BACKGROUND: Adverse social determinants of health have been shown to be associated with a greater chance of developing chronic conditions. Although there has been increased focus on screening for health-related social needs (HRSNs) in health care delivery systems, it is seldom examined if the provision of needed services to address HRSNs is sufficiently available in communities where patients reside.
METHODS: The authors used geospatial analysis to determine how well a newly formed health system and community-based organizations (CBOs) social care coordination network covered the areas in which a high number of patients experiencing HRSNs live. Geospatial clusters (hotspots) were constructed for Kaiser Permanente Northwest members experiencing any of the following 4 HRSNs: transportation needs, housing instability, food insecurity, or financial strain. Next, a geospatial polygon was calculated indicating whether a member could reach a social care provider within 30 minutes of travel time.
RESULTS: A total of 185,535 Kaiser Permanente Northwest members completed a HRSN screener between April 2022 and April 2023. Overall, the authors found that among Kaiser Permanente Northwest members experiencing any of the 4 HRSNs, 97% to 98% of them were within 30 minutes of a social care provider. A small percentage of members who lived greater than 30 minutes to a social care provider were primarily located in rural areas.
CONCLUSIONS: This study demonstrates the importance of health system and community-based organization partnerships and investment in community resources to develop social care coordination networks, as well as how patient-level HRSN can be used to assess the coverage and representativeness of the network.

BACKGROUND: Many health systems are trying to support the ability of older adults to remain in their homes for as long as possible. Little is known about the relationship between patient-reported social risks and length of time spent at home. We assessed how social risks were associated with days at home for a cohort of older Veterans at high risk for hospitalization and mortality.
METHODS: A prospective cross-sectional study using a 2018 survey of 3479 high-risk Veterans aged ≥65 linked to Veterans Health Administration data. Social risks included measures of social resources (i.e., no partner present, low social support), material resources (i.e., not employed, financial strain, medication insecurity, food insecurity, and transportation barriers), and personal resources (i.e., low medical literacy and less than high school education). We estimated how social risks were associated with days at home, defined as the number of days spent outside inpatient, long-term care, observation, or emergency department settings over a 12-month period, using a negative binomial regression model.
RESULTS: Not having a partner, not being employed, experiencing transportation barriers, and low medical literacy were respectively associated with 2.57, 3.18, 3.39, and 6.14 fewer days at home (i.e., 27% more facility days, 95% confidence interval [CI] 8%-50%; 42% more facility days, 95% CI 7%-89%; 34% more facility days, 95% CI 7%-68%; and 63% more facility days, 95% CI 27%-109%). Experiencing food insecurity was associated with 2.62 more days at home (i.e., 24% fewer facility days, 95% CI 3%-59%).
CONCLUSIONS: Findings suggest that screening older Veterans at high risk of community exit for social risks (i.e., social support, material resources, and medical literacy) may help identify patients likely to benefit from home- and community-based health and social services that facilitate remaining in home settings. Future research should focus on understanding the mechanisms by which these associations occur.

BACKGROUND: The relationship between work and health is complex and bidirectional, where work can have both health-harming and health-enhancing effects. Though employment is recognized as a social determinant of health, and clinical healthcare delivery systems are increasingly using screening tools to ask patients about social needs, little research has explored the extent to which employment-related social risk is captured in these screening tools. This study aimed to identify and characterize employment- and work-related questions in social risk screening tools that have been implemented in clinical healthcare delivery systems.
METHODS: We conducted a qualitative content analysis of employment-related items in screening tools that have been implemented in clinical healthcare service delivery systems. Three content areas guided data extraction and analysis: Setting, Domain, and Level of Contextualization.
RESULTS: Screening tools that asked employment-related questions were implemented in settings that were diverse in the populations served and the scope of care provided. The intent of employment-related items focused on four domains: Social Risk Factor, Social Need, Employment Exposure, and Legal Need. Most questions were found to have a low Level of Contextualization and were largely focused on identifying an individual\'s employment status.
CONCLUSIONS: Several existing screening tools include measures of employment-related social risk, but these items do not have a clear purpose and range widely depending on the setting in which they are implemented. In order to maximize the utility of these tools, clinical healthcare delivery systems should carefully consider what domain(s) they aim to capture and how they anticipate using the screening tools to address social determinants of health.

BACKGROUND: Adapting clinical care decisions for patient-reported social risks is essential to social health integration and patient-centered care. Most research in this area focuses on awareness and assistance (social-needs-targeted care), such as screening and referral to food, financial, and other resources. Limited evidence for adjustment strategies (social risk-informed care) or adapting care for social risks made it difficult for Kaiser Permanente to implement new initiatives. This article describes a codesign process to build a novel, adjustment-focused continuing medical education course.
METHODS: The authors codeveloped the online continuing medical education course with patients and clinicians using user-centered design. Transcripts from codesign activities were coded and analyzed by thematic analysis to identify major themes, including perceptions of social risk-informed care and barriers to care adjustment.
RESULTS: Practical hurdles for implementing social risk-informed care emerged, including clinicians\' concerns about the ethics of adjustment as substandard care, particularly without robust assistance activities. However, patients expressed a desire for their care to be adapted to their social circumstances, to allow for more realistic care plans.
CONCLUSIONS: Implementation barriers identified from the codesign were addressed through an interactive, case-study approach. Existing evidence on contextualized care and shared decision making informed a general framework for primary care providers to engage in awareness and adjustment activities, paired with 3 interactive case studies based on real-world, clinician-supplied scenarios.
CONCLUSIONS: The authors recommend that multiple stakeholder perspectives be incorporated during the development of social health integration initiatives, particularly adjustment. Education complemented by active, nuanced, flexible implementation strategies may be necessary for the successful uptake of care-delivery-based social health integration activities.

