Moving Beyond International Classification of Diseases Codes for the Retrospective Identification of Gender Diverse Veterans.

Purpose: The Veterans Health Administration (VHA) systematically asks Veterans to self-report gender identity for documentation in their electronic health record. Veterans with transgender and gender diverse (TGD) identities experience higher rates of several health conditions compared to Veterans without minoritized gender identities. Historically, cohorts of TGD Veterans were built with International Classification of Diseases Version 10 (ICD-10) codes assigned during clinical encounters. We examined concordance between self-reported gender identity and relevant ICD-10 codes in VHA health records to inform use of these indicators for examining the health needs of TGD Veterans. Methods: TGD-related ICD-10 codes were compared to self-reported gender identity from more than 1.5 million Veterans (2019-2022). Results: Only 34% of TGD Veterans included through self-report had an ICD-10 code associated with transgender care. ICD-10 codes had low sensitivity and high specificity compared to self-reported gender. Conclusion: These findings suggest ICD-10 codes alone undercount the larger population of TGD Veterans in the VHA.

Food Insecurity Prevalence and Risk Factors at a Large Academic Medical Center in Michigan.

Importance: Health care systems are increasingly adopting methods to screen for and integrate food insecurity and other social risk factors into electronic health records. However, there remain knowledge gaps regarding the cumulative burden of food insecurity in large clinical settings, which patients are most at risk, and the extent to which patients are interested in social assistance through their health care system. Objective: To evaluate the 5-year prevalence and associated risk factors of food insecurity among adult primary care patients, and to examine factors associated with patients' interest in social assistance among those with food insecurity. Design, Setting, and Participants: This cross-sectional analysis of a retrospective cohort study took place at a tertiary care academic medical center (encompassing 20 primary care clinics) in Michigan. Participants included adult patients who completed screening for social risk factors between August 1, 2017, and August 1, 2022. Data analysis was performed from November 2022 to June 2023. Exposure: Food insecurity was assessed using the Hunger Vital Sign. Main Outcomes and Measures: The primary outcome was patients' interest in social assistance, and associated factors were examined using multivariate logistic regression models, adjusting for patients' demographic and health characteristics. Results: Over the 5-year period, 106 087 adult primary care patients (mean [SD] age, 52.9 [17.9] years; 61 343 women [57.8%]) completed the standardized social risk factors questionnaire and were included in the analysis. The overall prevalence of food insecurity was 4.2% (4498 patients), with monthly trends ranging from 1.5% (70 positive screens) in August 2018 to 5.0% (193 positive screens) in June 2022. Food insecurity was significantly higher among patients who were younger, female, non-Hispanic Black or Hispanic, unmarried or unpartnered, and with public health insurance. Food insecurity was significantly associated with a higher cumulative burden of social needs, including social isolation, medical care insecurity, medication nonadherence, housing instability, and lack of transportation. Only 20.6% of patients with food insecurity (927 patients) expressed interest in social assistance. Factors associated with interest in social assistance including being non-Hispanic Black, unmarried or unpartnered, a current smoker, and having a higher burden of other social needs. Conclusions and Relevance: In this retrospective cohort study, the overall prevalence of food insecurity was 4.2%, of whom approximately 1 in 5 patients with food insecurity expressed interest in assistance. This study highlights ongoing challenges in ensuring all patients complete routine social determinants of health screening and gaps in patients' interest in assistance for food insecurity and other social needs through their health care system.

Participation of Veterans Affairs Medical Centers in veteran-centric community-based service navigation networks: A mixed methods study.

