The Construction and Meaning of Race Within Hypertension Guidelines: A Systematic Scoping Review.

BACKGROUND: Professional society guidelines are evidence-based recommendations intended to promote standardized care and improve health outcomes. Amid increased recognition of the role racism plays in shaping inequitable healthcare delivery, many researchers and practitioners have critiqued existing guidelines, particularly those that include race-based recommendations. Critiques highlight how racism influences the evidence that guidelines are based on and its interpretation. However, few have used a systematic methodology to examine race-based recommendations. This review examines hypertension guidelines, a condition affecting nearly half of all adults in the United States (US), to understand how guidelines reference and develop recommendations related to race. METHODS: A systematic scoping review of all professional guidelines on the management of essential hypertension published between 1977 and 2022 to examine the use and meaning of race categories. RESULTS: Of the 37 guidelines that met the inclusion criteria, we identified a total of 990 mentions of race categories. Black and African/African American were the predominant race categories referred to in guidelines (n = 409). Guideline authors used race in five key domains: describing the prevalence or etiology of hypertension; characterizing prior hypertension studies; describing hypertension interventions; social risk and social determinants of health; the complexity of race. Guideline authors largely used race categories as biological rather than social constructions. None of the guidelines discussed racism and the role it plays in perpetuating hypertension inequities. DISCUSSION: Hypertension guidelines largely refer to race as a distinct and natural category rather than confront the longstanding history of racism within and beyond the medical system. Normalizing race as a biological rather than social construct fails to address racism as a key determinant driving inequities in cardiovascular health. These changes are necessary to produce meaningful structural solutions that advance equity in hypertension education, research, and care delivery.

Evaluating Intensity, Complexity, and Potential for Causal Inference in Social Needs Interventions: A Review of a Scoping Review.

Importance: Interventions that address needs such as low income, housing instability, and safety are increasingly appearing in the health care sector as part of multifaceted efforts to improve health and health equity, but evidence relevant to scaling these social needs interventions is limited. Objective: To summarize the intensity and complexity of social needs interventions included in randomized clinical trials (RCTs) and assess whether these RCTs were designed to measure the causal effects of intervention components on behavioral, health, or health care utilization outcomes. Evidence Review: This review of a scoping review was based on a Patient-Centered Outcomes Research Institute-funded evidence map of English-language US-based RCTs of social needs interventions published between January 1, 1995, and April 6, 2023. Studies were assessed for features related to intensity (defined using modal values as providing as-needed interaction, 8 participant contacts or more, contacts occurring every 2 weeks or more often, encounters of 30 minutes or longer, contacts over 6 months or longer, or home visits), complexity (defined as addressing multiple social needs, having dedicated staff, involving multiple intervention components or practitioners, aiming to change multiple participant behaviors [knowledge, action, or practice], requiring or providing resources or active assistance with resources, and permitting tailoring), and the ability to assess causal inferences of components (assessing interventions, comparators, and context). Findings: This review of a scoping review of social needs interventions identified 77 RCTs in 93 publications with a total of 135 690 participants. Most articles (68 RCTs [88%]) reported 1 or more features of high intensity. All studies reported 1 or more features indicative of high complexity. Because most studies compared usual care with multicomponent interventions that were moderately or highly dependent on context and individual factors, their designs permitted causal inferences about overall effectiveness but not about individual components. Conclusions and Relevance: Social needs interventions are complex, intense, and include multiple components. Our findings suggest that RCTs of these interventions address overall intervention effectiveness but are rarely designed to distinguish the causal effects of specific components despite being resource intensive. Future studies with hybrid effectiveness-implementation and sequential designs, and more standardized reporting of intervention intensity and complexity could help stakeholders assess the return on investment of these interventions.

Clinical Care Adjustments Based on Socioeconomic Adversity.

This Viewpoint discusses methods for addressing socioeconomic challenges to receiving equitable care that children face.

New Supplemental Benefits and Plan Ratings Among Medicare Advantage Enrollees.

