Using social risks to predict unplanned hospital readmission and emergency care among hospitalized Veterans.

OBJECTIVES: (1) To estimate the association of social risk factors with unplanned readmission and emergency care after a hospital stay. (2) To create a social risk scoring index. DATA SOURCES AND SETTING: We analyzed administrative data from the Department of Veterans Affairs (VA) Corporate Data Warehouse. Settings were VA medical centers that participated in a national social work staffing program. STUDY DESIGN: We grouped socially relevant diagnoses, screenings, assessments, and procedure codes into nine social risk domains. We used logistic regression to examine the extent to which domains predicted unplanned hospital readmission and emergency department (ED) use in 30 days after hospital discharge. Covariates were age, sex, and medical readmission risk score. We used model estimates to create a percentile score signaling Veterans' health-related social risk. DATA EXTRACTION: We included 156,690 Veterans' admissions to a VA hospital with discharged to home from 1 October, 2016 to 30 September, 2022. PRINCIPAL FINDINGS: The 30-day rate of unplanned readmission was 0.074 and of ED use was 0.240. After adjustment, the social risks with greatest probability of readmission were food insecurity (adjusted probability = 0.091 [95% confidence interval: 0.082, 0.101]), legal need (0.090 [0.079, 0.102]), and neighborhood deprivation (0.081 [0.081, 0.108]); versus no social risk (0.052). The greatest adjusted probabilities of ED use were among those who had experienced food insecurity (adjusted probability 0.28 [0.26, 0.30]), legal problems (0.28 [0.26, 0.30]), and violence (0.27 [0.25, 0.29]), versus no social risk (0.21). Veterans with social risk scores in the 95th percentile had greater rates of unplanned care than those with 95th percentile Care Assessment Needs score, a clinical prediction tool used in the VA. CONCLUSIONS: Veterans with social risks may need specialized interventions and targeted resources after a hospital stay. We propose a scoring method to rate social risk for use in clinical practice and future research.

Benefits of using both the Hunger Vital Sign and brief nutrition security screener in health-related social needs screening.

Food security is a commonly screened for health-related social need at hospitals and community settings, and until recently, there were no tools to additionally screen for nutrition security. The purpose of this study was to assess the potential advantage of including a one-item brief nutrition security screener (BNSS) alongside the commonly used two-item Hunger Vital Sign (HVS) food security screener for identifying individuals with diet-related health risks. Cross-sectional survey data were collected from April to June 2021. Generalized linear mixed models were used to assess associations between screening status and dietary and health variables. Recruitment was done across five states (California, Florida, Maryland, North Carolina, and Washington) from community-based organizations. Participants (n = 435) were, on average, 44.7 years old (SD = 14.5), predominantly women (77%), and racially/ethnically diverse. In adjusted analyses, being in the food insecure and nutrition insecure group (but not the food insecure and nutrition secure or food secure and nutrition insecure groups) was associated with significantly increased odds for self-reported "fair" or "poor" general health [OR = 2.914 (95% CI = 1.521-5.581)], reporting at least one chronic condition [2.028 (1.024-4.018)], and "low" fruit and vegetable intake [2.421 (1.258-4.660)], compared with the food secure and nutrition secure group. These findings support using both the HVS and BNSS simultaneously in health-related social needs screening to identify participants at the highest risk for poor dietary and health outcomes and warrant further investigation into applying these screeners to clinical and community settings.

Food security and nutrition security are related to a household's ability to get enough food and to get food that is good for their health, respectively. Patients at hospitals, or clients who go to food pantries for help, are often asked about their food security status. This is referred to as screening. On the basis of their answers, they may get help such as referral to a food pantry and/or consultation with a dietitian. While there is a standard tool to screen for food security status, until recently, there has not been one for nutrition security. We used both the commonly used Hunger Vital Sign (HVS) food security screener and the newly developed brief nutrition security screener to identify food and nutrition security screening status. Being in the food insecure and nutrition insecure groups (but not the food insecure and nutrition secure or food secure and nutrition insecure groups) was associated with significantly increased odds for poor dietary and health outcomes. These findings support using both the HVS and brief nutrition security screener simultaneously in health-related social needs screening to identify participants at the highest risk.

