Effectiveness of Social Needs Screening and Interventions in Clinical Settings on Utilization, Cost, and Clinical Outcomes: A Systematic Review

Differences in Healthcare Utilization Across 2 Social Health Support Modalities: Results From a Randomized Pilot Evaluation

Introduction

The aim of this study was to assess differences in utilization outcomes among patients with social needs as part of a pilot social health integration program in 2 clinics in an integrated health system in the Pacific Northwest.

Methods

Patients who reported social needs between October 2022 and January 2023 were randomized to receive support from either local, clinic-based community resource specialists or a centralized Connections Call Center. The authors used administrative and claims data for 534 participants to compare the following utilization outcomes between arms over 9 months after randomization: primary care encounters, specialty care encounters, behavioral health encounters, emergency department encounters, inpatient admissions, urgent care encounters, and secure patient messages. Using an intent-to-treat approach, the authors used negative binomial regression models to compare visit counts and logistic regression to estimate differences in the probability of any emergency department visit or inpatient admissions between groups. The authors conducted secondary as-treated analyses comparing participants who received resource information from community resource specialists with those who did not.

Results

Unadjusted results showed no statistically significant differences between community resource specialists and Connections Call Center. Adjusted results showed that community resource specialist participants received 1.04 more primary care encounters than Connections Call Center participants (95% CI=0.336, 1.746). As-treated results showed that participants who received support from community resource specialists had higher counts of primary care encounters, specialty care encounters, and patient messages than those who did not.

Conclusions

Beyond social needs navigation, clinic-based supports may be better integrated with care teams to provide ongoing support for patients' medical needs. Findings from this primary care social health pilot program showed that local, clinic-based support was associated with greater outpatient utilization than a call center support.

Patient and clinician acceptability of automated extraction of social drivers of health from clinical notes in primary care

OBJECTIVE

Artificial Intelligence (AI)-based approaches for extracting Social Drivers of Health (SDoH) from clinical notes offer healthcare systems an efficient way to identify patients' social needs, yet we know little about the acceptability of this approach to patients and clinicians. We investigated patient and clinician acceptability through interviews.

MATERIALS AND METHODS

We interviewed primary care patients experiencing social needs (n = 19) and clinicians (n = 14) about their acceptability of "SDoH autosuggest," an AI-based approach for extracting SDoH from clinical notes. We presented storyboards depicting the approach and asked participants to rate their acceptability and discuss their rationale.

RESULTS

Participants rated SDoH autosuggest moderately acceptable (mean = 3.9/5 patients; mean = 3.6/5 clinicians). Patients' ratings varied across domains, with substance use rated most and employment rated least acceptable. Both groups raised concern about information integrity, actionability, impact on clinical interactions and relationships, and privacy. In addition, patients raised concern about transparency, autonomy, and potential harm, whereas clinicians raised concern about usability.

DISCUSSION

Despite reporting moderate acceptability of the envisioned approach, patients and clinicians expressed multiple concerns about AI systems that extract SDoH. Participants emphasized the need for high-quality data, non-intrusive presentation methods, and clear communication strategies regarding sensitive social needs. Findings underscore the importance of engaging patients and clinicians to mitigate unintended consequences when integrating AI approaches into care.

CONCLUSION

Although AI approaches like SDoH autosuggest hold promise for efficiently identifying SDoH from clinical notes, they must also account for concerns of patients and clinicians to ensure these systems are acceptable and do not undermine trust.

Social Risk and Acute Health Care Utilization Among Insured Adults

Importance

Millions of Americans are impacted by adverse social risk factors such as financial strain, housing instability, and food insecurity. A better understanding of if and how these factors are associated with acute care utilization is needed.

Objective

To examine the association between exposure to social risk factors and emergency department (ED) visits and hospitalizations among a sample of insured adults.

Design, Setting, and Participants

This cohort study used US health data from a national initiative that employed a multistage, stratified sampling framework across 8 regional markets of an integrated health care delivery system. Eligible participants were insured adults who responded to health surveys. Population-based samples were taken proportionate to the sex and age distribution of each market.

Exposures

Validated survey questions captured social risk exposure (positive screening for financial strain, housing instability, and/or food insecurity) during the past year; across 2 survey waves (2020, 2022). Self-reported social risk was categorized into mutually exclusive risk levels, social risk vs no social risk.

Main Outcomes and Measures

Primary outcome was acute health care utilization defined as time to the first event (ED visit, hospitalization) observed following the first survey completion (January 2020 to July 2023). Weighted Cox proportional hazards regression examined the association between social risk and subsequent care utilization, adjusting for demographic and clinical covariates.

Results

The analytic cohort included 9785 survey respondents. The weighted cohort data (mean age, 48.4 years [95% CI, 47.9-48.9 years]) included 54.1% female respondents (95% CI, 52.3%-55.9%); 14.6% of the sample were Asian (95% CI, 13.3%-16.0%), 8.1% Black (95% CI, 7.3%-9.1%), 27.1% Hispanic (95% CI, 25.5%-28.8%), and 43.6% non-Hispanic White (95% CI, 41.2%-44.7%); and 50.3% reported exposure to 1 or more social risk factor. During the follow-up period (median [IQR], 3.48 [3.01-3.50] years), 25.4% (95% CI, 22.9%-28.1%) and 10.3% (95% CI, 8.9%-11.9%) of the cohort experienced an ED visit and hospitalization, respectively. Utilization rates varied by level of social risk exposure. Respondents who reported any social risk had a 21% higher risk of an ED visit compared with those with no social risk exposure (adjusted hazard ratio [HR], 1.21 [95% CI, 1.03-1.41]). Social risk was not associated with hospitalizations (adjusted HR, 1.05 [95% CI, 0.84-1.32]).

