domain indicated marked economic burdens for FCGs. Four interconnected themes emerged among articles on the influence of SDOH on FCG-centered outcomes in lung cancer: (I) psychological well-being, (II) overall quality of life, (III) relationship quality, and (IV) economic hardship. Notably, most participants in the studies were White females. The tools used to measure SDOH factors included primarily demographic variables. Current studies provide evidence on the role of SDOH factors on lung cancer FCGs' QOL. Expanded utilization of validated SDOH measures in future studies would provide greater consistency in data, that could in turn inform interventions to improve QOL. Further research focusing on the domains of education quality and access and neighborhood and built environment should be carried out to bridge gaps in knowledge.

The Combined Effects of Social Determinants of Health on Childhood Overweight and Obesity.

Background: To characterize the association between multiple social determinants of health (SDOH) and overweight and obesity among US children. Methods: We conducted a cross-sectional analysis using the 2016-2020 National Survey of Children's Health. SDOH domains consisted of Economic Stability, Social and Community Context, Neighborhood and Built Environment, and Health Care Access and Quality. We used ordinal logistic regression to model associations between SDOH and weight status and calculate predicted probabilities of having overweight or obesity for various SDOH profiles. Results: Data from 81,716 children represented a weighted sample of 29,415,016 children ages 10-17 years in the United States. Of these, 17% had overweight and 17% had obesity. Compared with children with the theoretically lowest-risk SDOH profile, children with the highest-risk SDOH profiles in all four domains had an odds ratio of having a higher BMI category of 4.38 (95% confidence interval 1.67-7.09). For the lowest risk profile, the predicted probability of obesity varied from 8% to 11%, depending on race. For the highest risk profile, the predicted probability of obesity varied from 26% to 34%, depending on race. Conclusions: While high-risk values in each SDOH domain were associated with higher predicted probability of overweight and obesity, it was the combination of highest risk values in all the SDOH domains that led to greatest increases. This suggests a complex and multilayered relationship between the SDOH and childhood obesity, necessitating a comprehensive approach to addressing health equity to reduce childhood obesity.

Relationship between social determinants of health and quality of life in low income adults with diabetes in Lebanon

ABSTRACT Background & objective Global rates of type 2 diabetes (T2DM) are increasing, with the Middle East and North Africa (MENA) region having the second highest prevalence in the world. Populations from the MENA region, including Lebanon, are also witnessing massive waves of immigration to the western hemisphere. Limited data exist about how social determinants of health (SDOH) impact outcomes for T2DM in this population. Thus, the aim of this study was to assess the relationship between SDOH and quality of life (QoL) in Lebanese adults with T2DM. Methods Adults with T2DM (n = 300) were recruited from primary healthcare centers in Lebanon. Demographic characteristics and WHO QoL domains (physical health, psychological wellbeing, social relationships, and environment) were assessed. SDOH included socioeconomic, neighborhood/built environment, and psychosocial variables. Partially and fully adjusted regression models were used to test for associations between SDOH and QoL domains. Results Mean age of the participants was 60.3 years, 48% were women, 73% were married, and 64% had less than high-school education. Results from the fully adjusted regression models showed that psychosocial (i.e. adverse childhood experiences and depression), socioeconomic (i.e. employment, income, family size, insurance, financial status, and financial independence), and neighborhood/built environment (i.e. transportation, number of rooms in the household, and certain household items) variables were independent correlates of different QoL domains. Conclusions This study shows that psychosocial, socioeconomic, and neighborhood/built environment variables are differentially associated with different QoL domains, suggesting that SDOH factors are strongly associated with quality of life in low-income adults with T2DM in Lebanon.

Social Determinants of Seeking and Reaching Injury Care in South Africa: A Community-Based Qualitative Study.

