Accelerating the Implementation of Social Determinants of Health Interventions in Internal Medicine

Development of a Social Risk Score in the Electronic Health Record to Identify Social Needs Among Underserved Populations: Retrospective Study

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.

Use of and barriers to adopting standardized social risk screening tools in federally qualified health centers during the first year of the COVID-19 pandemic

OBJECTIVE

To describe the national rate of social risk factor screening adoption among federally qualified health centers (FQHCs), examine organizational factors associated with social risk screening adoption, and identify barriers to utilizing a standardized screening tool in 2020.

DATA SOURCE

2020 Uniform Data System, a 100% sample of all US FQHCs (N = 1375).

STUDY DESIGN

We used multivariable linear probability models to assess the association between social risk screening adoption and key FQHC characteristics. We used descriptive statistics to describe variations in screening tool types and barriers to utilizing standardized tools. We thematically categorized open-ended responses about tools and barriers.

DATA COLLECTION

None.

PRINCIPAL FINDINGS

In 2020, 68.9% of FQHCs screened patients for any social risk factors. Characteristics associated with a greater likelihood of screening adoption included having high proportions of patients best served in a language other than English (18.8 percentage point [PP] increase, 95% CI: 6.0, 31.6) and being larger in size (10.3 PP increase, 95% CI: 0.7, 20.0). Having higher proportions of uninsured patients (14.2 PP decrease, 95% CI: -25.5, -0.3) and participating in Medicaid-managed care contracts (7.3 PP decrease, 95% CI: -14.2, -0.3) were associated with lower screening likelihood. Among screening FQHCs, the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE) was the most common tool (47.1%). Among non-screening FQHCs, common barriers to using a standardized tool included lack of staff training to discuss social issues (25.2%), inability to include screening in patient intake (21.7%), and lack of funding for addressing social needs (19.2%).

CONCLUSIONS

Though most FQHCs screened for social risk factors in 2020, various barriers have prevented nearly 1 in 3 FQHCs from adopting a screening tool. Policies that provide FQHCs with resources to support training and workflow changes may increase screening uptake and facilitate engagement with other sectors.

The impact of social determinants of health on textbook oncological outcomes and overall survival in locally advanced non-small cell lung cancer

Objectives

Textbook oncological outcome (TOO) is a composite metric for surgical outcomes, including non-small cell lung cancer (NSCLC). We hypothesized that social determinants of health (SDH) can affect both the attainment of TOO and the overall survival (OS) in surgically resected NSCLC patients with pathological nodal disease.

Methods

We queried the National Cancer Database (2010-2017) for preoperative therapy-naïve lobectomies for NSCLC with tumor size <7 cm and pathologic N1/N2. Socioeconomic factors comprised SDH scores, where SDH negative (-) was considered if SDH ≥2 (disadvantage); otherwise, SDH was positive (+). TOO+ was defined as R0 resection, ≥5 lymph nodes resected, hospital stay <75th percentile, no 30-day mortality, adjuvant chemotherapy initiation ≤3 months, and no unplanned readmission. If one of these parameters was not achieved, the case was considered TOO-.

Results

Of 11,274 patients, 48% of cases were TOO+ and 38% were SDH+. A total of 15% of patients were SDH- and were less likely (adjusted odds ratio, 0.85; 95% confidence interval [CI], 0.78-0.92) to achieve TOO+ than patients with SDH+. After accounting for confounders, patients with TOO+ had 22% lower overall mortality than patients with TOO- (adjusted hazard ratio, 0.78; CI, 0.73-0.82). In contrast, SDH- remained an independently significant risk factor, reducing survival by 24% compared with SDH+ (adjusted hazard ratio, 1.24; CI, 1.17-1.32). The impact of SDH on OS was significant for both patients with TOO+ and TOO-: SDH+/TOO+ had the best OS and SDH-/TOO-had the worst OS.

Conclusions

SDH score has a significant association with TOO achievement and TOO-driven overall posttreatment survival in patients with lobectomy-resected NSCLC with postoperative pathologic N1/N2 nodal metastasis. Addressing SDH is important to optimize care and long-term survival of this patient population.

Housing instability and psychological distress in African American cancer survivors: findings from the Detroit Research on Cancer Survivors study

PURPOSE

As health care systems seek to screen for and address housing instability in patient populations, robust evidence linking unstable housing to patient-reported outcomes is needed. Housing instability may increase psychological distress in cancer survivors, potentially more so among African American cancer survivors who are also likely to experience disproportionate burden of housing instability. The purpose of this analysis was to estimate associations between housing instability and psychological distress in African Americans diagnosed with cancer.