Conclusions and Relevance

In this cohort of 9785 adults, the significant association between social risk and time to first ED event warrants future study to determine if improved social risk are associated with lower ED utilization.

Integrating Social Needs into Health Care: An Implementation Science Perspective

Unmet social needs (e.g., housing instability, food insecurity, transportation barriers) impact a patient's ability to participate in health-seeking behaviors (e.g., physical activity, routine preventive care) and to achieve optimal health. A rapidly growing number of health care systems are incorporating social needs screening and assistance into clinical workflows, yet many implementation and sustainability challenges exist and require collaboration with social service organizations. This review highlights implementation approaches used within this rapidly changing US landscape and uses implementation science frameworks to systematically identify multilevel barriers to and facilitators of implementing and sustaining social needs care. Policies and economic investments are necessary as they determine critical barriers and facilitators within the clinical and social service contexts. Implementation may be further strengthened by cross-sector engagement, evidence-based implementation strategies, and capacity building within clinical and social service organizations. Successful, sustained implementation of social needs care may improve the quality of health care, population health, and health equity.

Hospital-Based Interventions Addressing Social Needs: A Systematic Narrative Review

INTRODUCTION

Healthcare settings worldwide are adopting screening and referral interventions to address patients' social needs. Some interventions provide one-off lists of resources ("light-touch" interventions) while others employ Health Navigators to provide ongoing assistance and advocacy with community organizations ("high-touch" interventions). Understanding the manner in which these interventions are integrated in hospital settings, and their effects on medical and social outcomes, is limited.

METHODS

This systematic narrative review uses narrative synthesis to explore workflows for screening and referral interventions for social needs in hospital settings, and barriers and enablers to intervention success. Health and social science databases (Embase, CINAHL, PubMed, PsycInfo, Scopus, Web of Science) and grey literature (ProQuest) were searched. Conference abstracts and editorial papers were excluded. This review was prospectively registered in PROSPERO (registration number: CRD42023462535). Data were collected and analyzed from January 2023 to August 2024.

RESULTS

All studies (n=37) occurred in the U.S. Interventions took place in emergency departments, inpatient and outpatient clinics, and hospital-based primary care clinics. Overall, studies were of moderate quality (n=22, 59%), and provided limited methodological data regarding workflows for screening and responding to social needs. High-touch interventions underreported caseload and other methodological data, and Health Navigator roles varied substantially. Few studies reported social needs outcomes, and intervention effects on outcomes were mixed.

DISCUSSION

To improve the evidence base for hospital-based interventions, researchers should prioritize reporting methodological data and publishing in-depth protocols. Social needs outcomes should be consistently reported to better understand how these interventions may benefit disadvantaged populations, and trauma-informed principles should be applied to the collection and storage of social needs data.

Implementation of a Loneliness Screening and Referral Program in Primary Care: A Mixed Methods Pilot Study

PURPOSE

Loneliness screening is recommended as best practice in primary care for older adults, yet it is not widely implemented. The purpose of the current study was to assess feasibility of a loneliness screening and referral program (SOCIAL Rx) in a primary care practice.

METHOD

Loneliness was assessed using the 3-item UCLA Loneliness Scale and curated referrals were provided for those who screened positive. Outcome measures were organized using the RE-AIM framework domains of reach, effectiveness, and adoption. Qualitative interviews were conducted to explore feasibility/acceptability and patient preferences regarding referrals.

RESULTS

Eighty-one percent of patients were screened for loneliness; 33.3% were somewhat lonely and 17.7% were very lonely. Fifty-two percent of those who were lonely were provided a referral, and 40% of providers referred ≥50% of eligible patients.

CONCLUSION

Loneliness was prevalent in this population of older adults, highlighting the imperative for screening and intervention. [Research in Gerontological Nursing, 18(2), 69-80.].

Associations of social support, living arrangements, and residential stability with cancer screening in the United States

PURPOSE

Social support has been linked to increased use of preventive care services. Living arrangements and residential stability may be important structural sources of social support, but few studies have examined their impact on cancer screening.

METHODS

Data were from the 2021 National Health Interview Survey. Participants were classified as up-to-date or not with female breast cancer (BC), cervical cancer (CVC), and colorectal cancer (CRC) screening recommendations. Multivariable logistic regression was used to model associations between screening and residential stability (< 1 year, 1-3 years, 4-10 years, 11-20 years, or > 20 years), living arrangement (with spouse/partner only, children only, both, or neither), and perceived social support (rarely/never, sometimes, usually, or always available), overall and stratified by sex (CRC) and age group (CVC).

RESULTS

The adjusted odds of BC (odds ratio [OR]  0.61, 95% CI 0.45-0.81) and CVC (OR 0.76, 95% CI 0.60-0.96) screening were lowest for those who reported never/rarely vs. always having social support. The adjusted odds of BC (OR 1.44, 95% CI 1.22-1.70) and CRC (ORFEMALE = 1.42, 95% CI 1.20-1.68; ORMALE = 1.61, 95% CI 1.35-1.90) screening were higher for those living with a spouse/partner only vs. those living with neither spouse/partner nor children. Less residential stability was associated with increased CVC screening among females 21-34 years of age, but not BC or CRC screening.