Importance: In 2018, the US Congress gave Medicare Advantage (MA) historic flexibility to address members' social needs with a set of Special Supplemental Benefits for the Chronically Ill (SSBCIs). In response, the Centers for Medicare & Medicaid Services expanded the definition of primarily health-related benefits (PHRBs) to include nonmedical services in 2019. Uptake has been modest; MA plans cited a lack of evidence as a limiting factor. Objective: To evaluate the association between adopting the expanded supplemental benefits designed to address MA enrollees' nonmedical and social needs and enrollees' plan ratings. Design, Setting, and Participants: This cohort study compared the plan ratings of MA enrollees in plans that adopted an expanded PHRB, SSBCI, or both using difference-in-differences estimators with MA Consumer Assessment of Health Care Providers and Systems survey data from March to June 2017, 2018, 2019, and 2021 linked to Medicare administrative claims and publicly available benefits and enrollment data. Data analysis was performed between April 2023 and March 2024. Exposure: Enrollees in MA plans that adopted a PHRB and/or SSBCI in 2021. Main Outcomes and Measures: Enrollee plan rating on a 0- to 10-point scale, with 0 indicating the worst health plan possible and 10 indicating the best health plan possible. Results: The study sample included 388 356 responses representing 467 MA contracts and 2558 plans in 2021. Within the weighted population of responders, the mean (SD) age was 74.6 (8.7) years, 57.2% were female, 8.9% were fully Medicare-Medicaid dual eligible, 74.6% had at least 1 chronic medical condition, 13.7% had not graduated high school, 9.7% were helped by a proxy, 45.1% reported fair or poor physical health, and 15.6% were entitled to Medicare due to disability. Adopting both a new PHRB and SSBCI benefit in 2021 was associated with an increase of 0.22 out of 10 points (95% CI, 0.4-4.0 points) in mean enrollee plan ratings. There was no association between adoption of only a PHRB (adjusted difference, -0.12 points; 95% CI, -0.26 to 0.02 points) or SSBCI (adjusted difference, 0.09 points; 95% CI, -0.03 to 0.21 points) and plan rating. Conclusions and Relevance: Medicare Advantage plans that adopted both benefits saw modest increases in mean enrollee plan ratings. This evidence suggests that more investments in supplemental benefits were associated with improved plan experiences, which could contribute to improved plan quality ratings.

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

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

Adjusting Clinical Plans Based on Social Context.

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

Structured and unstructured social risk factor documentation in the electronic health record underestimates patients' self-reported risks.

OBJECTIVES: National attention has focused on increasing clinicians' responsiveness to the social determinants of health, for example, food security. A key step toward designing responsive interventions includes ensuring that information about patients' social circumstances is captured in the electronic health record (EHR). While prior work has assessed levels of EHR "social risk" documentation, the extent to which documentation represents the true prevalence of social risk is unknown. While no gold standard exists to definitively characterize social risks in clinical populations, here we used the best available proxy: social risks reported by patient survey. MATERIALS AND METHODS: We compared survey results to respondents' EHR social risk documentation (clinical free-text notes and International Statistical Classification of Diseases and Related Health Problems [ICD-10] codes). RESULTS: Surveys indicated much higher rates of social risk (8.2%-40.9%) than found in structured (0%-2.0%) or unstructured (0%-0.2%) documentation. DISCUSSION: Ideally, new care standards that include incentives to screen for social risk will increase the use of documentation tools and clinical teams' awareness of and interventions related to social adversity, while balancing potential screening and documentation burden on clinicians and patients. CONCLUSION: EHR documentation of social risk factors currently underestimates their prevalence.

Revising the Logic Model Behind Health Care's Social Care Investments.

Policy Points This article summarizes recent evidence on how increased awareness of patients' social conditions in the health care sector may influence health and health care utilization outcomes. Using this evidence, we propose a more expansive logic model to explain the impacts of social care programs and inform future social care program investments and evaluations.

Caregivers' and providers' perspectives of social and medical care after pediatric liver transplant: Results from the multicenter SOCIAL-Tx study.

Disparities exist in pediatric liver transplant (LT). We characterized barriers and facilitators to providing transplant and social care within pediatric LT clinics. This was a multicenter qualitative study. We oversampled caregivers reporting household financial strain, material economic hardship, or demonstrating poor health literacy. We also enrolled transplant team members. We conducted semistructured interviews with participants. Caregiver interviews focused on challenges addressing transplant and household needs. Transplant provider interviews focused on barriers and facilitators to providing social care within transplant teams. Interviews were recorded, transcribed, and coded according to the Capability, Opportunity, Motivation-Behavior model. We interviewed 27 caregivers and 27 transplant team members. Fifty-two percent of caregivers reported a household income <$60,000, and 62% reported financial resource strain. Caregivers reported experiencing (1) high financial burdens after LT, (2) added caregiving labor that compounds the financial burden, (3) dependency on their social network's generosity for financial and logistical support, and (4) additional support being limited to the perioperative period. Transplant providers reported (1) relying on the pretransplant psychosocial assessment for identifying social risks, (2) discomfort initiating social risk discussions in the post-transplant period, (3) reliance on social workers to address new social risks, and (4) social workers feeling overburdened by quantity and quality of the social work referrals. We identified barriers to providing effective social care in pediatric LT, primarily a lack of comfort in assessing and addressing new social risks in the post-transplant period. Addressing these barriers should enhance social care delivery and improve outcomes for these children.