OBJECTIVE: To understand the determinants and benefits of cross-sector partnerships between Veterans Affairs Medical Centers (VAMCs) and geographically affiliated AmericaServes Network coordination centers that address Veteran health-related social needs. DATA SOURCES AND SETTING: Semi-structured interviews were conducted with AmericaServes and VAMC staff across seven regional networks. We matched administrative data to calculate the percentage of AmericaServes referrals that were successfully resolved (i.e., requested support was provided) in each network overall and stratified by whether clients were also VAMC patients. STUDY DESIGN: Convergent parallel mixed-methods study guided by Himmelman's Developmental Continuum of Change Strategies (DCCS) for interorganizational collaboration. DATA COLLECTION: Fourteen AmericaServes staff and 17 VAMC staff across seven networks were recruited using snowball sampling and interviewed between October 2021 and April 2022. Rapid qualitative analysis methods were used to characterize the extent and determinants of VAMC participation in networks. PRINCIPAL FINDINGS: On the DCCS continuum of participation, three networks were classified as networking, two as coordinating, one as cooperating, and one as collaborating. Barriers to moving from networking to collaborating included bureaucratic resistance to change, VAMC leadership buy-in, and not having VAMCs staff use the shared technology platform. Facilitators included ongoing communication, a shared mission of serving Veterans, and having designated points-of-contact between organizations. The percentage of referrals that were successfully resolved was lowest in networks engaged in networking (65.3%) and highest in cooperating (85.6%) and collaborating (83.1%) networks. For coordinating, cooperating, and collaborating networks, successfully resolved referrals were more likely among Veterans who were also VAMC patients than among Veterans served only by AmericaServes. CONCLUSIONS: VAMCs participate in AmericaServes Networks at varying levels. When partnerships are more advanced, successful resolution of referrals is more likely, especially among Veterans who are dually served by both organizations. Although challenges to establishing partnerships exist, this study highlights effective strategies to overcome them.

Screening for Financial Hardship: Comparing Patient Survey Responses Using Two Different Screening Tools.

BACKGROUND: Healthcare delivery organizations are increasingly screening patients for social risks using tools that vary in content and length. OBJECTIVES: To compare two screening tools both containing questions related to financial hardship. DESIGN: Cross-sectional survey. PARTICIPANTS: Convenience sample of adult patients (n = 471) in three primary care clinics. MAIN MEASURES: Participants randomly assigned to self-complete either: (1) a screening tool developed by the Centers for Medicare & Medicaid Services (CMS) consisting of six questions on financial hardship (housing stability, housing quality, food security, transportation security, utilities security); or (2) social and behavioral risk measures recommended by the National Academy of Medicine (NAM), including one question on financial hardship (financial strain). We compared patient acceptability of screening, positive screening rates for financial hardship, patient interest in assistance, and self-rated health. RESULTS: Ninety-one percent of eligible/interested patients completed the relevant survey questions to be included in the study (N = 471/516). Patient acceptability was high for both tools, though more participants reported screening was appropriate when answering the CMS versus NAM questions (87% vs. 79%, p = 0.02). Of respondents completing the CMS tool, 57% (132/232) reported at least one type of financial hardship; on the NAM survey, 52% (125/239) reported financial hardship (p = 0.36). Nearly twice as many respondents indicated interest in assistance related to financial hardship after completing items on the CMS tool than on the NAM question (39% vs. 21%, p < 0.01). CONCLUSIONS: Patients reported high acceptability of both social risk assessment tools. While rates of positive screens for financial hardship were similar across the two measures, more patients indicated interest in assistance after answering questions about financial hardship on the CMS tool. This might be because the screening questions on the CMS tool help patients to appreciate the types of assistance related to financial hardship that may be available after screening. Future research should assess the validity and comparative validity of individual measures and measure sets. Tool selection should be based on setting and population served, screening goals, and resources available.

Developing a brief assessment of social risks for the Veterans Health Administration Survey of Healthcare Experiences of Patients.

OBJECTIVE: To determine whether a 6- or 12-month look-back period affected rates of reported social risks in a social risk survey for use in the Veterans Health Administration and to assess associations of social risks with overall health and mental health. STUDY DESIGN: Cross-sectional survey of respondents randomized to 6- or 12-month look-back period. DATA SOURCES AND STUDY SETTING: Online survey with a convenience sample of Veterans in June and July 2021. DATA COLLECTION/EXTRACTION METHODS: Veteran volunteers were recruited by email to complete a survey assessing social risks, including financial strain, adult caregiving, childcare, food insecurity, housing, transportation, internet access, loneliness/isolation, stress, discrimination, and legal issues. Outcomes included self-reported overall health and mental health. Chi-squared tests compared the prevalence of reported social risks between 6- and 12-month look-back periods. Spearman correlations assessed associations among social risks. Bivariate and multivariable logistic regression models estimated associations between social risks and fair/poor overall and mental health. PRINCIPAL FINDINGS: Of 3418 Veterans contacted, 1063 (31.10%) responded (87.11% male; 85.61% non-Hispanic White; median age = 70, interquartile range [IQR] = 61-74). Prevalence of most reported social risks did not significantly differ by look-back period. Most social risks were weakly intercorrelated (median |r| = 0.24, IQR = 0.16-0.31). Except for legal issues, all social risks were associated with higher odds of fair/poor overall health and mental health in bivariate models. In models containing all significant social risks from bivariate models, adult caregiving and stress remained significant predictors of overall health; food insecurity, housing, loneliness/isolation, and stress remained significant for mental health. CONCLUSIONS: Six- and 12-month look-back periods yielded similar rates of reported social risks. Although most individual social risks are associated with fair/poor overall and mental health, when examined together, only adult caregiving, stress, loneliness/isolation, food, and housing remain significant.