CONCLUSIONS

Social support measures were associated with screening to varying degrees by site and age, but higher perceived social support and living with a spouse/partner only demonstrated a consistent positive association. Interventions that mobilize social support networks and address the unmet social needs of parents/caregivers may improve cancer control.

Screening and Referral for Social Needs Among Veterans: A Randomized Controlled Trial

BACKGROUND

Healthcare-based social need screening and referral (S&R) among adult populations has produced equivocal results regarding social need resource connection.

OBJECTIVE

Assess the efficacy of S&R on resource connection (primary outcome) and unmet need reduction (secondary outcome).

DESIGN

Intention-to-treat randomized controlled trial. Analyses adjusted for demographics (e.g., age, race), comorbidity (Elixhauser), and VA priority group (PG).

PARTICIPANTS

Veterans with and at-risk for cardiovascular disease and one of more (hereafter " ≥ 1") social needs receiving healthcare at one of three Veterans Healthcare Administration (VHA) medical facilities.

INTERVENTION

Study arms represented referral strategies of varying intensity. Arm 1 (control) received generic resource information; Arm 2 (low intensity) received generic and tailored resource information; Arm 3 (high intensity) received all the above plus social work navigation assistance.

MAIN MEASURES

Post index surveys at 2-months assessed resource connection (connection to ≥ 1 new resources) and 6-months assessed need reduction (≥ 1 needs at the index screen no longer identified).

KEY RESULTS

A total of 479 Veterans were randomized: 50% were minoritized Veterans, mean age was 64, and 91% were male. Arm 3 was associated with greater resource connection but differences across study arms were not statistically significant. For example, compared to the control arm, participants in Arm 3 had higher but non-statistically significant odds of connecting to ≥ 1 resources (OR = 1.60, CI [.96, 2.67]).

CONCLUSIONS

Among VHA-enrolled Veterans, a high-intensity S&R intervention was associated with a non-statistically significant increase in connection to social need resources. Further study needed to establish S&R efficacy.

TRIAL REGISTRATION

NCT04977583.

1. Improving Care and Promoting Health in Populations: Standards of Care in Diabetes-2025

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Health-related social needs screening, reporting, and assistance in a large health system

BACKGROUND

National mandates require screening for and addressing health-related social needs (HRSNs) in healthcare settings. However, differences in HRSN screening process (i.e., completed screenings, screening results, documented offer of assistance, documented assistance request) have been reported by population subgroup. Knowledge of the most effective HRSN screening and intervention methods is limited. We sought to describe differences in completed HRSN screenings, screening results, and assistance request rates across patient and healthcare visit characteristics.

METHODS

We examined data from all patients aged ≥18 years and residing in the US receiving services at a large, Midwestern healthcare system with a goal to screen all patients for HRSN at least once annually between July 2021-June 2023 (n = 1,190,488). We examined the proportion of patients with any HRSN screening, with any reported HRSN, asked whether they wanted assistance, or who requested assistance for a reported HRSN stratified by patient demographics and healthcare visit characteristics (i.e., payer, screening location, who completed the screening).

RESULTS

Less than half of eligible patients (47.0 %) were screened for HRSNs. About one-sixth (16.9 %) reported any HRSN. Although most patients reporting HRSNs were asked whether they wanted assistance, only about one-quarter (26.8 %) responded affirmatively. Proportions included in each step of the HRSN screening process significantly differed by patient and healthcare visit characteristics.

DISCUSSION

This study is one of the first to investigate various steps of a population-wide HRSN screening program. Our findings suggest that examining differences in HRSN screening process by population subgroup is key to addressing HRSNs through a health equity lens.

The Impact of Language Discordance on Acquiring Broad Social History: A Qualitative Study of Patients, Clinicians, and Interpreters

BACKGROUND

By acquiring a broad social history (BSH), which includes aspects of patients' social needs in addition to their hobbies and activities, values, and perspectives on care, clinicians can provide more patient-centered care, which is known to improve health outcomes. However, the impact of patient-clinician language discordance on acquisition of BSH has not been well studied.

OBJECTIVE

To ascertain whether language discordance impacts clinicians' acquisition of patients' BSH by interviewing patients, clinicians, and medical interpreters.

DESIGN

Qualitative study based on semi-structured interviews, followed by thematic analysis using rapid qualitative data analysis methods.

PARTICIPANTS (OR PATIENTS OR SUBJECTS)

We interviewed 8 Spanish-speaking and 5 English-speaking patients seen for primary care within a public hospital in San Francisco, 6 primary care clinicians, and 8 medical interpreters.

APPROACH

All interviews were recorded and transcribed. The transcriptions were summarized into domains using rapid qualitative data analysis. The summaries were displayed in a matrix and used to generate themes and subthemes.

KEY RESULTS

Analysis of interviews highlighted two overarching themes concerning BSH acquisition. One theme was the importance of BSH: namely, it is critical for patient-clinician relationships and personalized care. Commonly elicited BSH facets were social drivers of health, but leisure activities were less frequently asked. The second theme described ways in which language discordance, via the need for interpretation, affects the collection of BSH, both through increasing time pressure, and hindering rapport-building strategies. Cultural barriers pose an obstacle to BSH acquisition and may operate independently of language discordance.