Screening for Health-Related Social Needs and Financial Toxicity Among Patients With Cancer Treated With Radiation Therapy: Findings From a Quality Improvement Project.

INTRODUCTION: Financial toxicity is common among patients with cancer, as are co-occurring health-related social risks (HRSRs). There is limited evidence to support best practices in screening for HRSRs and financial toxicity in the cancer context. This analysis sought to understand variations of identified needs based on treatment course using data from a large screening program. METHODS: This 2022 to 2023 screening quality improvement program included four services (breast, gastrointestinal, gynecologic, thoracic) at an urban comprehensive cancer center. The Comprehensive Score for Financial Toxicity measured financial toxicity. Patients completed an HRSR checklist documenting food, housing, medication, or transportation insecurity and financial borrowing practices. Differences were evaluated by treatment course (radiation therapy [RT] versus other treatment and RT plus chemotherapy versus other treatment). RESULTS: Screening surveys were sent to 70,983 unique patients; 38,249 completed a screening survey (54% response rate). Of responders, 4% (n = 1,686) underwent RT in the 120 days before their survey, and 3% (n = 1,033) received RT in combination with chemotherapy. Overall, patients receiving RT had lower unadjusted Comprehensive Score for Financial Toxicity scores, indicating worse financial toxicity. The proportion of patients receiving RT reporting unmet transportation (15% versus 12%, P < .001) and food (13% versus 11%, P = .02) needs was significantly higher than for patients not receiving RT. More patients receiving RT borrowed money than did patients not receiving RT (17% versus 15%, P = .02). In multivariable models, RT (alone or in combination) was associated with worse financial toxicity and transportation difficulties. CONCLUSIONS: Screening for financial toxicity and HRSR is possible at a large cancer center. Patients receiving RT have higher transportation insecurity and worse financial toxicity compared with those receiving other treatments. Tailored intervention throughout the treatment trajectory is essential.

Understanding social risk factors in patients presenting to the emergency Department for Acute Heart Failure: A pilot study.

BACKGROUND: The standard of care for congestive heart failure (CHF) aims to slow disease progression and maximize patient function, however there is an increase in emergency department (ED) revisits and readmissions. Social risk factors play a role in the disease management and prognosis of CHF. There is a gap in the identification of low-risk CHF patient who would be safely discharged using an initial social risk factor stratification. OBJECTIVES: To generate a social risk profile for patients presenting to the ED with acute CHF exacerbation and identify variables that may increase the risk of 7-day and overall mortality, 30-day ED revisit, and readmission. METHODS: We conducted a pilot prospective survey-based study among adult patients presenting to the ED with acute CHF exacerbation. The combination of a self-report questionnaire and retrospective chart review was used to generate a CHF risk profile. RESULTS: A total of 62 patients were recruited in the pilot study with a mean age of 69.5 years. The preliminary data indicated that prior to this ED visit, 21% of patients were not aware of a previous CHF diagnosis; 64.5% of patients rated their sleep quality as poor or very poor; 72.6% reported orthopnea; and 43.5% reported recent weight gain. 37.1% of patients did not adhere to dietary recommendations and some patients did not adhere to their medication regime 100%. CONCLUSION: This study suggests establishing a social risk profile for patients presenting to the ED with CHF can help formulate a CHF-specific care plan and optimize multidisciplinary management to reduce ED revisits and readmissions.

Social risk to infant: The role of kin for maternal visual monitoring in Tibetan macaques.