METHODS

We included survey responses from 2875 African American cancer survivors in the Detroit Research on Cancer Survivors (ROCS) study. We examined how housing instability at enrollment, using an item adapted from the Health Leads Screening Toolkit, related to psychological distress at enrollment, using Patient Reported Outcomes Measurement System (PROMIS) 4-item anxiety and depression short forms. Linear regression models adjusted for sociodemographic factors were used to estimate associations overall and stratified by stage at diagnosis.

RESULTS

Approximately 12% of participants reported being unstably housed. Housing instability was associated with significant differences in PROMIS scores for both anxiety (difference: 6.79; 95% CI: 5.57-8.01) and depression (difference: 6.16; 95% CI: 4.99-7.34). We did not find meaningful differences stratifying by disease stage.

CONCLUSION

Housing instability was experienced by over a tenth of this cohort of African American cancer survivors and was related to statistically and clinically meaningful differences in psychological distress even following adjustment for sociodemographics.

IMPLICATIONS FOR CANCER SURVIVORS

These findings provide evidence supporting screening of housing instability in cancer survivors, especially those from medically underserved populations.

Addressing Social Needs in Clinical Settings: Early Lessons from Accountable Health Communities

The Centers for Medicare and Medicaid Services recently adopted quality metrics that require hospitals to screen for health-related social risks. The hope is that these requirements will encourage health care organizations to refer patients with social needs to community resources and, as possible, offer navigation services. This approach-screening, referrals, and navigation-is based, in part, on the Accountable Health Communities (AHC) model. Twenty-two of 31 participants in the AHC model in 2019 were interviewed to generate guidance for health care organizations as they implement screening, referral, and navigation activities to improve patients' health-related social risks. From these interviews, the team identified 4 key program design elements that facilitated AHC implementation: (1) centralized management office, (2) accountability milestones, (3) prescriptive requirements, and (4) technology support. The structure and requirements of the AHC model spurred participating organizations to rapidly implement social care activities, but the model did not allow for the flexibility necessary to ensure sustained adoption of AHC activities. The AHC model required a designated centralized management office, which was instrumental in ensuring AHC activities were implemented effectively. The centralized management office was typically external from participating clinical sites that impacted the AHC model's integration within clinical workflows. The reliance on the centralized management office to implement AHC activities limited the sustainability of the model. As payers, policymakers, and delivery system leaders aim to develop sustainable and effective social care programs, insights from these interviews can help guide and shape policy and program design elements.

Assessment of the Massachusetts Flexible Services Program to Address Food and Housing Insecurity in a Medicaid Accountable Care Organization

Importance

Health systems are increasingly addressing health-related social needs. The Massachusetts Flexible Services program (Flex) is a 3-year pilot program to address food insecurity and housing insecurity by connecting Medicaid accountable care organization (ACO) enrollees to community resources.

Objective

To understand barriers and facilitators of Flex implementation in 1 Medicaid ACO during the first 17 months of the program.

Design, Setting, and Participants

This mixed-methods qualitative evaluation study from March 2020 to July 2021 used the Reach, Efficacy, Adoption, Implementation, Maintenance/Practical, Robust Implementation, and Sustainability Model (RE-AIM/PRISM) framework. Two Mass General Brigham (MGB) hospitals and affiliated community health centers were included in the analysis. Quantitative data included all MGB Medicaid ACO enrollees. Qualitative interviews were conducted with 15 members of ACO staff and 17 Flex enrollees.

Main Outcomes and Measures

Reach was assessed by the proportion of ACO enrollees who completed annual social needs screening (eg, food insecurity and housing insecurity) and the proportion and demographics of Flex enrollees. Qualitative interviews examined other RE-AIM/PRISM constructs (eg, implementation challenges, facilitators, and perceived effectiveness).