CONCLUSIONS

Our results suggest two action steps for health systems: (a) apportioning more time for language-discordant visits to increase rapport-building and BSH acquisition, and (b) increasing training for clinicians on acquiring BSH when working with interpreters. Further research is needed to investigate the relationship between language discordance, acquisition of BSH, and patient outcomes.

Standardizing social determinants of health data: a proposal for a comprehensive screening tool to address health equity a systematic review

Social determinants of health (SDoH) significantly impacts health outcomes and disparities. While the Centers for Medicare and Medicaid Services has mandated hospitals to collect standardized SDoH data, existing tools lack key elements. This systematic review identified 78 studies and 20 screening tools addressing various SDoH domains. However, most tools were missing several key domains and lacked standardization. We propose a comprehensive tool meeting essential criteria: validated questions, brevity, actionability, cultural appropriateness, workflow integration, and community linkage. Our tool addresses gaps in available tools and incorporates standardized and validated questions to enable patient-centered screening for diverse social and environmental determinants of health. It uniquely includes detailed race/ethnicity data collection, housing characteristics, physical activity assessment, access to healthy food measures, and environmental exposure evaluation. The tool aims to provide actionable data for immediate interventions while informing broader population health strategies and policy initiatives. By offering a holistic assessment of SDoH across multiple domains, our tool enables standardized data collection, risk stratification, and focused initiatives to address health inequities at both individual and population levels. Further research is needed to develop evidence-based pathways for integrating SDoH data into real-world patient care workflows, improve risk prediction algorithms, address health-related social needs, and reduce disparities.

A Compelling Health Promoting Primary Care Clinic Using a Settings-Based Approach: A Demonstration Project

The Ottawa Charter for Health Promotion, issued by the World Health Organization in 1986, called for several strategies to promote the public's health. One of the strategies was to create health-promoting health services. Over 35 years have passed since the Ottawa Charter was released, since then, efforts to improve health care have been implemented such as the Patient-Centered Medical Home, the Triple Aim, and the Affordable Care Act, yet little has been done to reorient the cultural and physical environment of health care services to one focused on health promotion. In this perspective, the author offers a compelling description of how one primary care clinic, serving an ethnically and economically diverse population, utilized a settings-based approach to design and implement several health-promoting policies, systems, and environmental strategies. This reorientation of a primary care clinic to one that is health-promoting leveraged the clinical specialty of lifestyle medicine as a cornerstone of the settings-based approach.

Health Navigator intervention to address the unmet social needs of populations living with cancer attending outpatient treatment at a major metropolitan hospital in Australia: protocol for a mixed-methods feasibility trial

INTRODUCTION

Integrating health and social care to address unmet social needs is an emerging priority for health systems worldwide. Screening and referral interventions for unmet social needs, also known as Health Navigator (HN) interventions, in healthcare settings have shown mixed but promising results, mostly due to a large variability in intervention design and outcomes assessed. Most HN interventions are implemented in primary care, despite evidence that disadvantaged populations face substantial barriers to accessing such care, and these interventions are limited in Australia. To address this gap, we designed a HN intervention to address the unmet social needs of a disadvantaged population living with cancer presenting at an outpatient cancer treatment facility in South Australia. To our knowledge, this paper presents a protocol for one of the first feasibility and acceptability studies of an HN intervention in an Australian healthcare setting.

METHODS AND ANALYSIS

We will conduct a single-centre study to explore the feasibility and acceptability of screening and referral for unmet social needs for patients attending an outpatient cancer clinic at a major metropolitan hospital serving a disadvantaged population in South Australia. Eligible participants are 18 years of age or older receiving treatment at the Northern Adelaide Cancer Centre, with an expected prognosis of minimum 6 months. During recruitment, a researcher will ask eligible participants to complete unmet social needs screening and baseline assessments. Participants with unmet social needs who request assistance will be connected with an HN. The HN will work with participants to prioritise their needs and provide referrals to community and government services with follow-up of over 6 months from enrolment. Post-HN intervention, all participants will be asked to complete repeat unmet social needs screening and repeat assessments. The primary criteria for determining feasibility success are: (1) recruitment rates, where 80% of eligible participants agree to unmet needs screening; (2) intervention uptake, where 80% of participants who report unmet social needs consent to assistance from a HN; (3) intervention completion, where 80% of participants receive HN assistance complete follow-up; (4) reasons for not completing intervention; and (5) participant and clinician acceptability of the intervention. Secondary outcomes include changes to unmet social needs and coping with cancer ability, quality of life and patient-reported experience measures. Thematic analysis will be applied to focus groups with clinicians and participants to assess intervention acceptability. Secondary clinical outcomes will be reported as effect size estimates for future trials. Based on previous work in this area, we will aim to recruit 350 participants. Study findings will be used to optimise recruitment and intervention components and develop suitable outcome measures for larger, randomised studies.

ETHICS AND DISSEMINATION

The protocol has ethical approval from the Central Adelaide Local Health Network Human Research Ethics Committee (approval ID: 16448). Findings will be disseminated in research publications and non-academic formats for a variety of audiences.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trial Registry (ACTRN12622000802707p).Protocol date and version: 07 June 2022, V1.