Maternal monitoring of conspecifics is a crucial anti-predator strategy that also protects infants against risks within the social group. This study examines how maternal characteristics, infant characteristics, mother-infant distance, and the social environment affect maternal monitoring behaviors in free-ranging Tibetan macaques (Macaca thibetana). We observed 12 females with infants and analyzed their visual monitoring patterns. Our findings indicate that maternal rank significantly influences the time allocated to maternal visual monitoring, higher-ranking mothers spending less time than lower-ranking mothers. Maternal experience also played a role in monitoring strategies. Differences in monitoring strategies were observed based on maternal experience: first-time mothers (primiparity) engaged in longer but less frequent monitoring sessions compared to experienced mothers (multiparity). The time and frequency of maternal monitoring decreased as infants aged, and mothers with male infants showed higher levels of monitoring than those with female infants. The distance between mother and infant also affected visual monitoring behavior, with mothers increasing their monitoring levels when infants were nearby (1-5 m), rather than within reach (0-1 m) or beyond nearby (>5 m). Additionally, the presence of kin and non-kin influenced monitoring: as the number of nearby kin increased, monitoring levels decreased, while the presence of more non-kin males led to an increase in monitoring time, and higher-ranking non-kin neighbors increased the frequency of monitoring. These results suggest that Tibetan macaque mothers can adapt their visual monitoring to the social risks faced by their infants, adjusting their strategies to their status and the needs of their offspring.

Families' Perspectives on Social Services Navigation After Pediatric Urgent Care.

BACKGROUND: Interest is growing in clinic-based programs that screen for and intervene on patients' social risk factors, including housing, food, and transportation. Though several studies suggest these programs can positively impact health, few examine the mechanisms underlying these effects. This study explores pathways through which identifying and intervening on social risks can impact families' health. METHODS: This qualitative study was embedded in a randomized clinical trial that examined the health impacts of participation in a social services navigation program. We conducted semi-structured interviews with 27 English or Spanish-speaking caregivers of pediatric patients who had participated in the navigation program. Interviews were analyzed using thematic analysis. RESULTS: Caregivers described 3 pathways through which the navigation program affected overall child and/or caregiver health: 1) increasing families' knowledge of and access to social services; 2) helping families connect with health care services; and 3) providing emotional support that reduced caregiver isolation and anxiety. Participants suggested that navigation programs can influence health even when they do not directly impact resource access. DISCUSSION: Social care programs may impact health through multiple potential pathways. Program impacts seem to be mediated by the extent to which programs increase knowledge of and access to social and health care services and support positive relationships between families and program personnel.

Adjusting Clinical Plans Based on Social Context.

BACKGROUND: Social risk data collection is expanding in community health centers (CHCs). We explored clinicians' practices of adjusting medical care based on their awareness of patients' social risk factors-that is, changes they make to care plans to mitigate the potential impacts of social risk factors on their patients' care and health outcomes-in a set of Texas CHCs. METHODS: Convergent mixed methods. Surveys/interviews explored clinician perspectives on adjusting medical care based on patient social risk factors. Survey data were analyzed with descriptive statistics; interviews were analyzed using thematic analysis and inductive coding. RESULTS: Across 4 CHCs, we conducted 15 clinician interviews and collected 97 surveys. Interviews and surveys overall indicated support for adjustment activities. Two main themes emerged: 1) clinicians reported making frequent adjustments to patient care plans based on their awareness of patients' social contexts, while simultaneously expressing concerns about adjustment; and 2) awareness of patients' social risk factors, and clinician time, training, and experience all influenced clinician adjustments. CONCLUSIONS: Clinicians at participating CHCs described routinely adjusting patient care plans based on their patients' social contexts. These adjustments were being made without specific guidelines or training. Standardization of adjustments may facilitate the contextualization of patient care through shared decision making to improve outcomes.

Development and content validation of a questionnaire to assess the social determinants of mental health in clinical practice.