Results

Of 67 098 Medicaid ACO enrollees from March 2020 to July 2021 (mean [SD] age, 28.8 [18.7] years), 38 442 (57.3%) completed at least 1 social needs screening; 10 730 (16.0%) screened positive for food insecurity, and 7401 (11.0%) screened positive for housing insecurity. There were 658 (1.6%) adults (mean [SD] age, 46.6 [11.8] years) and 173 (0.7%) children (<21 years; mean [SD] age, 10.1 [5.5]) enrolled in Flex; of these 831 people, 613 (73.8%) were female, 444 (53.4%) were Hispanic/Latinx, and 172 (20.7%) were Black. Most Flex enrollees (584 [88.8%] adults; 143 [82.7%] children) received the intended nutrition or housing services. Implementation challenges identified by staff interviewed included administrative burden, coordination with community organizations, data-sharing and information-sharing, and COVID-19 factors (eg, reduced clinical visits). Implementation facilitators included administrative funding for enrollment staff, bidirectional communication with community partners, adaptive strategies to identify eligible patients, and raising clinician awareness of Flex. In Flex enrollee interviews, those receiving nutrition services reported increased healthy eating and food security; they also reported higher program satisfaction than Flex enrollees receiving housing services. Enrollees who received nutrition services that allowed for selecting food based on preferences reported higher satisfaction than those not able to select food.

Conclusions and Relevance

This mixed-methods qualitative evaluation study found that to improve implementation, Medicaid and health system programs that address social needs may benefit from providing funding for administrative costs, developing bidirectional data-sharing platforms, and tailoring support to patient preferences.

COVID-19 stressors for Hispanic/Latino patients living with type 2 diabetes: a qualitative study

Background and aim

During the early stages of the COVID-19 pandemic, nationwide lockdowns caused disruption in the diets, physical activities, and lifestyles of patients with type 2 diabetes. Previous reports on the possible association between race/ethnicity, COVID-19, and mortality have shown that Hispanic/Latino patients with type 2 diabetes who are socioeconomically disadvantaged are disproportionately affected by this novel virus. The aim of this study was to explore stressors associated with changes in diabetes self-management behaviors. Our goal was to highlight the health disparities in these vulnerable racial/ethnic minority communities and underscore the need for effective interventions.

Methods and participants

Participants were enrolled in part of a larger randomized controlled trial to compare diabetes telehealth management (DTM) with comprehensive outpatient management (COM) in terms of critical patient-centered outcomes among Hispanic/Latino patients with type 2 diabetes. We conducted a thematic analysis using patient notes collected from two research nurses between March 2020 and March 2021. Two authors read through the transcripts independently to identify overarching themes. Once the themes had been identified, both authors convened to compare themes and ensure that similar themes were identified within the transcripts. Any discrepancies were discussed by the larger study team until a consensus was reached.

Results

Six themes emerged, each of which can be categorized as either a source or an outcome of stress. Sources of stress associated with the COVID-19 pandemic were (1) fear of contracting COVID-19, (2) disruptions from lockdowns, and (3) financial stressors (e.g., loss of income). Outcomes of COVID-19 stressors were (1) reduced diabetes management (e.g., reduced diabetes monitoring and physical activity), (2) suboptimal mental health outcomes (e.g., anxiety and depression), and (3) outcomes of financial stressors.

Conclusion

The findings indicated that underserved Hispanic/Latino patients with type 2 diabetes encountered a number of stressors that led to the deterioration of diabetes self-management behaviors during the pandemic.

"More than just giving them a piece of paper": Interviews with Primary Care on Social Needs Referrals to Community-Based Organizations

BACKGROUND

Primary care practices are responding to calls to incorporate patients' social risk factors, such as housing, food, and economic insecurity, into clinical care. Healthcare likely relies on the expertise and resources of community-based organizations to improve patients' social conditions, yet little is known about the referral process.

OBJECTIVE

To characterize referrals to community-based organizations by primary care practices.

DESIGN

Qualitative study using semi-structured interviews with healthcare administrators responsible for social care efforts in their organization.

PARTICIPANTS

Administrators at 50 diverse US healthcare organizations with efforts to address patients' social risks.

MAIN MEASURES

Approaches used in primary care to implement social needs referral to community-based organizations.

RESULTS

Interviewed administrators reported that social needs referrals were an essential element in their social care activities. Administrators described the ideal referral programs as placing limited burden on care teams, providing patients with customized referrals, and facilitating closed-loop referrals. We identified three key challenges organizations experience when trying to implement the ideal referrals program: (1) developing and maintaining resources lists; (2) aligning referrals with patient needs; and (3) measuring the efficacy of referrals. Collectively, these challenges led to organizations relying on staff to manually develop and update resource lists and, in most cases, provide patients with generic referrals. Administrators not only hoped that referral platforms may help overcome some of these barriers, but also reported implementation challenges with platforms including inconsistent buy-in and use across staff; integration with electronic health records; management and prioritization of resources; and alignment with other organizations in their market.

CONCLUSION AND RELEVANCE

Referrals to community-based organizations were used in primary care to improve patients' social conditions, but despite strong motivations, interviewees reported challenges providing tailored and up-to-date information to patients.