Comparing the performance of screening surveys versus predictive models in identifying patients in need of health-related social need services in the emergency department

BACKGROUND

Health-related social needs (HRSNs), such as housing instability, food insecurity, and financial strain, are increasingly prevalent among patients. Healthcare organizations must first correctly identify patients with HRSNs to refer them to appropriate services or offer resources to address their HRSNs. Yet, current identification methods are suboptimal, inconsistently applied, and cost prohibitive. Machine learning (ML) predictive modeling applied to existing data sources may be a solution to systematically and effectively identify patients with HRSNs. The performance of ML predictive models using data from electronic health records (EHRs) and other sources has not been compared to other methods of identifying patients needing HRSN services.

METHODS

A screening questionnaire that included housing instability, food insecurity, transportation barriers, legal issues, and financial strain was administered to adult ED patients at a large safety-net hospital in the mid-Western United States (n = 1,101). We identified those patients likely in need of HRSN-related services within the next 30 days using positive indications from referrals, encounters, scheduling data, orders, or clinical notes. We built an XGBoost classification algorithm using responses from the screening questionnaire to predict HRSN needs (screening questionnaire model). Additionally, we extracted features from the past 12 months of existing EHR, administrative, and health information exchange data for the survey respondents. We built ML predictive models with these EHR data using XGBoost (ML EHR model). Out of concerns of potential bias, we built both the screening question model and the ML EHR model with and without demographic features. Models were assessed on the validation set using sensitivity, specificity, and Area Under the Curve (AUC) values. Models were compared using the Delong test.

RESULTS

Almost half (41%) of the patients had a positive indicator for a likely HRSN service need within the next 30 days, as identified through referrals, encounters, scheduling data, orders, or clinical notes. The screening question model had suboptimal performance, with an AUC = 0.580 (95%CI = 0.546, 0.611). Including gender and age resulted in higher performance in the screening question model (AUC = 0.640; 95%CI = 0.609, 0.672). The ML EHR models had higher performance. Without including age and gender, the ML EHR model had an AUC = 0.765 (95%CI = 0.737, 0.792). Adding age and gender did not improve the model (AUC = 0.722; 95%CI = 0.744, 0.800). The screening questionnaire models indicated bias with the highest performance for White non-Hispanic patients. The performance of the ML EHR-based model also differed by race and ethnicity.

CONCLUSION

ML predictive models leveraging several robust EHR data sources outperformed models using screening questions only. Nevertheless, all models indicated biases. Additional work is needed to design predictive models for effectively identifying all patients with HRSNs.

Randomized pilot trial of an unconditional cash transfer intervention to address food insecurity in oncology

Screening for food insecurity and other social determinants of health is being integrated into oncology practice. We performed a pilot randomized trial to investigate whether an unconditional cash transfer (UCT) could be used to address food insecurity among female breast and gynecological cancer survivors. Food-insecure cancer survivors completed a baseline survey and were randomly assigned to receive $100/month for 3 months (UCT) or usual care (UC). Participants (n = 14) completed a follow-up survey after 3 months, and we compared changes in health-related quality of life, indicators of food insecurity, diet quality, and whether a participant had to forgo, delay, or make changes to medical care because of cost. The UCT was associated with higher physical health scores, fewer indicators of food insecurity, better diet quality, and a lower likelihood of forgoing medical care than those who received UC. Our results suggest that UCTs can improve outcomes for food-insecure cancer survivors.

Development, Implementation, and Formative Evaluation of a Social Needs Screening Tool

We aim to develop and formatively evaluate a brief social needs screening tool that adheres to Massachusetts Department of Public Health (MDPH) clinical service standards for sexual and reproductive health (SRH) agencies and is acceptable and feasible for use by staff during a clinical encounter. Through a multi-stage literature and expert review process, we developed an evidence-informed, two-page social needs screening tool, scoring form, and implementation guide. We piloted this tool at three SRH agencies in Massachusetts and recruited staff to provide quantitative and qualitative feedback through post-pilot test self-reported surveys and semi-structured interviews. Participants (n = 13) felt the social needs screening tool was easy to integrate into their clinical workflow and were comfortable using it with patients. All participants reported feeling comfortable administering the tool, scoring it, and referring patients to appropriate resources, if applicable. Most reported they would like to continue using the tool after the pilot implementation period, either with or without modifications. Our multi-stage tool development and formative evaluation process involving literature review, expert review, and pilot-testing in clinical settings enabled our team to create a brief, evidence-informed social needs screening tool that is acceptable to staff and feasible for use during a short clinic visit at SRH agencies in Massachusetts. Staff felt that there is value in using this tool, are comfortable using it, and are able to integrate it into their existing clinical workflows.

Implementation strategies to improve adoption of unmet social needs screening and referrals in care management using enabling technologies: study protocol for a cluster randomized trial

Background

Adverse social determinants of health contribute to health inequities. Practice guidelines now recommend incorporating patient unmet social needs into patient care, and payors increasingly reimburse for screening and providing related referrals to community organizations. Emergent electronic health record (EHR)-based tools can enable clinical-community linkages, but their adoption commonly faces workflow and infrastructure barriers. Targeted implementation support such as training, championship, practice facilitation, and audit and feedback, can enhance such tools' adoption, but no prior research has assessed such strategies' impact on the adoption of 'enabling technologies' supporting clinical-community linkages. This study will test whether providing targeted implementation support to safety-net primary care health center care management teams improves the sustained adoption of EHR-based enabling technologies used to 1) screen for social needs and 2) link patients to community organizations.