Introduction: There is growing consensus that consideration of the Social Determinants of Mental Health should be at the centre of mental health care provision. To facilitate this, a validated means to assess mental health service users' social contextual information is arguably needed. We therefore developed a questionnaire to assess the Social Determinants of Mental Health in clinical practice. Methods: Our guideline-informed development consisted of three steps; i) construct and purpose definition, ii) initial item generation based on the literature, similar questionnaires, and a selection of the ICD-10, iii) evaluation, revision, and content validation of the questionnaire. Initially we developed 249 items that were reduced, revised, and validated in several stages to 73 items. Content validation of the questionnaire was achieved through surveys and focus groups including mental health care service users and professionals. Results: The surveys and focus groups indicated the need for a standardised assessment of adverse social factors and highlighted that the benefits of such an assessment would be a more holistic approach to identifying and addressing fundamental factors involved in the development of mental health difficulties. Importantly, this study also revealed how any assessment of the Social Determinants of Mental Health must prioritise the assessed person having a central role in the process and control over their own data. The focus groups identified contradicting recommendations regarding the most suitable context to administer the questionnaire. Discussion: The resulting questionnaire can be considered to be theoretically robust and partially validated. Future research is discussed.

Interventions to reduce inequalities for pregnant women living with disadvantage in high-income countries: an umbrella review protocol.

BACKGROUND: Women who live with disadvantages such as socioeconomic deprivation, substance misuse, poor mental health, or domestic abuse face inequalities in health before, during, and after pregnancy and for their infants through to childhood. Women do not experience these factors alone; they accumulate and interact. Therefore, there is a need for an overview of interventions that work across health and social care and target women at risk of inequalities in maternal or child health. METHODS: Systematic review methodology will be used to identify systematic reviews from high-income countries that describe interventions aiming to reduce inequalities for women who experience social disadvantage during pregnancy. We will describe the range of interventions and their effectiveness in reducing inequalities in maternal or child health. Any individual, hospital, or community-level activity specific to women during the pre-conception, antenatal, or postpartum period up to 1 year after birth will be included, regardless of the setting in which they are delivered. We will search eight electronic databases with the pre-determined search strategy and supplement them with extensive grey literature searches. We will present a narrative synthesis, taking into account the quality assessment and coverage of included studies. DISCUSSION: Inequalities in maternal and child health are a key priority area for national policymakers. Understanding the range and effectiveness of interventions across the perinatal period will inform policy and practice. Identifying gaps in the evidence will inform future research. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42023455502.

Understanding individual health-related social needs in the context of area-level social determinants of health: The case for granularity.

Introduction: Screening for health-related social needs (HRSNs) within health systems is a widely accepted recommendation, however challenging to implement. Aggregate area-level metrics of social determinants of health (SDoH) are easily accessible and have been used as proxies in the interim. However, gaps remain in our understanding of the relationships between these measurement methodologies. This study assesses the relationships between three area-level SDoH measures, Area Deprivation Index (ADI), Social Deprivation Index (SDI) and Social Vulnerability Index (SVI), and individual HRSNs among patients within one large urban health system. Methods: Patients screened for HRSNs between 2018 and 2019 (N = 45,312) were included in the analysis. Multivariable logistic regression models assessed the association between area-level SDoH scores and individual HRSNs. Bivariate choropleth maps displayed the intersection of area-level SDoH and individual HRSNs, and the sensitivity, specificity, and positive and negative predictive values of the three area-level metrics were assessed in relation to individual HRSNs. Results: The SDI and SVI were significantly associated with HRSNs in areas with high SDoH scores, with strong specificity and positive predictive values (∼83% and ∼78%) but poor sensitivity and negative predictive values (∼54% and 62%). The strength of these associations and predictive values was poor in areas with low SDoH scores. Conclusions: While limitations exist in utilizing area-level SDoH metrics as proxies for individual social risk, understanding where and how these data can be useful in combination is critical both for meeting the immediate needs of individuals and for strengthening the advocacy platform needed for resource allocation across communities.

Predictors of social risk for post-ischemic stroke reintegration.