Timely access to quality injury care saves lives and prevents disabilities. The impact of social determinants of health on the high injury prevalence in South Africa is well documented, however, evidence of their role in accessing injury care is lacking. This study explored the social determinants of seeking and reaching injury care in South Africa. This was a qualitative study involving rural and urban patients, community members, and healthcare providers in Western Cape, South Africa. Data were obtained through semi-structured interviews and focus group discussions using an interview guide informed by the four-delays framework. Inductive and deductive approaches were used for thematic analysis. A total of 20 individual interviews and 5 focus group discussions were conducted. There were 28 males (individual interviews: 13; focus groups: 15) and 22 females (individual interviews: 7; focus groups: 15), and their mean age was 41 (standard deviation ±15) years. Barriers to seeking and reaching injury care cut across five social determinants of health domains: healthcare access and quality; neighbourhood and environment; social and community context; education; and economic stability. The most prominent social determinants of seeking and reaching injury care were related to healthcare access and quality, including perceived poor healthcare quality, poor attitude of healthcare workers, long waiting time, and ambulance delays. However, there was a strong interconnection between these and neighbourhood and environmental determinants such as safety concerns, high crime rates, gangsterism, lack of public transportation, and social and community factors (presence/absence of social support and alcohol use). Barriers related to education and economic stability were less prevalent. We found a substantial role of neighbourhood, social, and community factors in seeking and reaching injury care. Therefore, efforts aimed at improving access to injury care and outcomes must go beyond addressing healthcare factors to include other social determinants and should involve collaborations with multiple sectors, including the community, the police, the transport department, and alcohol regulation agencies.

Social Risks and Health Care Utilization Among a National Sample of Children With Asthma.

Prior studies using single-center populations have established associations between social risks and health care utilization among children with asthma. We aimed to evaluate associations between social risks and health care utilization among a nationally representative sample of children with asthma. In this cross-sectional study, we utilized the 2018-2019 National Survey of Children's Health to identify children 2 to 17 years old with asthma. Using the Healthy People (HP) 2030 social determinants of health (SDOH) framework, we identified 31 survey items assessing 18 caregiver-identified social risks as exposure variables and classified them into the 5 HP SDOH domains (Economy, Education, Health care, Community, and Environment). Primary outcome was caregiver-reported health care utilization. Associations between individual social risks and total number of SDOH domains experienced with health care utilization were assessed. The weighted study population included 8.05 million children, 96% of whom reported ≥1 social risk. Fourteen social risks, spanning all 5 SDOH domains, were significantly associated with increased health care utilization. The 3 risks with the highest adjusted odds ratios (aOR) of health care utilization included: experiencing discrimination (aOR 3.26 [95% confidence interval (CI): 1.75, 6.08]); receiving free/reduced lunch (aOR 2.16, [95% CI 1.57, 2.98]); and being a victim of violence (aOR 2.11, [95% CI 1.11, 4]). Children with risks across more SDOH domains reported significantly higher health care utilization. Among our national population of children with asthma, social risks are prevalent and associated with increased health care utilization, highlighting their potential contribution to pediatric asthma morbidity.

A personalized risk stratification tool for perinatal morbidity and mortality using explainable artificial intelligence (AI)

Late preterm delivery is frequently considered when competing maternal risks begin to outweigh perinatal risks, but tools for precise, personalized perinatal risk estimation are lacking. Traditional regression methods do not capture the complex interactions specific to each possible combination of risk factors, which can be synergistic rather than simply additive. AI-based Probabilistic Graphical Models (PGMs) can quantify these synergies transparently. We aimed to develop an ‘explainable AI’ machinery for personalized perinatal morbidity risk estimation using variables from clinical and social determinants of health domains.

Evaluating Social Determinants of Health Domains and Their Predictive Validity Within Black/African American and White Older Adults From the ACTIVE Trial.

To assess domains of social determinants of health (SDoH) and their associations with cognition and quality of life. This investigation uses baseline data from individuals participating in the ACTIVE trial (n = 2505) to reproduce the SDoH domains described in Healthy People 2030 (economic stability, health care, education, neighborhood and built environment, and social and community context). Results: Results support using data from the ACTIVE trial to assess all five SDoH domains, and the ability of the composites to predict baseline performance on measures of cognition and self-reported quality of life within a sample of older adults. Additionally, higher SDoH domain scores were associated with better functioning on composite measures of cognition and higher scores for mental and general health-related quality of life with Access to Healthcare associated with all outcomes. Discussion: These findings can inform investigators interested in assessing multiple domains of SDoH and highlight the importance of access to health care within older Black/African American and White older adults.

Assessment of Population-Level Disadvantage Indices to Inform Equitable Health Policy.