BACKGROUND: Patients with unmet social needs and social determinants of health (SDOH) challenges continue to face a disproportionate risk of increased prevalence of disease, health care use, higher health care costs, and worse outcomes. Some existing predictive models have used the available data on social needs and SDOH challenges to predict health-related social needs or the need for various social service referrals. Despite these one-off efforts, the work to date suggests that many technical and organizational challenges must be surmounted before SDOH-integrated solutions can be implemented on an ongoing, wide-scale basis within most US-based health care organizations.
OBJECTIVE: We aimed to retrieve available information in the electronic health record (EHR) relevant to the identification of persons with social needs and to develop a social risk score for use within clinical practice to better identify patients at risk of having future social needs.
METHODS: We conducted a retrospective study using EHR data (2016-2021) and data from the US Census American Community Survey. We developed a prospective model using current year-1 risk factors to predict future year-2 outcomes within four 2-year cohorts. Predictors of interest included demographics, previous health care use, comorbidity, previously identified social needs, and neighborhood characteristics as reflected by the area deprivation index. The outcome variable was a binary indicator reflecting the likelihood of the presence of a patient with social needs. We applied a generalized estimating equation approach, adjusting for patient-level risk factors, the possible effect of geographically clustered data, and the effect of multiple visits for each patient.
RESULTS: The study population of 1,852,228 patients included middle-aged (mean age range 53.76-55.95 years), White (range 324,279/510,770, 63.49% to 290,688/488,666, 64.79%), and female (range 314,741/510,770, 61.62% to 278,488/448,666, 62.07%) patients from neighborhoods with high socioeconomic status (mean area deprivation index percentile range 28.76-30.31). Between 8.28% (37,137/448,666) and 11.55% (52,037/450,426) of patients across the study cohorts had at least 1 social need documented in their EHR, with safety issues and economic challenges (ie, financial resource strain, employment, and food insecurity) being the most common documented social needs (87,152/1,852,228, 4.71% and 58,242/1,852,228, 3.14% of overall patients, respectively). The model had an area under the curve of 0.702 (95% CI 0.699-0.705) in predicting prospective social needs in the overall study population. Previous social needs (odds ratio 3.285, 95% CI 3.237-3.335) and emergency department visits (odds ratio 1.659, 95% CI 1.634-1.684) were the strongest predictors of future social needs.
CONCLUSIONS: Our model provides an opportunity to make use of available EHR data to help identify patients with high social needs. Our proposed social risk score could help identify the subset of patients who would most benefit from further social needs screening and data collection to avoid potentially more burdensome primary data collection on all patients in a target population of interest.

We aimed to compare disclosure of social risks according to self-report on an iPad versus face-to-face questions from a health professional and to explore carers\' experiences of screening. This two-arm, parallel group, randomized trial was conducted from January 19, 2021, to December 17, 2021, in a public hospital pediatric ward serving a disadvantaged area of an Australian capital city. Carers of children aged ≤ 5 years admitted to the Children\'s Ward were eligible. The primary outcome was disclosure of social risks. The screener included nine items on food security, household utilities, transport, employment, personal and neighborhood safety, social support, housing and homelessness. Disclosure of social risks was similar between the self-completion (n = 193) and assisted-completion (n = 193) groups for all 9 items, ranging 4.1% higher for worrying about money for food (95% CI - 11.4, 3.1%) among the assisted-completion group, to 5.7% (-1.6, 13.0%) higher for unemployment among the self-completion group. In qualitative interviews, participants were positive about screening for social risks in the hospital ward setting and the majority indicated a preference for self-completion.  Conclusion: Differences in the disclosure of social risks according to self- versus assisted-completion were small, suggesting that either method could be used. Most carers expressed a preference for self- completion, which is therefore recommended as the ideal mode for such data collection for Australian pediatric inpatient settings.  Trial registration: Australia New Zealand Clinical Trial Registry ( www.anzctry.org.au ; #ACTRN12620001326987; date of registration 8 December 2020). What is Known: • Most evidence on screening of social risks in pediatric inpatient settings is from the USA. • Little is known about disclosure of social risks in countries with universal health care and social welfare. What is New: • Disclosure of social risks was similar for electronic compared with face-to-face screening. • Carers preferred electronic completion over face-to-face completion.