Methods

Formative evaluation of barriers and facilitators to adopting EHR-enabled social needs referrals and ascertainment of services received will include semi-structured interviews and a 'guided tour' of enabling technology used by care managers serving patients with complex health and/or social needs. A modified Delphi process conducted with care management staff and subject matter experts will then inform the development of an intervention targeting adoption of social risk EHR-enabled tools. The intervention will be piloted in three health centers, refined, then tested in a pragmatic stepped-wedge cluster-randomized trial in 20 health centers (five wedges of four health centers) that provide care management to high-risk patients with social needs.

Discussion

This study is among the first to evaluate an intervention designed to support care management teams' adoption of enabling technologies to increase clinical-community linkages. It was funded in September 2023 by the National Institute of Nursing Research. Formative activities will take place from January to June 2024, the intervention will be developed in July-December 2024, the pilot study will be conducted from January-March 2025, and the cluster-randomized trial will occur from July 2025 -September 2026. Study data will be analyzed and results disseminated in 2027-2028. Study results have the potential to improve clinical-community linkages and in so doing to advance health equity.

Trial registration

Clinicaltrials.gov registration # NCT06489002. Registered July 5, 2024, https//clinicaltrials.gov/study/NCT06489002?term=NCT06489002&rank=1.

Realizing the potential of social determinants data in EHR systems: A scoping review of approaches for screening, linkage, extraction, analysis, and interventions

Background

Social determinants of health (SDoH), such as socioeconomics and neighborhoods, strongly influence health outcomes. However, the current state of standardized SDoH data in electronic health records (EHRs) is lacking, a significant barrier to research and care quality.

Methods

We conducted a PubMed search using "SDOH" and "EHR" Medical Subject Headings terms, analyzing included articles across five domains: 1) SDoH screening and assessment approaches, 2) SDoH data collection and documentation, 3) Use of natural language processing (NLP) for extracting SDoH, 4) SDoH data and health outcomes, and 5) SDoH-driven interventions.

Results

Of 685 articles identified, 324 underwent full review. Key findings include implementation of tailored screening instruments, census and claims data linkage for contextual SDoH profiles, NLP systems extracting SDoH from notes, associations between SDoH and healthcare utilization and chronic disease control, and integrated care management programs. However, variability across data sources, tools, and outcomes underscores the need for standardization.

Discussion

Despite progress in identifying patient social needs, further development of standards, predictive models, and coordinated interventions is critical for SDoH-EHR integration. Additional database searches could strengthen this scoping review. Ultimately, widespread capture, analysis, and translation of multidimensional SDoH data into clinical care is essential for promoting health equity.

A Randomized Controlled Trial to Improve Unmet Social Needs and Clinical Outcomes Among Adults with Diabetes

BACKGROUND

Adults with type 1 or type 2 diabetes often face financial challenges and other unmet social needs to effective diabetes self-management.

OBJECTIVE

Whether a digital intervention focused on addressing socioeconomic determinants of health improves diabetes clinical outcomes more than usual care.

DESIGN

Randomized trial from 2019 to 2023.

PARTICIPANTS

A total of 600 adults with diabetes, HbA1c ≥ 7.5%, and self-reported unmet social needs or financial burden from a health system and randomized to the intervention or standard care.

INTERVENTION

CareAvenue is an automated, e-health intervention with eight videos that address unmet social needs contributing to poor outcomes.

MEASURES

Primary outcome was HbA1c, measured at baseline, and 6 and 12 months after randomization. Secondary outcomes included systolic blood pressure and reported met social needs, cost-related non-adherence (CRN), and financial burden. We examined main effects and variation in effects across predefined subgroups.

RESULTS

Seventy-eight percent of CareAvenue participants completed one or more modules of the website. At 12-month follow-up, there were no significant differences in HbA1c changes between CareAvenue and control group (p = 0.24). There were also no significant between-group differences in systolic blood pressure (p = 0.29), met social needs (p = 0.25), CRN (p = 0.18), and perceived financial burden (p = 0.31). In subgroup analyses, participants with household incomes 100-400% FPL (1.93 (SE = 0.76), p < 0.01), 201-400% FPL (1.30 (SE = 0.62), p < 0.04), and > 400% FPL (1.27 (SE = 0.64), p < 0.05) had significantly less A1c decreases compared to the control group.

CONCLUSIONS

On average, CareAvenue participants did not achieve better A1c lowering, met needs, CRN, or perceived financial burden compared to control participants. CareAvenue participants with higher incomes achieved significantly less A1c reductions than control. Further research is needed on social needs interventions that consider tailored approaches to population subgroups.

CLINICAL TRIALS REGISTRY

ClinicalTrials.gov ID NCT03950973, May 2019.

Predicting Self-Reported Social Risk in Medically Complex Adults Using Electronic Health Data

BACKGROUND

Social barriers to health care, such as food insecurity, financial distress, and housing instability, may impede effective clinical management for individuals with chronic illness. Systematic strategies are needed to more efficiently identify at-risk individuals who may benefit from proactive outreach by health care systems for screening and referral to available social resources.

OBJECTIVE

To create a predictive model to identify a higher likelihood of food insecurity, financial distress, and/or housing instability among adults with multiple chronic medical conditions.