Screening for Social Risk at Federally Qualified Health Centers: A National Study

INTRODUCTION

Federally Qualified Health Centers serve 29.8 million low-income patients across the U.S., many of whom have unaddressed social risks. In 2019, for the first time, data on social risk screening capabilities were collected from every U.S. Federally Qualified Health Center. The objectives of this study were to describe the national rates of social risk screening capabilities across Federally Qualified Health Centers, identify organizational predictors of screening, and assess between-state heterogeneity.

METHODS

Using a 100% sample of U.S. Federally Qualified Health Centers (N=1,384, representing 29.8 million patients) from the 2019 Uniform Data System, the primary outcome was whether a Federally Qualified Health Center collected data on patients' social risk factors (yes/no). Summary statistics on the rates of social risk screening capabilities were generated in aggregate and by state. Linear probability models were then used to estimate the relationship between the probability of social risk screening and 7 key Federally Qualified Health Center characteristics (e.g., Federally Qualified Health Center size, Medicaid MCO contract, Medicaid accountable care organization presence). Data were analyzed in 2020‒2021.

RESULTS

Most (71%) Federally Qualified Health Centers collected social risk data, with a between-state variation. The most common screener was the Protocol for Responding to and Assessing Patients' Assets Risks and Experiences (43% of Federally Qualified Health Centers that screened), whereas 22% collected social risk data using a nonstandardized screener. After adjusting for other characteristics, Federally Qualified Health Centers with social risk screening capabilities served more total patients, were more likely to be located in a state with a Medicaid accountable care organization, and were less likely to have an MCO contract.

CONCLUSIONS

There has been widespread adoption of social risk screening tools across U.S. Federally Qualified Health Centers, but between-state disparities exist. Targeting social risk screening resources to smaller Federally Qualified Health Centers may increase the adoption of screening tools.

Addressing patient’s unmet social needs: disparities in access to social services in the United States from 1990 to 2014, a national times series study

Background

To address patient’s unmet social needs and improve health outcomes, health systems have developed programs to refer patients in need to social service agencies. However, the capacity to respond to patient referrals varies tremendously across communities. This study assesses the emergence of disparities in spatial access to social services from 1990 to 2014.

Methods

Social service providers in the lower 48 continental U.S. states were identified annually from 1990 to 2014 from the National Establishment Times Series (NETS) database. The addresses of providers were linked in each year to 2010 US Census tract geometries. Time series analyses of annual counts of services per Km² were conducted using Generalized Estimating Equations with tracts stratified into tertiles of 1990 population density, quartiles of 1990 poverty rate and quartiles of 1990 to 2010 change in median household income.

Results

Throughout the period, social service agencies/Km² increased across tracts. For high population density tracts, in the top quartile of 1990 poverty rate, compared to tracts that experienced the steepest declines in median household income from 1990 to 2010, tracts that experienced the largest increases in income had more services (+ 1.53/Km², 95% CI 1.23, 1.83) in 1990 and also experienced the steepest increases in services from 1990 to 2010: a 0.09 services/Km²/year greater increase (95% CI 0.07, 0.11). Similar results were observed for high poverty tracts in the middle third of population density, but not in tracts in the lowest third of population density, where there were very few providers.

Conclusion

From 1990 to 2014 a spatial mismatch emerged between the availability of social services and the expected need for social services as the population characteristics of neighborhoods changed. High poverty tracts that experienced further economic decline from 1990 to 2010, began the period with the lowest access to services and experienced the smallest increases in access to services. Access was highest and grew the fastest in high poverty tracts that experienced the largest increases in median household income. We theorize that agglomeration benefits and the marketization of welfare may explain the emergence of this spatial mismatch.

Predicting health-related social needs in Medicaid and Medicare populations using machine learning

Providers currently rely on universal screening to identify health-related social needs (HRSNs). Predicting HRSNs using EHR and community-level data could be more efficient and less resource intensive. Using machine learning models, we evaluated the predictive performance of HRSN status from EHR and community-level social determinants of health (SDOH) data for Medicare and Medicaid beneficiaries participating in the Accountable Health Communities Model. We hypothesized that Medicaid insurance coverage would predict HRSN status. All models significantly outperformed the baseline Medicaid hypothesis. AUCs ranged from 0.59 to 0.68. The top performance (AUC = 0.68 CI 0.66–0.70) was achieved by the “any HRSNs” outcome, which is the most useful for screening prioritization. Community-level SDOH features had lower predictive performance than EHR features. Machine learning models can be used to prioritize patients for screening. However, screening only patients identified by our current model(s) would miss many patients. Future studies are warranted to optimize prediction of HRSNs.