After stroke rehabilitation, patients need to reintegrate back into their daily life, workplace and society. Reintegration involves complex processes depending on age, sex, stroke severity, cognitive, physical, as well as socioeconomic factors that impact long-term outcomes post-stroke. Moreover, post-stroke quality of life can be impacted by social risks of inadequate family, social, economic, housing and other supports needed by the patients. Social risks and barriers to successful reintegration are poorly understood yet critical for informing clinical or social interventions. Therefore, the aim of this work is to predict social risk at rehabilitation discharge using sociodemographic and clinical variables at rehabilitation admission and identify factors that contribute to this risk. A Gradient Boosting modelling methodology based on decision trees was applied to a Catalan 217-patient cohort of mostly young (mean age 52.7), male (66.4%), ischemic stroke survivors. The modelling task was to predict an individual's social risk upon discharge from rehabilitation based on 16 different demographic, diagnostic and social risk variables (family support, social support, economic status, cohabitation and home accessibility at admission). To correct for imbalance in patient sample numbers with high and low-risk levels (prediction target), five different datasets were prepared by varying the data subsampling methodology. For each of the five datasets a prediction model was trained and the analysis involves a comparison across these models. The training and validation results indicated that the models corrected for prediction target imbalance have similarly good performance (AUC 0.831-0.843) and validation (AUC 0.881 - 0.909). Furthermore, predictor variable importance ranked social support and economic status as the most important variables with the greatest contribution to social risk prediction, however, sex and age had a lesser, but still important, contribution. Due to the complex and multifactorial nature of social risk, factors in combination, including social support and economic status, drive social risk for individuals.

Screening for Food and Nutrition Insecurity in the Healthcare Setting: A Cross-Sectional Survey of Non-Medicaid Insured Adults in an Integrated Healthcare Delivery System.

OBJECTIVES: Healthcare screening identifies factors that impact patient health and well-being. Hunger as a Vital Sign (HVS) is widely applied as a screening tool to assess food security. However, there are no common practice screening questions to identify patients who are nutrition insecure or acquire free food from community-based organizations. This study used self-reported survey data from a non-Medicaid insured adult population approximately one year after the start of the COVID-19 pandemic (2021). The survey examined the extent to which the HVS measure might have under-estimated population-level food insecurity and/or nutrition insecurity, as well as under-identified food and nutrition insecurity among patients being screened for social risks in the healthcare setting. METHODS: Data from a 2021 English-only mailed/online survey were analyzed for 2791 Kaiser Permanente Northern California (KPNC) non-Medicaid insured members ages 35-85 years. Sociodemographics, financial strain, food insecurity, acquiring free food from community-based organizations, and nutrition insecurity were assessed. Data from respondents' electronic health records were abstracted to identify adults with diet-related chronic health conditions. Data were weighted to the age × sex × racial/ethnic composition of the 2019 KPNC adult membership. Differences between groups were evaluated for statistical significance using adjusted prevalence ratios (aPRs) derived from modified log Poisson regression models. RESULTS: Overall, 8.5% of participants reported moderate or high food insecurity, 7.7% had acquired free food from community-based organizations, and 13% had nutrition insecurity. Black and Latino adults were significantly more likely than White adults to have food insecurity (17.4% and 13.1% vs 5.6%, aPRs = 2.97 and 2.19), acquired free food from community-based organizations (15.1% and 15.3% vs 4.1%, aPRs = 3.74 and 3.93), nutrition insecurity (22.1% and 23.9% vs 7.9%, aPRs = 2.65 and 2.64), and food and nutrition insecurity (32.4% and 32.5% vs 12.3%, aPRs = 2.54 and 2.44). Almost 20% of adults who had been diagnosed with diabetes, prediabetes, ischemic CAD, or heart failure were food insecure and 14% were nutrition insecure. CONCLUSIONS: Expanding food-related healthcare screening to identify and assess food insecurity, nutrition insecurity, and use of community-based emergency food resources together is essential for supporting referrals that will help patients achieve optimal health.