RESEARCH DESIGN AND SUBJECTS

We developed and validated a predictive model in adults with 2 or more chronic conditions who were receiving care within Kaiser Permanente Northern California (KPNC) between January 2017 and February 2020. The model was developed to predict the likelihood of a "yes" response to any of 3 validated self-reported survey questions related to current concerns about food insecurity, financial distress, and/or housing instability. External model validation was conducted in a separate cohort of adult non-Medicaid KPNC members aged 35-85 who completed a survey administered to a random sample of health plan members between April and June 2021 (n = 2820).

MEASURES

We examined the performance of multiple model iterations by comparing areas under the receiver operating characteristic curves (AUCs). We also assessed algorithmic bias related to race/ethnicity and calculated model performance at defined risk thresholds for screening implementation.

RESULTS

Patients in the primary modeling cohort (n = 11,999) had a mean age of 53.8 (±19.3) years, 64.7% were women, and 63.9% were of non-White race/ethnicity. The final, simplified model with 30 predictors (including utilization, diagnosis, behavior, insurance, neighborhood, and pharmacy-based variables) had an AUC of 0.68. The model remained robust within different race/ethnic strata.

CONCLUSIONS

Our results demonstrated that a predictive model developed using information gleaned from the medical record and from public census tract data can be used to identify patients who may benefit from proactive social needs assessment. Depending on the prevalence of social needs in the target population, different risk output thresholds could be set to optimize positive predictive value for successful outreach. This predictive model-based strategy provides a pathway for prioritizing more intensive social risk outreach and screening efforts to the patients who may be in greatest need.

Pediatric ACEs Screening and Referral: Facilitators, Barriers, and Opportunities for Improvement

Despite well-documented associations between adverse childhood experiences (ACEs) and lifelong impairments in health and well-being, few studies have examined how to facilitate implementation of ACEs screening and referral programs in pediatric settings. We sought to identify facilitators and barriers related to screening for and addressing ACEs in a large integrated healthcare delivery system in Southern California. Using a developmental evaluation approach, we conducted twenty semi-structured interviews with pediatricians, nurses, social workers, and community referral organization staff. Interviews took place across six pediatric clinic pilot sites in Kaiser Permanente Southern California, where more than 7,000 pediatric patients were screened for ACEs between July 2018 and December 2019. Thematic analysis was conducted to identify themes. Key facilitators for screening and referrals for pediatric ACEs screening included providing clinician education to normalize conversations about ACEs, using screening data to provide more holistic and compassionate care, and collaborating across different types of clinicians. Key barriers included screening tool challenges related to patient confusion and cultural differences, capacity limitations, training issues, and care team silos. When used in the context of a trauma- and resilience-informed workforce, ACEs screening may be a powerful tool to support more collaborative and impactful care decisions that move away from symptom management to address root causes and promote prevention.

Addressing the Impacts of Racism on American Indian and Alaska Native Child Health

The legacy of racism toward Native Americans is far-reaching. We will review the topic using the conceptual model of racism as a form of violence as it is inherent in racism, as are prejudice and power. Using the basic frameworks of racism as internalized, interpersonal, institutional, and structural, we will discuss the many types of racism affecting Native Americans today. Racism is the bedrock of generations of trauma experienced in Native communities. The generational/historical trauma of racism has led to epigenetic-level changes affecting Native American people today. We will cover the health impacts of racism and the many institutions built in racist frameworks that continue to perpetuate racism, such as family separation and child removal by child protective services, adverse policing, and disparate incarceration. These allow reflection on policies and the intentionality of racist structures. We will conclude with what can and should be done, particularly as clinicians who work within and adjacent to existing systems of oppression.

State-Level Household Energy Insecurity and Diabetes Prevalence Among US Adults, 2020

The objective of this study was to examine the state-level association between household energy insecurity and diabetes prevalence in 2020. We obtained 1) state-level data on household energy characteristics from the 2020 Residential Energy Consumption Survey and 2) diagnosed diabetes prevalence from the US Diabetes Surveillance System. We found states with a higher percentage of household energy insecurity had greater diabetes prevalence compared with states with lower percentages of energy insecurity. Interventions related to energy assistance may help reduce household energy insecurity, mitigate the risk of diabetes-related complications, and alleviate some of the burden of diabetes management during extreme temperatures.

Building a Client Resource and Communication Platform for Community-Based Organizations to Address Health and Social Needs: Co-Design Study

Background

Connecting individuals to existing community resources is critical to addressing social needs and improving population health. While there is much ongoing informatics work embedding social needs screening and referrals into health care systems and their electronic health records, there has been less focus on the digital ecosystem and needs of community-based organizations (CBOs) providing or connecting individuals to these resources.

Objective

We used human-centered design to develop a digital platform for CBOs, focused on identification of health and social resources and communication with their clients.

Methods

Centered in the Develop phase of the design process, we conducted in-depth interviews in 2 phases with community-based organizational leadership and staff to create and iterate on the platform. We elicited and mapped participant feedback to theory-informed domains from the Technology Acceptance Model, such as Usefulness and Ease of Use, to build the final product and summarized all major design decisions as the platform development proceeded.