Food Insecurity and Suicidal Ideation: Results from a National Longitudinal Study of Military Veterans.

OBJECTIVE: Research examining social determinants of suicide risk in veterans suggests a potential link between food insecurity and subsequent suicidal ideation in military veterans. The objective of this study is to investigate, if and how, food insecurity predicts subsequent suicidal ideation in a nationally representative longitudinal survey of veterans. METHODS: A national longitudinal survey was analyzed of participants randomly drawn from over one million U.S. military service members who served after September 11, 2001. N = 1,090 veterans provided two waves of data one year apart (79% retention rate); the final sample was representative of post-9/11 veterans in all 50 states and all military branches. RESULTS: Veterans with food insecurity had nearly four times higher suicidal ideation one year later compared to veterans not reporting food insecurity (39% vs 10%). In multivariable analyses controlling for demographic, military, and clinical covariates, food insecurity (OR = 2.37, p =.0165) predicted suicidal ideation one year later, as did mental health disorders (OR = 2.12, p = .0097). Veterans with both food insecurity and mental health disorders had a more than nine-fold increase in predicted probability of suicidal ideation in the subsequent year compared to veterans with neither food insecurity nor mental health disorders (48.5% vs. 5.5%). CONCLUSION: These findings identify food insecurity as an independent risk marker for suicidal ideation in military veterans in addition to mental disorders. Food insecurity is both an indicator of and an intervention point for subsequent suicide risk. Regularly assessing for food insecurity, and intervening accordingly, can provide upstream opportunities to reduce odds of suicide among veterans.HIGHLIGHTSMilitary veterans with food insecurity were at elevated risk of suicidal ideation.Veterans with mental health disorders had higher odds of suicidal ideation one year later.Food insecurity plus mental health disorders led to a substantial increase in suicidal ideation.

Implementing a Social Needs Screening and Referral Program Among Veterans: Assessing Circumstances & Offering Resources for Needs (ACORN).

BACKGROUND: The Department of Veterans Affairs (VA) healthcare system routinely screens Veterans for food insecurity, housing instability, and intimate partner violence, but does not systematically screen for other health-related social needs (HRSNs). OBJECTIVES: To (1) develop a process for systematically identifying and addressing Veterans' HRSNs, (2) determine reported prevalence of HRSNs, and (3) assess the acceptability of HRSN screening among Veterans. DESIGN: "Assessing Circumstances and Offering Resources for Needs" (ACORN) is a Veteran-tailored HRSN screening and referral quality improvement initiative. Veterans were screened via electronic tablet for nine HRSNs (food, housing, utilities, transportation, legal needs, social isolation, interpersonal violence, employment, and education) and provided geographically tailored resource guides for identified needs. Two-week follow-up interviews with a purposive sample of Veterans explored screening experiences. PARTICIPANTS: Convenience sample of Veterans presenting for primary care at a VA urban women's health clinic and suburban community-based outpatient clinic (October 2019-May 2020). MAIN MEASURES: Primary outcomes included prevalence of HRSNs, Veteran-reported acceptability of screening, and use of resources guides. Data were analyzed using descriptive statistics, chi-square tests, and rapid qualitative analysis. KEY RESULTS: Of 268 Veterans screened, 50% reported one or more HRSNs. Social isolation was endorsed most frequently (29%), followed by educational needs (19%), interpersonal violence (12%), housing instability (9%), and utility concerns (7%). One in five Veterans reported at least one form of material hardship. In follow-up interviews (n = 15), Veterans found screening acceptable and felt VA should continue screening. No Veterans interviewed had contacted recommended resources at two-week follow-up, although several planned to use resource guides in the future. CONCLUSION: In a VA HRSN screening and referral program, Veterans frequently reported HRSNs, felt screening was important, and thought VA should continue to screen for these needs. Screening for HRSNs is a critical step towards connecting patients with services, identifying gaps in service delivery, and informing future resource allocation.