The role of grid management in community risk governance: a case study in Yuelu, China.

Objective: In this study, we aim to provide a comprehensive analysis of the effectiveness of the risk prevention and control mechanism within the grid management model for community risk prevention. We emphasize the importance of thoroughly examining the risk prevention and control mechanism to enhance risk management efforts in urban communities, particularly in response to unforeseen outbreaks such as COVID-19. Methods: Case studies are widely acknowledged as one of the most effective approaches to examine governance in China. In this study, the "Yuelu Model" serves as an illustrative example to demonstrate the application and effectiveness of grid management in community risk governance. To ensure the validity of the case study, it is imperative to adhere to the principle of representativeness. The collection of case data involves a combination of primary and secondary sources, and supplementary information is obtained through follow-up investigations conducted via WeChat, telephone, and other means, thereby enhancing the comprehensiveness and accuracy of the data. Results: Our analysis reveals significant findings regarding the impact of the grid management model, fulfilling a triple role as a "Social Safety Valve" in the management process: (1) Community stress reduction function, (2) Community alarm function, and (3) Community integration function. Furthermore, we explore the adaptability of the grid management mechanism in addressing community risks, highlighting its effectiveness and potential for broader application. Discussion: The findings of this study suggest that: Firstly, it is crucial to establish a shared information repository among different departments on a big data platform. Secondly, a dynamic government public information internal network should be established through collaborative efforts among multiple departments. Thirdly, implementing a regular (or periodic) early warning mechanism is essential. Lastly, the establishment of a high-quality talent team for power grid management is highly recommended. Our research provides valuable insights to enhance community risk governance.

Assessing New York City's COVID-19 Vaccine Rollout Strategy: A Case for Risk-Informed Distribution.

This study reviews the impact of eligibility policies in the early rollout of the COVID-19 vaccine on coverage and probable outcomes, with a focus on New York City. We conducted a retrospective ecological study assessing age 65+, area-level income, vaccination coverage, and COVID-19 mortality rates, using linked Census Bureau data and New York City Health administrative data aggregated at the level of modified zip code tabulation areas (MODZCTA). The population for this study was all individuals in 177 MODZCTA in New York City. Population data were obtained from Census Bureau and New York City Health administrative data. The total mortality rate was examined through an ordinary least squares (OLS) regression model, using area-level wealth, the proportion of the population aged 65 and above, and the vaccination rate among this age group as predictors. Low-income areas with high proportions of older people demonstrated lower coverage rates (mean vaccination rate 52.8%; maximum coverage 67.9%) than wealthier areas (mean vaccination rate 74.6%; maximum coverage 99% in the wealthiest quintile) in the first 3 months of vaccine rollout and higher mortality over the year. Despite vaccine shortages, many younger people accessed vaccines ahead of schedule, particularly in high-income areas (mean coverage rate 60% among those 45-64 years in the wealthiest quintile). A vaccine program that prioritized those at greatest risk of COVID-19-associated morbidity and mortality would have prevented more deaths than the strategy that was implemented. When rolling out a new vaccine, policymakers must account for local contexts and conditions of high-risk population groups. If New York had focused limited vaccine supply on low-income areas with high proportions of residents 65 or older, overall mortality might have been lower.

Trajectories and correlates of mental health among urban, school-age children during the COVID-19 pandemic: a longitudinal study.