There has been unprecedented uptake of disadvantage indices such as the Centers for Disease Control and Prevention Social Vulnerability Index (SVI) to identify place-based patterns of social risk and guide equitable health policy during the COVID-19 pandemic. However, limited evidence around data elements, interoperability, and implementation leaves unanswered questions regarding the utility of indices to prioritize health equity. We identified disadvantage indices that were (a) used three or more times from 2018 to 2021, (b) designed using national-level data, and (c) available at the census-tract or block-group level. We used a network visualization to compare social determinants of health (SDOH) domains across indices. We then used geospatial analyses to compare disadvantage profiles across indices and geographic areas. We identified 14 indices. All incorporated data from public sources, with half using only American Community Survey data (n = 7) and the other half combining multiple sources (n = 7). Indices differed in geographic granularity, with county level (n = 5) and census-tract level (n = 5) being the most common. Most states used the SVI during the pandemic. The SVI, the Area Deprivation Index (ADI), the COVID-19 Community Vulnerability Index (CCVI), and the Child Opportunity Index (COI) met criteria for further analysis. Selected indices shared five indicators (income, poverty, English proficiency, no high school diploma, unemployment) but varied in other metrics and construction method. While mapping of social risk scores in Durham County, North Carolina; Cook County, Illinois; and Orleans Parish, Louisiana, showed differing patterns within the same locations depending on choice of disadvantage index, risk scores across indices showed moderate to high correlation (rs 0.7-1). However, spatial autocorrelation analyses revealed clustering, with discrepant distributions of social risk scores between different indices. Existing disadvantage indices use varied metrics to represent place-based social risk. Within the same geographic area, different indices can provide differences in social risk values and interpretations, potentially leading to varied public health or policy responses.

S48 Health Disadvantage Is Associated With Persistent GI Symptoms in Adults With Crohn’s Disease in Endoscopic Remission

Background: While it is widely recognized that patients’ socioeconomic status and living environments play crucial roles in the management and clinical course of CD, there is a scarcity of health disparities research beyond the associations with race, ethnicity, and insurance coverage. We herein examine the relationship between the symptomatic and inflammatory burden of CD and social determinants of health (SDOH) compassing encompass neighborhood environments and community conditions, including access to education, job opportunities, transportation, and dietary resources. Methods: We performed a retrospective cohort study on adults with CD enrolled in a tertiary referral center biobank in Southern California from 2014-2021. We included patients with standardized clinical disease activity assessments (2-item patient-reported outcome [PRO-2] for abdominal pain [AP] and stool frequency [SF]; remission: AP ≤3 and SF≤1) within 7 days of an ileocolonoscopy scored by the Simple Endoscopic Score for Crohn Disease (remission <3). Health disadvantage was assessed using the California Healthy Places Index (SDOH index), a zip code-based system that ranks communities’ SDOH domains using weighted z-scores (0-100 percentile) from the most health disadvantage (low score) to the most health advantaged (high score) in 8 subdomains: economy, education, healthcare access, housing, neighborhoods, clean environment, transportation, and social environment. Multivariate regression models were created from patient/SDOH factors (dependent variable) that were statistically significant (P < 0.05) on univariate logistic regression to compare the differences between patient with and without active GI symptoms (independent variable) despite endoscopic remission. SDOH subdomains were classified as below (health disadvantage) or above the median (reference) on the SDOH Index. Results: Of the 353 ileocolonoscopies (cases) from 216 unique patients with CD, 151 cases (43%) from 108 unique patients had endoscopic remission. Health disadvantage was not associated with endoscopic disease activity (P = 0.95) with 42% (25/59) and 43% (126/294) of patients below and above the SDOH index median, respectively, were in endoscopic remission. Patients with health disadvantage (below median on the SDOH Index) were more likely to report GI symptoms despite endoscopic remission (OR 2.7, 95% CI 1.1-6.5, P = 0.03). On univariate analysis, poor economic conditions (OR 2.4, 95% CI 1.0-5.7, P = 0.04), low education attainment (OR 3.9, 95% CI 1.8-8.2, P = 0.0004), unfavorable neighborhood conditions (OR 3.1, 95% CI 1.6-6.3, P = 0.001), and poor healthcare access (OR 2.3, 95% CI 1.1-4.4, P = 0.02) were risk factors for persistent GI symptoms. Females (OR 2.8, 95% CI 1.4-5.7, P = 0.003) and smokers (OR 2.6, 95% CI 1.2-5.8, P = 0.02) also reported more persistent GI symptoms. On multivariable analysis, unfavorable neighborhood conditions (aOR 2.9, 95% CI 1.3-6.5, P = 0.01), smoking (aOR 2.6, 95% CI 1.1-6.4, P = 0.02), and female gender (aOR 2.8, 95% CI 1.3-6.5, P = 0.01) remained as risk factors for persistent GI symptoms despite endoscopic remission. Conclusion(s): Health disadvantage, specifically poor neighborhood conditions, may be non-inflammatory risk factors for persistent gastrointestinal symptoms of adults with Crohn’s disease in endoscopic remission. Further investigations into the role of social determinants of health and environmental risk factors in the clinical course and manifestation of IBD are warranted.