Assessing an electronic self-report method for improving quality of ethnicity and race data in the Veterans Health Administration.

Objective: Evaluate self-reported electronic screening (eScreening) in a VA Transition Care Management Program (TCM) to improve the accuracy and completeness of administrative ethnicity and race data. Materials and Methods: We compared missing, declined, and complete (neither missing nor declined) rates between (1) TCM-eScreening (ethnicity and race entered into electronic tablet directly by patient using eScreening), (2) TCM-EHR (Veteran-completed paper form plus interview, data entered by staff), and (3) Standard-EHR (multiple processes, data entered by staff). The TCM-eScreening (n = 7113) and TCM-EHR groups (n = 7113) included post-9/11 Veterans. Standard-EHR Veterans included all non-TCM Gulf War and post-9/11 Veterans at VA San Diego (n = 92 921). Results: Ethnicity: TCM-eScreening had lower rates of missingness than TCM-EHR and Standard-EHR (3.0% vs 5.3% and 8.6%, respectively, P < .05), but higher rates of "decline to answer" (7% vs 0.5% and 1.2%, P < .05). TCM-EHR had higher data completeness than TCM-eScreening and Standard-EHR (94.2% vs 90% and 90.2%, respectively, P < .05). Race: No differences between TCM-eScreening and TCM-EHR for missingness (3.5% vs 3.4%, P > .05) or data completeness (89.9% vs 91%, P > .05). Both had better data completeness than Standard-EHR (P < .05), which despite the lowest rate of "decline to answer" (3%) had the highest missingness (10.3%) and lowest overall completeness (86.6%). There was strong agreement between TCM-eScreening and TCM-EHR for ethnicity (Kappa = .92) and for Asian, Black, and White Veteran race (Kappas = .87 to .97), but lower agreement for American Indian/Alaska Native (Kappa = .59) and Native Hawaiian/Other Pacific Islander (Kappa = .50) Veterans. Conculsions: eScreening is a promising method for improving ethnicity and race data accuracy and completeness in VA.

Predictors of Interest in Offered Social Care Assistance Among People with Uncontrolled Diabetes.

Despite increasing resources dedicated to identifying and addressing social risks in health care settings, many patients screening positive for social risks either decline assistance or do not follow up with offered resources. This study assessed predictors of engagement with offered social care assistance through guided self-navigation or in-person assistance. Data came from a cross-sectional analysis of 6-month follow-up survey data from an ongoing trial of participants with poorly controlled diabetes and a positive social risk screen randomized to guided online self-navigation or in-person social care assistance. Multivariable logistic regression models estimated participant characteristics associated with engagement with offered assistance. Mean age was 55 years (standard deviation = 12). Of 407 participants, 41% (n = 165) engaged with offered assistance: 76% (n = 137) of those in the guided self-navigation arm and 13% (n = 28) of those in the in-person assistance arm. A sizable proportion of participants endorsed already using assistance for medications (30%), food (26%), and employment (22%). Female gender [OR 1.57, 95% CI (1.03-2.40), P < 0.05] and being out of the workforce [OR 1.71, 95% CI (1.07-2.73), P < 0.05] predicted engagement with social care assistance. Those already using assistance for medications [OR 4.71, 95% CI (1.69-13.15), P < 0.05] and blood glucose supplies [OR 6.25, 95% CI (1.45-26.78) P < 0.05] were also more likely to engage with offered assistance. Fewer than half of individuals engaged with offered social assistance through either guided online self-navigation or in-person assistance; limited demographic and clinical factors predicted uptake. More investments are needed to understand how best to support uptake of offered assistance.

Motivators, Barriers, and Preferences to Engagement With Offered Social Care Assistance Among People With Diabetes: A Mixed Methods Study.