BACKGROUND: The COVID-19 pandemic posed numerous obstacles to psychosocial wellbeing for children. We conducted a longitudinal study to evaluate child mental health and social risks during the pandemic. METHODS: Participants were 172 caregivers of children aged 6-11 years old who attended well child visits within 6 months before pandemic onset at an urban safety net hospital in the US. Prepandemic data was extracted from the electronic medical record, and surveys were administered at three time points between August 2020 and July 2021. We measured mental health symptoms with the Pediatric Symptom Checklist-17, social risks (e.g., food and housing insecurity) with the THRIVE questionnaire, and school modality (in-person, hybrid, remote). RESULTS: Compared to pre-pandemic, children had significantly higher PSC-17 total scores (overall mental health symptoms) and THRIVE total scores (total burden of social risks) at all three mid-pandemic waves. Using longitudinal mixed models accounting for time, social risks, and school modality, both social risks (B = 0.37, SE = 0.14, p < 0.01) and school modality were significantly associated with PSC-17 scores (B = - 1.95, SE = 0.63, p < 0.01). Children attending in-person school had fewer mental health symptoms than those attending remote or hybrid school. CONCLUSION: Mental health symptoms and social risks remained significantly higher fifteen months after the onset of the COVID-19 pandemic compared to prepandemic. In-person attendance at school appeared protective against persistently elevated mental health symptoms.

The relationship between community social risk factors and regional hospital-reported cash, negotiated, and chargemaster prices for 14 common services.

BACKGROUND: Social risk factors are key drivers of the geographic variation in spending in the United States but little is known how community-level social risk factors are associated with hospital prices. Our objective was to describe the relationship between regional hospital-reported prices and social risk factors by price type (chargemaster, cash, commercial, Medicare, and Medicaid). METHODS: This cross-sectional analysis used newly available hospital-reported prices from acute general hospitals in 2022. The prices were for 14 common services. Prices were winsorized at 98%, wage index-adjusted, standardized by service, and aggregated to hospital service areas (HSAs). For social risk, we used 23 measures across 5 domains of social risk (socioeconomic position; race, ethnicity, and culture; gender; social relationships; and residential and community context). Spearman's correlation was used to estimate associations between median prices and social risk by price type. RESULTS: Prices were reported from 2,386 acute general hospitals in 45% (1,502 of 3,436) HSAs. Correlations between regional prices and other social risk factors varied by price type (range: -0.19 to 0.31). Chargemaster and cash prices were significantly correlated with the most community characteristics (10 of 23, 43%) followed by commercial prices (8, 35%). Medicare and Medicaid prices were only significantly correlated with 1 measure (all p < 0.01). All price types were significantly correlated with the percentage of uninsured (all p < 0.01). Chargemaster, cash, and commercial prices were positively correlated with percentage of Hispanic residents, residents with limited English proficiency, and non-citizens (all p < 0.05). CONCLUSIONS: While regional correlations between prices and social risk factors were weak across all prices, chargemaster, cash, and commercial prices were more like closely aligned with community-level social risk factors than the two public payers (Medicare and Medicaid). Chargemaster, cash, and commercial hospital prices appeared to be higher in socially disadvantaged communities. Further research is needed to clarify the relationship between prices and community social risk factors.

Identifying individual social needs during intake for diabetes Self-Management education and support services in the Detroit, Michigan area.

The American Diabetes Association has recommended that diabetes self-management education and support (DSMES) teams improve diabetes outcomes by identifying and responding to patients' social needs. This study examines demographic patterns in how hemoglobin A1c (A1c) is related to individual social needs, reported urgency of those needs, and interest in obtaining assistance. A total of 1125 unique persons who had been referred for DSMES and had completed a social needs screener via our electronic medical record were included. The majority (51.9 %) had an A1c < 8 % at their most recent assessment and most respondents (52.5 %) reported having at least 1 unmet social need (n = 591), Those who reported having at least 1 social need, tended to have higher A1c levels compared with those who reported no social needs (median of 8.0 % versus 7.7 %; p < 0.05). Among Black individuals the associations were stronger (median A1c of 8.2 % among those with versus 7.2 % among those without a reported social need; p < 0.05). However, among White individuals, there was no difference in A1c between these two groups. Among those who reported a social need, those who also reported they needed assistance (35.7 %) tended to have higher A1c levels than those who did not (median 8.3 % versus 7.8 %; p < 0.10). This relationship did not vary by race. Ongoing study of the relationship between unmet social needs and glycemic control is warranted to help identify effective clinical workflows to help providers incorporate consideration of social needs into their medical decision making.