BACKGROUND: Social risks are common among cancer survivors who have the fewest financial resources; however, little is known about how prevalence differs by age at diagnosis, despite younger survivors\' relatively low incomes and wealth.
METHODS: The authors used data from 3703 participants in the Detroit Research on Cancer Survivors (ROCS) cohort of Black cancer survivors. Participants self-reported several forms of social risks, including food insecurity, housing instability, utility shut-offs, not getting care because of cost or lack of transportation, and feeling unsafe in their home neighborhood. Modified Poisson models were used to estimate prevalence ratios and 95% confidence intervals (CIs) of social risks by age at diagnosis, controlling for demographic, socioeconomic, and cancer-related factors.
RESULTS: Overall, 35% of participants reported at least one social risk, and 17% reported two or more risks. Social risk prevalence was highest among young adults aged 20-39 years (47%) followed by those aged 40-54 years (43%), 55-64 years (38%), and 65 years and older (24%; p for trend < .001). Compared with survivors who were aged 65 years and older at diagnosis, adjusted prevalence ratios for any social risk were 1.75 (95% CI, 1.42-2.16) for survivors aged 20-39 years, 1.76 (95% CI, 1.52-2.03) for survivors aged 40-54 years, and 1.41 (95% CI, 1.23-1.60) for survivors aged 55-64 years at diagnosis. Similar associations were observed for individual social risks and experiencing two or more risks.
CONCLUSIONS: In this population of Black cancer survivors, social risks were inversely associated with age at diagnosis. Diagnosis in young adulthood and middle age should be considered a risk factor for social risks and should be prioritized in work to reduce the financial effects of cancer on financially vulnerable cancer survivors.

Assessment of risks and benefits of study participation is standard practice preceding the initiation of human subjects research. Although tracking adverse events during research participation is routine, collecting information from participants about what they perceive as benefits is less common. We longitudinally tracked social risks and benefits of participation among a cohort of 241 men who have sex with men participating in a sexual health study to improve participants\' experiences and enhance understanding of participant motivations to enroll and attend follow-up. Of the participants who returned for at least one follow-up visit (n = 217, 90%), most (n = 185, 85%) reported positive consequences resulting from participation. Reporting of negative social consequences was rare, and all concerned a stigmatized reaction from someone learning about the participant\'s involvement in a sexual health study. Better identification of both positive and negative consequences resulting from research participation may improve how researchers design, recruit, and conduct research.

UNASSIGNED: Area-level social determinants of health (SDoH) and individual-level social risks are different, yet area-level measures are frequently used as proxies for individual-level social risks. This study assessed whether demographic factors were associated with patients being screened for individual-level social risks, the percentage who screened positive for social risks, and the association between SDoH and patient-reported social risks in a nationwide network of community-based health centers.
UNASSIGNED: Electronic health record data from 1,330,201 patients with health center visits in 2021 were analyzed using multilevel logistic regression. Associations between patient characteristics, screening receipt, and screening positive for social risks (e.g., food insecurity, housing instability, transportation insecurity) were assessed. The predictive ability of three commonly used SDoH measures (Area Deprivation Index, Social Deprivation Index, Material Community Deprivation Index) in identifying individual-level social risks was also evaluated.
UNASSIGNED: Of 244,155 (18%) patients screened for social risks, 61,414 (25.2%) screened positive. Sex, race/ethnicity, language preference, and payer were associated with both social risk screening and positivity. Significant health system-level variation in both screening and positivity was observed, with an intraclass correlation coefficient of 0.55 for social risk screening and 0.38 for positivity. The three area-level SDoH measures had low accuracy, sensitivity, and area under the curve when used to predict individual social needs.
UNASSIGNED: Area-level SDoH measures may provide valuable information about the communities where patients live. However, policymakers, healthcare administrators, and researchers should exercise caution when using area-level adverse SDoH measures to identify individual-level social risks.

Growing evidence linking social determinants of health (SDOH) to child health outcomes has prompted widespread recommendations for pediatricians to screen and refer for adverse SDOH at primary care visits. Yet there is little evidence to date demonstrating the effectiveness of practice-based SDOH screening and referral interventions on increasing family engagement with resources. This hybrid type 2 effectiveness-implementation trial aims to demonstrate the non-inferiority of a low-touch implementation strategy in order to facilitate dissemination of an existing SDOH screening and referral system (WE CARE) and demonstrate its effectiveness and sustainability in various pediatric practices.
We recruited eighteen pediatric practices in fourteen US states through two pediatric practice-based research networks. For this stepped wedge cluster RCT, practices serve as their own controls during the Usual Care phase and implement WE CARE during the intervention phase via one of two randomized implementation strategies: self-directed, pre-recorded webinar vs. study team-facilitated, live webinar. We collect data at practice, clinician/staff, and parent levels to assess outcomes grounded in the Proctor Conceptual Model of Implementation Research. We use generalized mixed effects models and differences in proportions to compare rates of resource referrals by implementation strategy, and intention-to-treat analysis to compare odds of engagement with new resources among families enrolled in the Usual Care vs. WE CARE phases.
Findings from this trial may inform decisions about broader dissemination of SDOH screening systems into a diverse spectrum of pediatric practices across the US and potentially minimize the impact of adverse SDOH on children and families.