Associations between Social Adversity and Biomarkers of Inflammation, Stress, and Aging in Children.

BACKGROUND: Prior work has found relationships between childhood social adversity and biomarkers of stress, but knowledge gaps remain. To help address these gaps, we explored associations between social adversity and biomarkers of inflammation (interleukin-1ß [IL-1ß], IL-6, IL-8, tumor necrosis factor-alpha [TNF-α], and salivary cytokine hierarchical "clusters" based on the three interleukins), neuroendocrine function (cortisol, cortisone, dehydroepiandrosterone, testosterone, and progesterone), neuromodulation (N-arachidonoylethanolamine, stearoylethanolamine, oleoylethanolamide, and palmitoylethanolamide), and epigenetic aging (Pediatric-Buccal-Epigenetic clock). METHODS: We collected biomarker samples of children ages 0-17 recruited from an acute care pediatrics clinic and examined their associations with caregiver-endorsed education, income, social risk factors, and cumulative adversity. We calculated regression-adjusted means for each biomarker and compared associations with social factors using Wald tests. We used logistic regression to predict being in the highest cytokine cluster based on social predictors. RESULTS: Our final sample included 537 children but varied based on each biomarker. Cumulative social adversity was significantly associated with having higher levels of all inflammatory markers and with cortisol, displaying a U-shaped distribution. There were no significant relationships between cumulative social adversity and cortisone, neuromodulation biomarkers or epigenetic aging. CONCLUSION: Our findings support prior work suggesting that social stress exposures contribute to increased inflammation in children. IMPACT: Our study is one of the largest studies examining associations between childhood social adversity and biomarkers of inflammation, neuroendocrine function, neuromodulation, and epigenetic aging. It is one of the largest studies to link childhood social adversity to biomarkers of inflammation, and the first of which we are aware to link cumulative social adversity to cytokine clusters. It is also one of the largest studies to examine associations between steroids and epigenetic aging among children, and one of the only studies of which we are aware to examine associations between social adversity and endocannabinoids among children. CLINICAL TRIAL REGISTRATION: NCT02746393.

Caregiver Perceptions of Social Risk Screening in Pediatric Liver Transplantation: From the Multicenter SOCIAL-Tx Study.

BACKGROUND: The social determinants of health contribute to adverse post-liver transplant outcomes. Identifying unmet social risks may enable transplant teams to improve long-term outcomes for at-risk children. However, providers may feel uncomfortable asking about household-level social risks in the posttransplant period because they might make their patients/families uncomfortable. METHODS: We conducted a mixed-methods analysis of caregiver participants (ie, parents/guardians of pediatric liver transplant recipients) in the Social and Contextual Impact on Children Undergoing Liver Transplantation study to assess their perceptions of provider-based social risk screening. Participants (N = 109) completed a 20-min social determinants of health questionnaire that included questions on the acceptability of being asked intimate social risk questions. A subset of participants (N = 37) engaged in an in-depth qualitative interview to share their perceptions of social risk screening. RESULTS: Of 109 participants across 9 US transplant centers, 60% reported financial strain and 30% reported at least 1 material economic hardship (eg, food insecurity, housing instability). Overall, 65% of respondents reported it very or somewhat appropriate and 25% reported being neutral to being screened for social risks in a liver transplant setting. In qualitative analyses, participants reported trust in the providers and a clear understanding of the intention of the screening as prerequisites for liver transplant teams to perform social risk screening. CONCLUSIONS: Only a small minority of caregivers found social risk screening unacceptable. Pediatric liver transplant programs should implement routine social risk screening and prioritize the patient and family voices when establishing a screening program to ensure successful implementation.

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.

Hospital Characteristics Associated With Social Needs Activities in the US.

This study assesses what hospital characteristics, including hospital participation in payment and delivery reform, are associated with activities related to health-related social needs.

Advancing health equity through social care interventions.