Septic Shock and Septic Shock Mortality in Relation to Social Disorganization Index Among Children Being Treated for De Novo Acute Myeloid Leukemia on COG Clinical Trials

Introduction: Acute myeloid leukemia (AML) requires intensive chemotherapy that increases the risk of life-threatening complications such as septic shock (SS). The relationship between social determinants of health (SDOH) and risk of developing SS in children with AML is not well understood. We previously identified associations between race-ethnicity and public insurance and risk of SS in children receiving treatment for acute leukemias (PBC 2019 10.1002/pbc.27713 #2024). To explore this further, we examined associations between the Social Disorganization Index (SDI), an area-based composite measure of SDOH domains, and time to SS and SS-associated mortality (SS-mortality). We hypothesized that higher social disorganization is associated with decreased SS-free survival and higher SS-mortality. Methods: We used a previously assembled cohort of children with de novo AML treated on two Children's Oncology Group (COG) clinical trials merged with daily resource utilization data from the Pediatric Health Information System database (PHIS; PLOS One 2015 10:e0143480). We used the SDI (Health & Place 2017 10.1016/j.healthplace.2016.12.004) to characterize patients’ relative exposure to adversity across SDOH domains. The SDI was calculated using the American Community Survey 5-year estimates and the US Census Bureau's 5-digit national ZIP Code Tabulation Area-level data and linked to patients’ 5-digit ZIP code recorded on first admission. SDI is calculated as the sum of the following proportions: overall unemployment, households receiving public assistance, low-income households at <100% and at 100-149% poverty level, high school dropouts, female-headed households, renter-occupied houses, and moved households within the last year. Higher SDI values indicate a more disorganized neighborhood. To define their exposure to neighborhood disorganization, patients were grouped into one of 5 categories (from least to most disorganized) based on their nationally normed SDI. We used our previously developed and validated method to detect SS events in PHIS (PBC 2019 10.1002/pbc.27713 #2024) and used COG data for patient and disease characteristics and for treatment data. Our secondary outcome, SS-mortality, was defined as death within 2 weeks of antecedent SS event (Lancet Oncol. 2015 10.1016/S1470-2045(15)00197-7). Follow-up started 7 days from first chemotherapy until observed end of therapy to capture treatment-associated SS events. Patients were censored at relapse or death for the time to SS analysis. Time to first SS was summarized using Kaplan Meier estimates. Cox regression models were used to estimate unadjusted hazard ratios (HR) and associated 95% confidence intervals (CI) of SS outcome by SDI category. Results: We identified 701 COG-PHIS patients with AML who had at least 7 days of protocol therapy. Most patients were from SDI category 5 (highest disorganization; Table 1). Patients in higher SDI categories were more likely to be Hispanic or non-Hispanic Black and have public insurance compared to those in the lowest categories. There were 201 (28.7%) incident SS events observed during protocol therapy, which occurred a median of 78 days (IQR 34-122) from start of therapy. We found no significant difference in time to incident SS between SDI categories (log rank p=0.67) or in unadjusted HR for SS events among the SDI categories (Figure 1). Among patients who had SS events, 9 (4.4%) experienced SS-mortality, of which 8 (88.9%) were in higher disorganization categories (SDI 4 or 5). Seven (77.7%) patients who experienced SS-mortality were non-Hispanic White, 6 (66.7%) were female, and 6 (66.7%) had private insurance. SS-mortality occurred a median of 42 days (IQR 15-167) from start of therapy. Five (56%) of the 9 SS-mortality events occurred in cycle 1, 1 (11%) occurred in cycle 2, 3 (33%) occurred in either cycle 4 or 5. Conclusion: In our unadjusted model, neighborhood disorganization was not significantly associated with time to SS. Almost 90% of SS-mortality occurred among patients exposed to higher disorganization neighborhoods (SDI 4 or 5). Over half of SS-mortality occurred with the first cycle of therapy, suggesting a need to investigate associations between the SDI, severity at presentation, and AML induction mortality (Am J Hematol. 2017 10.1002/ajh.24605). We are designing multivariable-adjusted models to address potential confounding and competing risk analyses. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