An embedded multiple case study: using CFIR to map clinical food security screening constructs for the development of primary care practice guidelines

BACKGROUND

Food insecurity (FI), the limited access to healthy food to live an active and healthy life, is a social determinant of health linked to poor dietary health and difficulty with disease management in the United States (U.S.). Healthcare experts support the adoption of validated screening tools within primary care practice to identify and connect FI patients to healthy and affordable food resources. Yet, a lack of standard practices limits uptake. The purpose of this study was to understand program processes and outcomes of primary care focused FI screening initiatives that may guide wide-scale program implementation.

METHODS

This was an embedded multiple case study of two primary care-focused initiatives implemented in two diverse health systems in Chicago and Suburban Cook County that routinely screened patients for FI and referred them to onsite food assistance programs. The Consolidated Framework for Implementation Research and an iterative process were used to collect/analyze qualitative data through semi-structured interviews with N = 19 healthcare staff. Intended program activities, outcomes, actors, implementation barriers/facilitators and overarching implementation themes were identified as a part of a cross-case analysis.

RESULTS

Programs outcomes included: the number of patients screened, identified as FI and that participated in the onsite food assistance program. Study participants reported limited internal resources as implementation barriers for program activities. The implementation climate that leveraged the strength of community collaborations and aligned internal, implementation climate were critical facilitators that contributed to the flexibility of program activities that were tailored to fill gaps in resources and meet patient and clinician needs.

CONCLUSION

Highly adaptable programs and the healthcare context enhanced implementation feasibility across settings. These characteristics can support program uptake in other settings, but should be used with caution to preserve program fidelity. A foundational model for the development and testing of standard clinical practice was the product of this study.

Results of an Initiative Supporting Community-Based Organizations and Health Care Clinics to Assist Individuals With Enrolling in SNAP

CONTEXT

Only 58% of eligible Coloradans are enrolled in the Supplemental Nutrition Assistance Program (SNAP). In recent years, more community-based organizations (CBOs) and health care clinics are incorporating screening for social needs into their workflows.

PROGRAM

Seven Colorado-based CBOs and 3 clinics received funding (2016-2018) to screen for food insecurity (FI) and provide SNAP application assistance to their clients and patients.

IMPLEMENTATION

Funded agencies were required to implement strategies focused on particular populations or settings based on Food Research and Action Center recommendations.

EVALUATION

A 5-part care cascade from screening to SNAP enrollment was conceptualized to guide the evaluation. Funded CBOs and clinics were asked to submit de-identified individual-level data to the evaluation team (number and characteristics of individuals screened, screening results, interest in receiving assistance, submitted application, enrolled in SNAP). The purpose of the evaluation was to assess the proportion of individuals CBOs and clinics screen for FI and assist with completing a SNAP application and describe the characteristics of individuals who are not interested in receiving assistance to complete a SNAP application and the characteristics of individuals who enroll in SNAP.

RESULTS

Thirty-five percent of individuals who reported FI participated in the care cascade and enrolled in SNAP. CBOs assisted a greater proportion of food-insecure individuals (55%) than clinics (22%) (P < .001). Males, adults 40 years or older, rural residents, and African Americans were more likely to be interested in receiving assistance, and adults 40 years or older, rural residents, and American Indians/Alaska Natives were more likely to enroll in SNAP.

DISCUSSION

CBOs were more successful in assisting individuals along the care cascade than clinics. Certain subpopulations are more likely to be interested in receiving assistance and enrolling in SNAP. These findings can be used by public health practitioners to plan interventions to increase enrollment in SNAP.

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

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

Implementing a Food is Medicine Program to Address Food Insecurity in an Academic Medical Center

BACKGROUND

Food insecurity is a public, social, and health concern.

LOCAL PROBLEM

A Food is Medicine Program was developed to address food insecurity.

METHODS

A quality improvement initiative was piloted on 3 acute care units.

INTERVENTIONS

Patients were screened for Social Determinant of Health (SDoH) needs and if identified as food insecure, linked to community resources and provided with a bag of food on discharge. Education was offered to nursing staff and a pre- and postsurvey was administered to assess SDoH knowledge and confidence.

RESULTS

Over a 3-month period, 2354 patients were admitted; 2063 (88%) were screened for SDoH and 220 (10%) were positive for food insecurity. Patients (n = 1525, 74%) were linked to community resources. Nearly all (97%) nurses participated in education and demonstrated increased knowledge and confidence (P < .001).