OBJECTIVE: To use evidence on addressing racism in social care intervention research to create a framework for advancing health equity for all populations with marginalized social identities (e.g., race, gender, and sexual orientation). Such groups have disproportionate social needs (e.g., food insecurity) and negative social determinants of health (SDOH; e.g., poverty). We recommend how the Agency for Healthcare Research and Quality (AHRQ) could advance health equity for marginalized populations through social care research and care delivery. DATA SOURCES AND STUDY SETTING: This commentary is informed by a literature review of social care interventions that were affiliated with healthcare systems; input from health equity researchers, policymakers, and community leaders attending the AHRQ Health Equity Summit; and consensus of the authors. PRINCIPAL FINDINGS: We recommend that AHRQ: (1) create an ecosystem that values research on SDOH and the effectiveness and implementation of social care interventions in the healthcare sector; (2) work with other federal agencies to (a) develop position statements with actionable recommendations about racism and other systems that perpetuate marginalization based on social identity and (b) develop aligned, complementary approaches to research and care delivery that address social marginalization; (3) advance both inclusive care delivery and inclusive research teams; (4) advance understanding of racism as a social determinant of health and effective strategies to mitigate its adverse impact on health; (5) advance the creation and scaling of effective strategies for addressing SDOH in healthcare systems, particularly in co-creation with community partners; and (6) require social care intervention researchers to use methods that advance our understanding of social health equity. CONCLUSIONS: AHRQ, as a federal agency, could help advance health equity using a range of strategies, including using the agency's levers to ensure AHRQ stakeholders examine and address the unique experiences of socially marginalized populations in SDOH and social care intervention research.

Evaluating the comparability of patient-level social risk data extracted from electronic health records: A systematic scoping review.

Objective: To evaluate how and from where social risk data are extracted from EHRs for research purposes, and how observed differences may impact study generalizability. Methods: Systematic scoping review of peer-reviewed literature that used patient-level EHR data to assess 1 ± 6 social risk domains: housing, transportation, food, utilities, safety, social support/isolation. Results: 111/9022 identified articles met inclusion criteria. By domain, social support/isolation was most often included (N = 68/111), predominantly defined by marital/partner status (N = 48/68) and extracted from structured sociodemographic data (N = 45/48). Housing risk was defined primarily by homelessness (N = 39/49). Structured housing data was extracted most from billing codes and screening tools (N = 15/30, 13/30, respectively). Across domains, data were predominantly sourced from structured fields (N = 89/111) versus unstructured free text (N = 32/111). Conclusion: We identified wide variability in how social domains are defined and extracted from EHRs for research. More consistency, particularly in how domains are operationalized, would enable greater insights across studies.

"Wanting the Best for Our Folks"-A Mixed Methods Analysis of Community Health Center Social Risk Screening Initiatives.

BACKGROUND: Many community health centers (CHC) are scaling social risk screening in response to growing awareness of the influence of social adversity on health outcomes and concurrent incentives for social risk data collection. We studied the implementation of social risk screening in Texas CHCs to inform best practices and understand equity implications. METHODS: Convergent mixed methods of 3 data sources. Using interviews and surveys with CHC providers and staff, we explored social risk screening practices to identify barriers and facilitators; we used electronic health record (EHR) data to assess screening reach and disparities in screening. RESULTS: Across 4 urban/suburban Texas CHCs, we conducted 27 interviews (15 providers/12 staff) and collected 97 provider surveys; 2 CHCs provided EHR data on 18,672 patients screened during the study period. Data revealed 2 cross-cutting themes: 1) there was broad support for social risk screening/care integration that was rooted in CHCs' mission and positionalities, and 2) barriers to social risk screening efforts were largely a result of limited time and staffing. Though EHR data showed screens per month and screens/encounters increased peri-pandemic (4.1% of encounters in 8/2019 to 46.1% in 2/2021), there were significant differences in screening rates by patient race/ethnicity and preferred language (P < .001). In surveys, 90.0% of surveyed providers reported incorporating social risk screening into patient conversations; 28.6% were unaware their clinic had an embedded screening tool. CONCLUSIONS: Study CHCs were in the early stages of standardizing social risk screening. Differences in screening reach by patient demographics raise concerns that social screening initiatives, which often serve as a path to resource/service connection, might exacerbate disparities. Overcoming barriers to reach, sustainability, and equity requires supports targeted to program design/development, workforce capacity, and quality improvement.

Social and Medical Care Integration Practices Among Children's Hospitals.

OBJECTIVES: In response to evidence linking social risk factors and adverse health outcomes, new incentives have emerged for hospitals to screen for adverse social determinants of health (SDOH). However, little information is available about the current state of social risk-related care practices among children's hospitals. To address outstanding knowledge gaps, we sought to describe social risk-related care practices among a national sample of children's hospitals. METHODS: We analyzed responses to the 2020 American Hospital Association Annual Survey. Among children's hospitals, we calculated the prevalence of screening for social needs, strategies to address social risks/needs, partnerships with community-based organizations to address social risks/needs at the individual and community level, and rates of impact assessments of how social risk-related interventions affect outcomes. We also used χ2 tests to compare results by hospital characteristics. We weighted results to adjust for nonresponse. RESULTS: The sample included 82 children's hospitals. A total of 79.6% screened for and 96.0% had strategies to address at least 1 social risk factor, although rates varied by SDOH domain. Children's hospitals more commonly partnered with community-based organizations to address patient-level social risks than to participate in community-level initiatives. A total of 39.2% of hospitals assessed SDOH intervention effectiveness. Differences in social risk-related care practices commonly varied by hospital ownership and Medicaid population but not by region. CONCLUSIONS: We found wide variability in social risk-related care practices among children's hospitals based on the risk domain and hospital characteristics. Findings can be used to monitor whether social risk-related care practices change in the setting of new incentives.