The Effects of Social Vulnerability on the Prognosis and Outcomes of Hodgkin's Lymphoma in Adults across the United States

Introduction: Hodgkin's Lymphoma (HL) is a common presentation of lymphoma in the United States, representing 10% of all newly diagnosed lymphomas or around 8540 cases annually. With an estimated 5-year survival of 88%, HL generally follows a more indolent course compared to other hematologic malignancies, necessitating patients with HL receiving longer follow up care. Therefore, social determinants of health (SDoH) have ample opportunity to impact care; individual SDoH factors, such as race or lower socioeconomic status (SES), have already been identified as contributing poorer prognosis. However, SDoH is realistically multifaceted and combining multiple factors of SDoH to assess HL outcomes has not yet been well characterized. Here, we compare aggregated SDoH encapsulated by the social vulnerability index, a tool created by the Centers for Disease Control (CDC) using census data, to determine how SDoH impacts prognosis and outcomes in patients with HL. Methods: All adult patients with HL as tracked in the Surveillance, Epidemiology, and End Results (SEER) Program were geographically matched to determine social vulnerability using the Social Vulnerability Index (SVI) at the time of diagnosis. Extranodal HL manifestations were excluded as this was a much rarer form with a different presentation. SVI dynamically weights 15 SDoH considerations into 4 themed domains, including SES, minority status & language, household composition & disability, and housing type & transportation, at the census tract, or county level in sparsely populated areas, to provide a percentile rank ranging from 0 (least vulnerable) to 1 (most vulnerable) across the United States. HL patients were grouped into equivalently sized relative-SVI quintiles based on actual SVI scores ranging from lowest to highest vulnerability. Data was analyzed for HL months surveyed and then patients lost to follow up were excluded to assess mortality in HL months survival for the established quintiles as seen in figure 1. Univariate linear regressions were used to determine significance. Similar methodologies and analyses were also conducted for the 4 SVI domains. Results: Overall, 49366 individuals were identified in SEER (113±105 months), with 17597 of those individuals included in months survival analysis (76±96 months). All groups were statistically significant (P<0.001) with both overall and SVI domains demonstrating decreasing months surveyed or survival with increasing social vulnerability. Additionally, as seen in table 1, a 31.2% decrease in months surveyed and a 48.9% decreased in months survival was noted for overall SVI when comparing the highest vulnerability (most negative SDoH profile) to the lowest vulnerability quintile (most positive SDOH profile). Substantial decreases were also seen in SES (34.3%, 35.2%), minority status & language (13.7%, 21.8%), household composition & disability (15.8%, 18.8%), and housing type & transportation (22.5%, 36.5%) for months surveyed and months survival respectively between the two groups. Conclusion: Higher overall SVI scores and specific social vulnerability domain scores correlated with statistically decreased months surveyed and months survival in patients with HL. Furthermore, the size of difference noted between high and low vulnerability groups in both categories indicate the substantial role SDoH has in both patient follow up and mortality and may suggest differing impact across various SDoH domains. Despite established management for HL, consequential health disparities are clearly still present affecting multiple avenues of care. With such a large and encompassing data set, greater power and statistical certainty can be generated. This work highlights the need for specific initiatives to target SDoH in HL to bridge the gap in providing equitable treatment for all. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Evaluating Social Determinants of Health in a Mobile Integrated Healthcare-Community Paramedicine Program.