CONCLUSIONS

These data provide preliminary outcomes from the Food is Medicine Program.

Factors Related to Providers Screening Children for Behavioral Health Risks in Primary Care Settings

PURPOSE

To provide information from a large sample of pediatric and family medicine primary care providers on practices in screening children for behavioral health risks.

DESIGN AND METHODS

Participants were a sample of physicians (n=319) and nurse practitioners (n=292) from across the U.S. who completed a confidential online survey about screening practices through a computer-assisted self-interview.

RESULTS

Almost all respondents (89%) reported screening children for depression/anxiety and behavior problems. Child substance use (82%), family social support (74%), significant household changes (73%), bullying (72%), child abuse (62%) and domestic violence (52%) were also asked about regularly, although with high rates of informal screening methods. Caregiver mental health (49%), caregiver substance use (35%), family financial strain (33%) and transportation difficulties (27%) were screened less frequently. Screening was associated with higher rates of referral for risk-related problems, and was more likely when providers reported greater confidence providing support to clients, perceived community resource availability as higher, and worked in systems with integrated primary care and behavioral health.

CONCLUSIONS

Findings suggest a great amount of diversity in how providers screen for behavioral health risks. There is reluctance to screen when options for addressing the problems are seen as limited. Research is needed to better guide healthcare providers in determining the right context and methods for screening social risks.

PRACTICE IMPLICATIONS

Protocols for screening adverse childhood events (ACES) and other social risk factors should be accompanied by adequate training and efforts to improve community resource and support networks.

A Community Resource Navigator Model: Utilizing Student Volunteers to Integrate Health and Social Care in a Community Health Center Setting

INTRODUCTION

While unmet social needs are major drivers of health outcomes, most health systems are not fully integrated with the social care sector to address them. In this case study, we describe the development and implementation of a model utilizing student volunteer community resource navigators to help patients connect with community-based organizations (CBOs). We then detail initial implementation outcomes and practical considerations for future work.

METHODS

We used the Ten Essential Public Health Services Framework to guide program planning of a student "Help Desk" model for a community health center. Planning included a literature review, observation of exemplar programs, development of a CBO directory, and evaluation of the center's patient population, clinical workflows, and data infrastructure. We piloted the model for two months. After pilot completion, we reviewed patient data to understand the feasibility of the student "Help Desk" model. We utilized planning and pilot execution materials, as well as pilot data, to develop and discuss practical considerations.

RESULTS

Design and implementation complemented ongoing social needs screening and referral to CBOs by center case managers. Patients were asked if they would accept telephone follow-up by volunteers two and four weeks after the clinic visit. Of 61 patients screened, 29 patients were referred for follow-up. Ninety percent were reached at least once during the follow-up period, and 48% of patients referred reported connecting to at least one CBO. Only 27% of patients required escalation back to case managers, and no emergency escalation was needed for any patients. Students, faculty advisors, and community health center frontline staff and leadership supported the scale up and continuation of the "Help Desk" model at the community health center.

DISCUSSION

Successful implementation required multi-sectoral collaboration, well-defined scope of practice, and data interoperability. Student volunteers are untapped resources to support integrated health and social care.

Does Parental Report of Having a Medical Home Attenuate the Negative Association Between Unmet Basic Needs and Health for Low-Income Children?

Background. It is unknown whether the medical home reduces the impact of adverse social determinants on low-income child health. Objective. To examine whether the medical home attenuates the association between unmet basic needs and health for low-income children. Design/Methods. Secondary data analysis of the 2011-12 NSCH restricted to <200% FPL children (n = 26 974). Multivariable logistic regression modeled child health with unmet basic needs to examine the effect modification of the medical home. Results. Low-income children with unmet needs had lower odds of "excellent/very good" health compared to children without unmet needs, regardless of the medical home [aOR = 0.78 (0.61-0.99) vs aOR = 0.77 (0.63-0.94), P = .01), respectively]. The medical home did not modify the negative association between unmet basic needs and "excellent/very good" child health (P = .97). Conclusion. Having a medical home per parental report did not attenuate the negative relationship between unmet basic needs and lowincome child health.