INTRODUCTION: A substantial proportion of patients screening positive for social risks either decline assistance or do not follow-up with offered resources. This study examined patient interest in and engagement with offered social care assistance among adults with poorly controlled diabetes at an academic medical center. METHODS: Surveys (n=307) and purposively sampled follow-up interviews (n=40) were conducted 6 months after randomization to receive guided online self-navigation or in-person assistance to address unmet social needs. Integrated mixed methods (data collected in 2019-2021) explored the motivators, barriers, and preferences regarding the uptake of offered assistance. Results were analyzed in 2021 using descriptive statistics, rapid qualitative analysis, and joint display models. RESULTS: A total of 77% of people randomized to online self-navigation and 14% randomized to in-person assistance engaged with offered assistance. Motivators for engagement were similar across groups and included ease of use, anticipating assistance that could address 1 or more needs, and interest in learning more about available resources. Barriers to engagement included not needing or desiring assistance, participants perceiving that offered assistance was not relevant to their needs or that they would not qualify, competing priorities/forgetting, previous negative experiences or stigma, and technology or access challenges (online self-navigation group). Preferences around offered assistance that directly addressed barriers to uptake included changing messaging and framing around offered help and the ability to tailor modalities. CONCLUSIONS: There are key barriers to the use of social care assistance that may directly reflect the process by which individuals are screened and offered assistance. Strategies to increase uptake should be patient centered and ideally provide multiple options for type of assistance and mode of engagement.

Temporal variation in individual social risk factors associated with testing positive for SARS-CoV-2 among veterans in the veterans health administration.

PURPOSE: Marginalized communities have been disproportionally impacted by SARS-CoV-2. How the associations between social determinants of health and the risk of SARS-CoV-2 infection shifted across time is unknown. In this evaluation, we examine individual-level social determinants of health as social risk factors for SARS-CoV-2 infection across the first 12 months of the pandemic among US Veterans. METHODS: We conducted a retrospective cohort analysis of 946,358 Veterans who sought testing or treatment for SARS-CoV-2 infection in U.S. Department of Veterans Affairs medical facilities. We estimated risk ratios for testing positive by social risk factors, adjusting for demographics, comorbidities, and time. Adjusted models were stratified by pandemic phase to assess temporal fluctuations in social risks. RESULTS: Approximately 19% of Veterans tested positive for SARS-CoV-2. Larger household size was a persistent risk factor and this association increased over time. Early in the pandemic, lower county-level population density was associated with lower SARS-CoV-2 infection risk, but between June 1 and August 31, 2020, this trend reversed. CONCLUSIONS: Temporal fluctuations in social risks associated with Veterans' SARS-CoV-2 infection suggest the need for ongoing, real-time tracking as the social and medical environment continues to evolve.

Leveraging Integrated Primary Care to Address Patients' and Families' Unmet Social Needs: Aligning Practice with National Academy of Sciences, Engineering and Medicine Recommendations.

Primary care is well-poised to address unmet social needs that affect health. Integrated primary care is increasingly common and can be leveraged to facilitate identification of practice and clinician-level modifiable characteristics and assist practices to address unmet social needs for patients and families. A recent National Academies of Sciences, Engineering, and Medicine (NASEM)'s consensus report identified 5 critical system-level activities to facilitate the integration of addressing social needs into health care: awareness (ask patients), adjustment (flexible intervention delivery), assistance (intervention to address the social need), alignment (link with community resources), and advocacy (policy change). This article outlines how integrated primary care characteristics, such as routine screening, functional workflows, interprofessional team communication, and patient-centered practices, exemplify the NASEM report's activities and offer robust biopsychosocial tools for addressing social needs. We provide a case to illustrate how these strategies might be used in practice.

Adaptation of a social risk screening and referral initiative across clinical populations, settings, and contexts in the Department of Veterans Affairs Health System.

Identifying and addressing social risks and social needs in healthcare settings is an important step towards achieving health equity. Assessing Circumstances and Offering Resources for Needs (ACORN) is a Department of Veterans Affairs (VA) social risk screening and referral model that aims to systematically identify and address social needs. Since initial piloting in 2018, our team has collaborated with clinical and operations partners to implement ACORN across multiple VA clinical settings while adapting and tailoring the initiative to meet the needs of different populations, specialties, and individuals administering screening. Given ACORN's complexity as a growing initiative with multiple partners and frequent real-time modifications within a large national healthcare system, we recognized a need to systematically document the rationale and process of adaptations over time. We looked to three implementation frameworks-RE-AIM, the Adaptome, and FRAME-to describe the rationale for adaptations, the nature of and context within which adaptations were made, and the details of each adaptation. In this manuscript, we uniquely interweave these three frameworks to document adaptations to ACORN across diverse VA clinical settings, with a focus on how adaptations support the promotion of heath equity in the Veteran population.