In 2018, the University of Maryland Medical Center and the Baltimore City Fire Department implemented a community paramedicine program to help medically or socially complex patients transition from hospital to home and avoid hospital utilization. This study describes how patients' social determinants of health (SDoH) needs were identified, and measures the association between needs and hospital utilization.SDoH needs were categorized into ten domains. Multinomial logistic regression was used to measure association between identified SDoH domains and predicted risk of readmission. Poisson regression was used to measure association between SDoH domains and actual 30-day hospital utilization.The most frequently identified SDoH needs were in the Coordination of Healthcare (37.7%), Durable Medical Equipment (18.8%), and Medication (16.3%) domains. Compared with low-risk patients, patients with an intermediate risk of readmission were more likely to have needs within the Coordination of Healthcare (RRR [95% CI] 1.12 [1.01, 1.24], p = 0.032) and Durable Medical Equipment (RRR = 1.13 [1.00, 1.27], p = 0.046) domains. Patients with the highest risk for readmission were more likely to have needs in the Utilities domain (RRR = 1.76 [0.97, 3.19], p = 0.063). Miscellaneous domain needs, such as requiring a social security card, were associated with increased 30-day hospital utilization (IRR = 1.23 [0.96, 1.57], p = 0.095).SDoH needs within the Coordination of Healthcare, Durable Medical Equipment, and Utilities domains were associated with higher predicted 30-day readmission, while identification documentation and social services needs were associated with actual readmission. These results suggest where to allocate resources to effectively diminish hospital utilization.

The effect of social determinants of health on utilization of surgical treatment for hepatocellular carcinoma patients

BackgroundA paucity of data exists on how social determinants of health (SDOH) influence treatment for Hepatocellular carcinoma (HCC). We investigated associations between SDOH (healthcare access, education, social/community context, economic stability, and built/neighborhood environment) and receipt of surgery. MethodsThe Pennsylvania Liver Cancer Registry was linked with neighborhood SDOH from the American Community Survey. Multilevel logistic regression models with patient and neighborhood SDOH variables were developed. ResultsOf 9423 HCC patients, 2393 were stage I. Only 36.3% of stage I patients received surgery. Black patients had significantly lower odds of surgery vs Whites (OR = 0.73; p < 0.01), but not after adjustments for SDOH. All 5 SDOH domains were associated with odds of surgery overall; 2 domains were associated in Stage I patients, social context (e.g., racial concentration, p = 0.03) and insurance access (p < 0.01). ConclusionsSDOH impact utilization of surgery for HCC. Findings can guide healthcare professionals to create programs for populations at risk for poor liver cancer outcomes.

Impact of social determinants of health on anticoagulant use among patients with atrial fibrillation: Systemic review and meta-analysis.

Background:A growing body of literature now exists examining associations between social determinants of health (SDOH) and adverse outcomes in patients with atrial fibrillation; however, little is available on anticoagulant prescriptions and the impact of SDOH.Purpose:Evaluate the impact of SDOH on anticoagulant prescriptions in patients with atrial fibrillation.Data Sources:Medline and Embase databases up to January 2021.Study Selection:Noninterventional studies were included if they reported associations between at least 1 of 14 SDOH domains and anticoagulant prescription in patients with atrial fibrillation. Two investigators independently screened and collected data.Data Extraction:Two investigators independently screened and collected data.Data Synthesis:Meta-analyses using random-effect models evaluated associations between SDOH and receiving an anticoagulant prescription. We included 13 studies, 11 of which were included in meta-analyses that reported on the impact of 9 of the 14 SDOH included in the search. Pooled estimates indicate a 0.85 (95% confidence interval [CI]: 0.75, 0.97) lower odds of receiving anticoagulant prescriptions among Black compared to non-Black patients (reported in 6 studies); 0.42 (95% CI: 0.32, 0.55) lower odds of receiving anticoagulant prescriptions among patients with mental illness compared to those without mental illness (2 studies); and a 0.64 (95% CI: 0.42, 0.96) lower likelihood of receiving oral anticoagulant prescription among employed patients compared to unemployed patients (2 studies).Limitations:SDOH lack consistent definitions and measures within the electronic health record.Conclusion:The literature reports on only half of the SDOH domains we searched for, indicating that many SDOH are not routinely assessed. Second, social needs impact the decision to prescribe anticoagulants, confirming the need to screen for and address social needs in the clinical setting to support clinicians in providing guideline concordant care to their patients.Registration:This systematic review and meta-analysis was registered with PROSPERO.