Feasibility of Mobile Technology to Identify and Address Patients' Unmet Social Needs in a Primary Care Clinic

Mobile health tools may overcome barriers to social needs screening; however, there are limited data on the feasibility of using these tools in clinical settings. The objective was to determine the feasibility of using a mobile health system to screen for patients' social needs. In one large primary care clinic, the authors tested a tablet-based system that screens patients for social needs, transmits results to the electronic health record, and alerts providers. All adult patients presenting for a nonurgent visit were eligible. The authors evaluated the feasibility of the system and conducted follow-up surveys to determine acceptability and if patients accessed resources through the process. All providers were surveyed. Of the 252 patients approached, 219 (86.9%) completed the screen. Forty-three (19.6%) required assistance with the tablet, and 150 (68.5%) screened positive for at least 1 unmet need (food, housing, or transportation). Of the 150, 103 (68.7%) completed a follow-up survey. The majority agreed that people would learn to use the tablet quickly. Forty-eight patients (46.6%) reported contacting at least 1 community organization through the process. Of the 27 providers, 23 (85.2%) completed a survey and >70% agreed the system would result in patients having better access to resources. It was feasible to use a tablet-based system to screen for social needs. Clinics considering using mobile tools will need to determine how to screen patients who may need assistance with the tool and how to connect patients to resources through the system based on the burden of unmet needs.

Implementation of Clinical Practice Guidelines in the Health Care Setting: A Concept Analysis

The literature is replete with clinical practice guidelines (CPGs) and evidence supporting them. Translating guidelines into practice, however, is often challenging. We conducted a concept analysis to define the concept of "implementation of CPGs in health care settings." We utilized Walker and Avant's methodology to define the concept of "implementation of CPGs in health care settings." This included a focused review of the literature, defining the relevant attributes, defining implementation, case examples, and antecedents and potential consequences from implementation of CPGs in health care settings. The concept "implementation" is complex, with numerous frameworks, facilitators, and barriers to implementation described in the literature. The existing literature supports our definition of implementation of CPGs in a health care setting as a process of changing practice in health care while utilizing the best level of evidence that is available in the published literature. These include 7 attributes necessary for effective implementation. Implementation of CPGs in health care settings requires an ongoing iterative process that considers these attributes and is inclusive to administrators, clinicians, and patients to ensure guidelines are understood, accepted, implemented, and evaluated for continued adoption of best practices. Ongoing efforts inclusive at all steps of implementation across multiple levels are needed to effectively change practice.

Clinician Experiences and Attitudes Regarding Screening for Social Determinants of Health in a Large Integrated Health System

BACKGROUND

Clinical screening for basic social needs-such as food and housing insecurity-is becoming more common as health systems develop programs to address social determinants of health. Clinician attitudes toward such programs are largely unexplored.

OBJECTIVE

To describe the attitudes and experiences of social needs screening among a variety of clinicians and other health care professionals.

RESEARCH DESIGN

Multicenter electronic and paper-based survey.

SUBJECTS

Two hundred fifty-eight clinicians including primarily physicians, social workers, nurses, and pharmacists from a large integrated health system in Southern California.

MEASURES

Level of agreement with prompts exploring attitudes toward and barriers to screening and addressing social needs in different clinical settings.

RESULTS

Overall, most health professionals supported social needs screening in clinical settings (84%). Only a minority (41%) of clinicians expressed confidence in their ability to address social needs, and less than a quarter (23%) routinely screen for social needs currently. Clinicians perceived lack of time to ask (60%) and resources (50%) to address social needs as their most significant barriers. We found differences by health profession in attitudes toward and barriers to screening for social needs, with physicians more likely to cite time constraints as a barrier.

CONCLUSIONS

Clinicians largely support social needs programs, but they also recognize key barriers to their implementation. Health systems interested in implementing social needs programs should consider the clinician perspective around the time and resources required for such programs and address these perceived barriers.

Screening for Social Determinants of Health in Free and Charitable Clinics in North Carolina

Free and charitable clinics care for patients at risk of unmet social needs, but limited research is available describing what these clinics do to address social determinants of health (SDH). We conducted a survey of free and charitable clinics in North Carolina to determine the proportion that screen for SDH. Clinics that were members of the North Carolina Association of Free and Charitable Clinics were eligible (n=67). Of the 55 clinics that completed the survey, 34 (61.8%) reported always screening for at least one SDH. The majority that were screening provided information about community resources. Twentyseven (49.1%) reported that they followed-up with patients at the next visit to determine if they received the resources. The primary barrier to screening was a lack of personnel. Future research should focus on how to implement SDH interventions in clinics with limited resources serving patients likely to have a high need for social services.

Standardized activities for lay patient navigators in breast cancer care: Recommendations from a citywide implementation study

BACKGROUND

There is a need for guidelines on patient navigation activities to promote both the quality of patient navigation and the standards of reimbursement for these services because a lack of reimbursement is a major barrier to the implementation, maintenance, and sustainability of these programs.