Risk factors for Veteran food insecurity: findings from a National US Department of Veterans Affairs Food Insecurity Screener.

OBJECTIVE: Food insecurity is associated with numerous adverse health outcomes. The US Veterans Health Administration (VHA) began universal food insecurity screening in 2017. This study examined prevalence and correlates of food insecurity among Veterans screened. DESIGN: Retrospective cross-sectional study using VHA administrative data. Multivariable logistic regression models were estimated to identify sociodemographic and medical characteristics associated with a positive food insecurity screen. SETTING: All US Veterans Administration (VA) medical centres (n 161). PARTICIPANTS: All Veterans were screened for food insecurity since screening initiation (July 2017-December 2018). RESULTS: Of 3 304 702 Veterans screened for food insecurity, 44 298 were positive on their initial screen (1·3 % of men; 2·0 % of women). Food insecurity was associated with identifying as non-Hispanic Black or Hispanic. Veterans who were non-married/partnered, low-income Veterans without VA disability-related compensation and those with housing instability had higher odds of food insecurity, as did Veterans with a BMI < 18·5, diabetes, depression and post-traumatic stress disorder. Prior military sexual trauma (MST) was associated with food insecurity among both men and women. Women screening positive, however, were eight times more likely than men to have experienced MST (48·9 % v. 5·9 %). CONCLUSIONS: Food insecurity was associated with medical and trauma-related comorbidities as well as unmet social needs including housing instability. Additionally, Veterans of colour and women were at higher risk for food insecurity. Findings can inform development of tailored interventions to address food insecurity such as more frequent screening among high-risk populations, onsite support applying for federal food assistance programs and formal partnerships with community-based resources.

The Long-Term Effect of Food Insecurity During College on Future Food Insecurity.

INTRODUCTION: Food insecurity has been associated with adverse health and academic outcomes among college students. However, little is known about the long-term impacts of experiencing food insecurity during college. This study examines the impacts of college food insecurity (measured from 1999 to 2003) on future food insecurity (measured from 2015 to 2017) and whether this association differs by economic independence during college. METHODS: Data came from 1,508 participants in the Panel Study of Income Dynamics, the longest-running and nationally representative panel survey. Household food security was assessed using the 18-item U.S. Household Food Security Survey Module during college enrollment in 1999-2003 and again during adulthood in 2015-2017. Generalized linear models were used to examine the impacts of college food insecurity on food insecurity in adulthood, adjusting for individual- and family-level sociodemographic characteristics. Data analysis was conducted in 2020-2021. RESULTS: After multivariable adjustment, college food insecurity was associated with an increased prevalence of food insecurity in adulthood (prevalence ratio=1.45, 95% CI=1.16, 1.81). This association was more pronounced among students who were economically independent from their parents during college (prevalence ratio=2.23, 95% CI=1.27, 3.90). CONCLUSIONS: Food insecurity during college is associated with a higher prevalence of food insecurity in early to middle adulthood, particularly among economically independent students. Given the seemingly cyclical nature of food insecurity over the life course, policies are needed to alleviate food insecurity during the critical college years.

Implementation of Health-Related Social Needs Screening at Michigan Health Centers: A Qualitative Study.

PURPOSE: Federally qualified health centers (FQHCs) are leaders in screening for and addressing patient's health-related social needs but variation exists in screening practices. This variation is relatively unexplored, particularly the influences of organizational and state policies. We employed a qualitative descriptive approach to study social needs screening practices at Michigan FQHCs to characterize screening processes and identify drivers of variation in screening implementation. METHODS: Site visits and semistructured interviews were conducted from October 2016 through March 2017, to explore implementation of social needs screening in clinical practice. Five FQHCs were selected through maximum variation sampling. Within each site, snowball sampling identified care team members highly knowledgeable about social needs screening. We conducted 4 to 5 interviews per site. Transcripts were analyzed using a thematic approach. RESULTS: We interviewed 23 participants from 5 sites; these sites varied by geography, age distribution, and race/ethnicity. We identified 4 themes: (1) statewide initiatives and local leadership drove variation in screening practices; (2) as community health workers (CHWs) played an integral role in identifying patients' needs, their roles often shifted from that of screener to implementer; (3) social needs screening data was variably integrated into electronic health records and infrequently used for population health management; and (4) sites experienced barriers to social needs screening that limited the perceived impact and sustainability. CONCLUSIONS: FQHCs placed value on the role of CHWs, on sustainable initiatives, and on funding to support continued social needs screening in primary care settings.