Differences in overdose deaths by intent: Unintentional & suicide drug poisonings in North Carolina, 2015–2019

Comprehensive fatal overdose prevention requires an understanding of the fundamental causes and context surrounding drug overdose. Using a social determinants of health (SDOH) framework, this descriptive study examined unintentional and self-inflicted (i.e., suicide) overdose deaths in North Carolina (NC), focusing on specific drug involvement and contextual factors. Unintentional and suicide overdose deaths were identified using 2015–2019 NC death certificate data. Specific drug involvement was assessed by searching literal text fields for drug mentions. County-level contextual factors were obtained from NC Institute of Medicine and County Health Rankings, encompassing five SDOH domains (economic stability, social/community context, health care access/quality, education access/quality, neighborhood/built environment). Descriptive statistics were calculated by intent for drug involvement and a variety of contextual factors. During 2015–2019, 9% of NC drug overdose deaths were self-inflicted and 89% were unintentional (2% other/undetermined). Unintentional overdoses largely involved illicit drugs [fentanyl (47%), cocaine (33%), heroin (29%)]. Suicide overdoses frequently involved prescription opioids [oxycodone (18%), hydrocodone (10%)] and antidepressants (32%). Overall, overdose deaths tended to occur in under-resourced counties across all SDOH domains, though unintentional overdoses occurred more often among residents of under-resourced counties than suicide overdoses, with differences most pronounced for economic stability-related factors. There are notable distinctions between unintentional and suicide overdose deaths in demographics and drug involvement, though the assessment of SDOH demonstrated that overdose mortality is broadly associated with marginalization across all domains. These findings highlight the value of allocating resources to prevention and intervention approaches that target upstream causes of overdose (e.g., housing first, violence prevention programs).

Addressing social risk factors in the inpatient setting: Initial findings from a screening and referral pilot at an urban safety-net academic medical center in Virginia, USA

Social Determinants of Health (SDOH) impact health outcomes; thus, a pilot to screen for important SDOH domains (food, housing, and transportation) and address social needs in hospitalized patients was implemented in an urban safety-net academic medical center. This study describes the pilot implementation and examines patient characteristics associated with SDOH-related needs.An internal medicine unit was designated as a pilot site. Outreach workers approached eligible patients (n = 1,135) to complete the SDOH screening survey at time of admission with 54% (n = 615) completing the survey between May 2019 and July 2020. Data from patient screening survey and electronic health records were linked to allow for examination of associations between SDOH needs for food, housing, and transportation and various demographic and clinical characteristics of patients in multivariate logistic regression models. Of 615 screened patients, 45% screened positive for any need. Of 275 patients with needs, 33% reported needs in 2, and 34% – in 3 domains. Medicaid beneficiaries were more likely than patients with private health insurance to screen positive for 2 and 3 needs; Black patients were more likely than White patients to screen positive for 1 and 3 needs; Patients with no designated primary care physician status screened positive for 1 need; Patients with a history of substance use disorder screened positive for all 3 needs.SDOH screening assisted in addressing social risk factors of inpatients, informed their discharge plans and linkage to community resources. SDOH screening demonstrated significant correlations of positive screens with race/ethnicity, insurance type, and certain clinical characteristics.

A-11 Social Determinants of Health in the Diagnosis and Management of Pediatric Concussion: A Content Analysis

Abstract Purpose: This content analysis examined the literature underlying the Centers for Disease Control and Prevention Guideline on the Diagnosis and Management of Mild Traumatic Brain Injury Among Children (i.e., the “Guideline”) to determine the extent to which social determinants of health (SDH) were examined or addressed. Methods: A published systematic review, that formed the basis for the Guideline, included 37 studies addressing diagnosis, prognosis, and treatment/rehabilitation. We examined those studies to identify SDH domains and associated subcategories derived from the Healthy People 2020 and 2030 websites. Pairs of raters coded each article with disagreements resolved by consensus. Results: At least one SDH domain was represented in 60% of the articles, usually mentioned descriptively, as a covariate, or as a design consideration. Very few were addressed as a primary focus of the study. The most frequently represented SDH domain was Education Access (43.2% of studies), receiving credit most often for reporting on participants with learning disabilities. Social and Community Context, broadly defined, was represented in nearly 1 of 3 studies (29.7%). Economic Stability and Health Care Access domains were included in 6 studies (16.2%). Some studies (k = 6, 16.2%) referenced SDH as important to consider for future research. The Guideline includes some commentary on health literacy and socioeconomic status. Conclusions: Social determinants of health are largely unrepresented as important or meaningful variables influencing the Guideline on the Diagnosis and Management of Mild Traumatic Brain Injury Among Children, or in the studies included in the systematic review that informed the guideline.