Social Determinants of Health Documentation in Structured and Unstructured Clinical Data of Patients With Diabetes: Comparative Analysis.

Background: Electronic health records (EHRs) have yet to fully capture social determinants of health (SDOH) due to challenges such as nonexistent or inconsistent data capture tools across clinics, lack of time, and the burden of extra steps for the clinician. However, patient clinical notes (unstructured data) may be a better source of patient-related SDOH information. Objective: It is unclear how accurately EHR data reflect patients' lived experience of SDOH. The manual process of retrieving SDOH information from clinical notes is time-consuming and not feasible. We leveraged two high-throughput tools to identify SDOH mappings to structured and unstructured patient data: PatientExploreR and Electronic Medical Record Search Engine (EMERSE). Methods: We included adult patients (≥18 years of age) receiving primary care for their diabetes at the University of California, San Francisco (UCSF), from January 1, 2018, to December 31, 2019. We used expert raters to develop a corpus using SDOH in the compendium as a knowledge base as targets for the natural language processing (NLP) text string mapping to find string stems, roots, and syntactic similarities in the clinical notes of patients with diabetes. We applied advanced built-in EMERSE NLP query parsers implemented with JavaCC. Results: We included 4283 adult patients receiving primary care for diabetes at UCSF. Our study revealed that SDOH may be more significant in the lives of patients with diabetes than is evident from structured data recorded on EHRs. With the application of EMERSE NLP rules, we uncovered additional information from patient clinical notes on problems related to social connectionsisolation, employment, financial insecurity, housing insecurity, food insecurity, education, and stress. Conclusions: We discovered more patient information related to SDOH in unstructured data than in structured data. The application of this technique and further investment in similar user-friendly tools and infrastructure to extract SDOH information from unstructured data may help to identify the range of social conditions that influence patients' disease experiences and inform clinical decision-making.

Community Health Center Staff Perspectives on Financial Payments for Social Care.

Policy Points State and federal payers are actively considering strategies to increase the adoption of social risk screening and interventions in health care settings, including through the use of financial incentives. Activities related to social care in Oregon community health centers (CHCs) provided a unique opportunity to explore whether and how fee-for-service payments for social risk screening and navigation influence CHC activities. CHC staff, clinicians, and administrative leaders were often unaware of existing financial payments for social risk screening and navigation services. As currently designed, fee-for-service payments are unlikely to strongly influence CHC social care practices. CONTEXT: A growing crop of national policies has emerged to encourage health care delivery systems to ask about and try to address patients' social risks, e.g., food, housing, and transportation insecurity, in care delivery contexts. In this study, we explored how community health center (CHC) staff perceive the current and potential influence of fee-for-service payments on clinical teams' engagement in these activities. METHODS: We interviewed 42 clinicians, frontline staff, and administrative leaders from 12 Oregon CHC clinical sites about their social care initiatives, including about the role of existing or anticipated financial payments intended to promote social risk screening and referrals to social services. Data were analyzed using both inductive and deductive thematic analysis approaches. FINDINGS: We grouped findings into three categories: participants' awareness of existing or anticipated financial incentives, uses for incentive dollars, and perceived impact of financial incentives on social care activities in clinical practices. Lack of awareness of existing incentives meant these incentives were not perceived to influence the behaviors of staff responsible for conducting screening and providing referrals. Current or anticipated meaningful uses for incentive dollars included paying for social care staff, providing social services, and supporting additional fundraising efforts. Frontline staff reported that the strongest motivator for clinic social care practices was the ability to provide responsive social services. Clinic leaders/managers noted that for financial incentives to substantively change CHC practices would require payments sizable enough to expand the social care workforce as well. CONCLUSIONS: Small fee-for-service payments to CHCs for social risk screening and navigation services are unlikely to markedly influence CHC social care practices. Refining the design of financial incentives-e.g., by increasing clinical teams' awareness of incentives, linking screening to well-funded social services, and changing incentive amounts to support social care staffing needs-may increase the uptake of social care practices in CHCs.