Screening for Interpersonal Violence: Missed Opportunities and Potential Harms.

INTRODUCTION: Screening for interpersonal violence is used in healthcare settings to identify patients experiencing violence. However, using unvalidated screening tools may misclassify patients' experience with violence. The Center for Medicare & Medicaid Innovation adapted a previously validated intimate partner violence screening tool for use in assessing interpersonal violence and retained the tool's original scoring rubric, despite the new tool's broader scope. This study evaluates the scoring system for detecting safety concerns. METHODS: This was a cross-sectional survey of a convenience sample of adult patients and caregivers of pediatric patients at 7 primary care clinics and 4 emergency departments (2018-2019). Surveys included the adapted 4-item Hurt Insult Threat Scream tool. Questions are scored by frequency on a Likert scale (1=never; 5=frequently). Scores of 11-20 are considered positive for safety concerns. Two-sided Fisher's exact tests were used for descriptive analyses. Data analyses occurred in 2019-2020. RESULTS: Of 1,014 participants, 66 (6.5%) reported any frequency of physical violence. Of these, 54 (81.8%) did not reach the threshold score of 11. Of the 1,014 participants, 93 (9.2%) reported any frequency of physical violence or being threatened with harm; 76 of 93 participants (81.7%) scored <11. CONCLUSIONS: Using the original scoring criteria for the adapted Hurt Insult Threat Scream, >80% of participants reporting physical violence did not screen positive for potential safety concerns. The scoring criteria did not reliably identify participants experiencing or at high risk for violence. To improve patient safety, the adapted Hurt Insult Threat Scream scoring rubric should be updated on the basis of stakeholder input and additional validation studies.

An Exploratory Framework to Interpret County-Level Indicators of Food Insecurity.

In 2017, 12.5% of the population was estimated to be food insecure (FI) with wide regional variation. County-level FI is closely associated with, but likely more complex, than the county-level poverty rates. Therefore, we sought to identify a more nuanced framework for understanding factors contributing to FI. In an exploratory design, we studied 32 counties stratified by high and low FI and poverty, which were defined in terms of the national averages. Once stratified, counties were analyzed across 14 metrics within four summary domains: food access, food affordability, overall health environment, and county innovation. Having a stronger health environment was correlated with lower FI; correlations between the remaining three summary domains and FI were not significant. This was an initial effort to conceptualize potential markers of FI into a coherent framework using publicly available population-level health metrics. Future research could expand the sample and add additional metrics.

Screening Discordance and Characteristics of Patients With Housing-Related Social Risks.

INTRODUCTION: Healthcare systems are increasingly interested in identifying patients' housing-related risks, but minimal information exists to inform screening question selection. The primary study aim is to evaluate discordance among 5 housing-related screening questions used in health care. METHODS: This was a cross-sectional multisite survey of social risks used in a convenience sample of adults seeking care for themselves or their child at 7 primary care clinics and 4 emergency departments across 9 states (2018-2019). Housing-related risks were measured using 2 questions from the Accountable Health Communities screening tool (current/anticipated housing instability, current housing quality problems) and 3 from the Children's HealthWatch recommended housing instability screening measures (prior 12-month: rent/mortgage strain, number of moves, current/recent homelessness). The 2-sided Fisher's exact tests analyzed housing-related risks and participant characteristics; logistic regression explored associations with reported health (2019-2020). RESULTS: Of 835 participants, 52% screened positive for ≥1 housing-related risk (n=430). Comparing the tools, 32.8% (n=274) screened discordant: 11.9% (n=99) screened positive by Children's HealthWatch questions but negative by Accountable Health Communities, and 21.0% (n=175) screened positive by the Accountable Health Communities tool but negative by Children's HealthWatch (p<0.001). Worse health was associated with screening positive for current/anticipated housing instability (AOR=0.56, 95% CI=0.32, 0.96) or current/recent homelessness (AOR=0.57, 95% CI=0.34, 0.96). CONCLUSIONS: The 5 housing questions captured different housing-related risks, contributed to different health consequences, and were relevant to different subpopulations. Before implementing housing-related screening initiatives, health systems should understand how specific measures surface distinct housing-related barriers. Measure selection should depend on program goals and intervention resources.