METHODS

A broad community-based participatory research process was used to identify the needs of patients for navigation. A panel of stakeholders of clinical providers was convened to identify specific activities for navigators to address the needs of patients and providers with the explicit goal of reducing delays in the initiation of cancer treatment and improving adherence to the care plan.

RESULTS

Specific activities were identified that could be generalized to all patient navigation programs for care during active cancer management to address the needs of vulnerable communities.

CONCLUSIONS

Oncology programs that seek to implement lay patient navigation may benefit from the adoption of these activities for quality monitoring. Such activities are necessary as we consider reimbursement strategies for navigators without clinical training or licensure.

Study protocol: a pragmatic, stepped-wedge trial of tailored support for implementing social determinants of health documentation/action in community health centers, with realist evaluation

BACKGROUND

National leaders recommend documenting social determinants of health and actions taken to address social determinants of health in electronic health records, and a growing body of evidence suggests the health benefits of doing so. However, little evidence exists to guide implementation of social determinants of health documentation/action.

METHODS

This paper describes a 5-year, mixed-methods, stepped-wedge trial with realist evaluation, designed to test the impact of providing 30 community health centers with step-by-step guidance on implementing electronic health record-based social determinants of health documentation. This guidance will entail 6 months of tailored support from an interdisciplinary team, including training and technical assistance. We will report on tailored support provided at each of five implementation steps; impact of tailored implementation support; a method for tracking such tailoring; and context-specific pathways through which these tailored strategies effect change. We will track the competencies and resources needed to support the study clinics' implementation efforts.

DISCUSSION

Results will inform how to tailor implementation strategies to meet local needs in real-world practice settings. Secondary analyses will assess impacts of social determinants of health documentation and referral-making on diabetes outcomes. By learning whether and how scalable, tailored implementation strategies help community health centers adopt social determinants of health documentation and action, this study will yield timely guidance to primary care providers. We are not aware of previous studies exploring implementation strategies that support adoption of social determinants of action using electronic health and interventions, despite the pressing need for such guidance.

TRIAL REGISTRATION

clinicaltrials.gov, NCT03607617 , registration date: 7/31/2018-retrospectively registered.

Supporting the Health Care Transition From Adolescence to Adulthood in the Medical Home

Risk and vulnerability encompass many dimensions of the transition from adolescence to adulthood. Transition from pediatric, parent-supervised health care to more independent, patient-centered adult health care is no exception. The tenets and algorithm of the original 2011 clinical report, "Supporting the Health Care Transition from Adolescence to Adulthood in the Medical Home," are unchanged. This updated clinical report provides more practice-based quality improvement guidance on key elements of transition planning, transfer, and integration into adult care for all youth and young adults. It also includes new and updated sections on definition and guiding principles, the status of health care transition preparation among youth, barriers, outcome evidence, recommended health care transition processes and implementation strategies using quality improvement methods, special populations, education and training in pediatric onset conditions, and payment options. The clinical report also includes new recommendations pertaining to infrastructure, education and training, payment, and research.

Adoption of Social Determinants of Health EHR Tools by Community Health Centers

PURPOSE

This pilot study assessed the feasibility of implementing electronic health record (EHR) tools for collecting, reviewing, and acting on patient-reported social determinants of health (SDH) data in community health centers (CHCs). We believe it is the first such US study.

METHODS

We implemented a suite of SDH data tools in 3 Pacific Northwest CHCs in June 2016, and used mixed methods to assess their adoption through July 2017. We modified the tools at clinic request; for example, we added questions that ask if the patient wanted assistance with SDH needs.

RESULTS

Social determinants of health data were collected on 1,130 patients during the study period; 97% to 99% of screened patients (n = 1,098) had ≥1 SDH need documented in the EHR, of whom 211 (19%) had an EHR-documented SDH referral. Only 15% to 21% of patients with a documented SDH need indicated wanting help. Examples of lessons learned on adoption of EHR SDH tools indicate that clinics should: consider how to best integrate tools into existing workflow processes; ensure that staff tasked with SDH efforts receive adequate tool training and access; and consider that timing of data entry impacts how and when SDH data can be used.

CONCLUSIONS

Our results indicate that adoption of systematic EHR-based SDH documentation may be feasible, but substantial barriers to adoption exist. Lessons from this study may inform primary care providers seeking to implement SDH-related efforts, and related health policies. Far more research is needed to address implementation barriers related to SDH documentation in EHRs.