Realizing the Potential of Social Determinants Data: A Scoping Review of Approaches for Screening, Linkage, Extraction, Analysis and Interventions.

Background: Social determinants of health (SDoH) like socioeconomics and neighborhoods strongly influence outcomes, yet standardized SDoH data is lacking in electronic health records (EHR), limiting research and care quality. Methods: We searched PubMed using keywords "SDOH" and "EHR", underwent title/abstract and full-text screening. Included records were analyzed under five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions. Results: We identified 685 articles, of which 324 underwent full review. Key findings include tailored screening instruments implemented across settings, census and claims data linkage providing contextual SDoH profiles, rule-based and neural network systems extracting SDoH from notes using NLP, connections found between SDoH data and healthcare utilization/chronic disease control, and integrated care management programs executed. However, considerable variability persists across data sources, tools, and outcomes. Discussion: Despite progress identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical to fulfill the potential of SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

Social Risk Factors and Racial and Ethnic Disparities in Health Care Resource Utilization Among Medicare Advantage Beneficiaries With Psychiatric Disorders.

The intersection of social risk and race and ethnicity on mental health care utilization is understudied. This study examined disparities in health care treatment, adjusting for clinical need, among 25,780 Medicare Advantage beneficiaries with a diagnosis of a psychiatric disorder. We assessed contributions to disparities from racial and ethnic differences in the composition and returns of social risk variables. Black and Hispanic beneficiaries had lower rates of mental health outpatient visits than Whites. Assessing composition, Black and Hispanic beneficiaries experienced greater financial, food, and housing insecurity than White beneficiaries, factors associated with greater mental health treatment. Assessing returns, food insecurity was associated with an exacerbation of Hispanic-White disparities. Health care systems need to address the financial, food and housing insecurity of racial and ethnic minority groups with psychiatric disorder. Accounting for racial and ethnic differences in social risk adjustment-based payment reforms has significant implications for provider reimbursement and outcomes.

The social determinants of mental health and disorder: evidence, prevention and recommendations.

People exposed to more unfavourable social circumstances are more vulnerable to poor mental health over their life course, in ways that are often determined by structural factors which generate and perpetuate intergenerational cycles of disadvantage and poor health. Addressing these challenges is an imperative matter of social justice. In this paper we provide a roadmap to address the social determinants that cause mental ill health. Relying as far as possible on high-quality evidence, we first map out the literature that supports a causal link between social determinants and later mental health outcomes. Given the breadth of this topic, we focus on the most pervasive social determinants across the life course, and those that are common across major mental disorders. We draw primarily on the available evidence from the Global North, acknowledging that other global contexts will face both similar and unique sets of social determinants that will require equitable attention. Much of our evidence focuses on mental health in groups who are marginalized, and thus often exposed to a multitude of intersecting social risk factors. These groups include refugees, asylum seekers and displaced persons, as well as ethnoracial minoritized groups; lesbian, gay, bisexual, transgender and queer (LGBTQ+) groups; and those living in poverty. We then introduce a preventive framework for conceptualizing the link between social determinants and mental health and disorder, which can guide much needed primary prevention strategies capable of reducing inequalities and improving population mental health. Following this, we provide a review of the evidence concerning candidate preventive strategies to intervene on social determinants of mental health. These interventions fall broadly within the scope of universal, selected and indicated primary prevention strategies, but we also briefly review important secondary and tertiary strategies to promote recovery in those with existing mental disorders. Finally, we provide seven key recommendations, framed around social justice, which constitute a roadmap for action in research, policy and public health. Adoption of these recommendations would provide an opportunity to advance efforts to intervene on modifiable social determinants that affect population mental health.