Results

Overall, we completed 22 interviews with 18 community-based organizational leadership and staff in 2 consecutive Develop phases. After coding of the interview transcripts, there were 4 major themes related to usability, relevance, and external factors impacting use. Specifically, CBOs expressed an interest in a customer relationship management software to manage their client interactions and communications, and they needed specific additional features to address the scope of their everyday work, namely (1) digital and SMS text messaging communication with clients and (2) easy ways to identify relevant community resources based on diverse client needs and various program eligibility criteria. Finally, clear implementation needs emerged, such as digital training and support for staff using new platforms. The final platform, titled "Mapping to Enhance the Vitality of Engaged Neighborhoods (MAVEN)," was completed in the Salesforce environment in 2022, and it included features and functions directly mapped to the design process.

Conclusions

Engaging community organizations in user-centered design of a health and social resource platform was essential to tapping into their deep expertise in serving local communities and neighborhoods. Design methods informed by behavioral theory can be similarly employed in other informatics research. Moving forward, much more work will be necessary to support the implementation of platforms specific to CBOs' needs, especially given the resources, training, and customization needed in these settings.

Social Risk and Clinical Outcomes Among Adults With Type 2 Diabetes

Importance

No clear process exists for categorizing social risks in a way that informs effective social risk screening and intervention development.

Objective

To investigate social risk profiles and associations of those profiles with clinical outcomes in adults with diabetes using latent profile analysis.

Design, Setting, and Participants

For this cross-sectional study, a latent profile analysis was conducted using data for adults with type 2 diabetes collected at 2 primary care clinics in the Southeastern US from 2013 to 2014. Data were analyzed from November to December 2023.

Main Outcomes and Measures

Participants completed validated questionnaires for 26 social risk factors within 5 domains of social determinants of health: socioeconomic, neighborhood, education, food, and social and community context. In addition, participants completed questions that assessed psychological risk and behavioral risk. A 3-step latent profile analysis was used to identify different subgroups within the sample. Profiles were then regressed on outcomes of hemoglobin A1c (HbA1c), blood pressure, and quality of life.

Results

A total of 615 participants (mean [SD] age, 61.3 [10.9] years; 379 men [61.6%]) were included. Five latent class profiles were identified. The lowest risk group had significantly higher mental health-related quality of life compared with a group with higher neighborhood risk (β, 1.11; 95% CI, 0.67 to 1.55). The second group had low economic risk but high neighborhood risk and served as the reference group. The third group had high economic and neighborhood risk and had significantly higher blood pressure (β, 8.08; 95% CI, 2.16 to 14.01) compared with the reference. The fourth group had high psychological and behavioral risks but low socioeconomic and neighborhood risks. This group had significantly higher HbA1c (β, 0.47; 95% CI, 0.01 to 0.92) and lower mental health-related quality of life (β, -1.83; 95% CI, -2.41 to -1.24) compared with the reference. The highest risk group indicated high risk in all domains, had significantly higher HbA1c (β, 1.07; 95% CI, 0.50 to 1.63), and had lower mental health-related quality of life (β, -2.15; 95% CI, -2.87 to -1.42) compared with the reference.

Conclusions and Relevance

These findings suggest that social risk profiles can be identified according to social, psychological, and behavioral risk domains and the health outcome of concern among adults with diabetes. Future work should consider the use of social risk profiles in intervention development and testing.

Precision Prevention: Using Data to Target the Right Intervention at the Right Intensity in the Right Community at the Right Time

OBJECTIVES

This survey paper summarizes the recent trend of "Precision Prevention" in public health, focusing on significant developments in informatics to enable targeted prevention and improved public health.

METHODS

Given relatively limited use of the term "Precision Prevention" in the literature to date, com-bined with significant developments in this space outside of peer reviewed literature, the topic was ill-suited for a systematic review approach. Instead, the co-authors used a narrative review approach, combining related search terms and complementary expertise to develop and refine sub-topics to be included. Each section was then written using a combination of prior knowledge and specific relevant search terms.

RESULTS

The paper opens with an explanation of the term "precision prevention", including its origins and relationship to other concepts such as precision medicine. It then provides an overview of types of data relevant to precision prevention, as well as how those data are collected in different contexts and through different modalities. The authors then describe the HL7 Gravity Project, a multi-stakeholder public collaborative project aimed at data standardization in the social determinants space. Finally, the authors present how those data types are used across the spectrum from clinical care to target outreach for human services, to data-driven health policy.

CONCLUSIONS

Precision prevention, targeting the right intervention to the right population at the right time, is now recognized as of vital importance, particularly in light of the COVID-19 pandemic's spotlight on health disparities and societal consequences. Optimizing interventions targeted at different communities and populations will require novel and innovative collection, use, and dissemination of data, information, and knowledge. The talent and skills of the international informatics community are critical for success in this work.

A Randomized Controlled Trial Testing the Effects of a Social Needs Navigation Intervention on Health Outcomes and Healthcare Utilization among Medicaid Members with Type 2 Diabetes

Health systems are increasingly assessing and addressing social needs with referrals to community resources. The objective of this randomized controlled trial was to randomize adult Medicaid members with type 2 diabetes to receive usual care (n = 239) or social needs navigation (n = 234) for 6 months and compare HbA1c (primary outcome), quality of life (secondary outcome), and other exploratory outcomes with t-tests and mixed-effects regression. Eligible participants had an HbA1c test in claims in the past 120 days and reported 1+ social needs. Data were collected from November 2019 to July 2023. Surveys were completed at baseline and at 3-, 6-, and 12-month follow-up. Health plan data included care management records and medical and pharmacy claims. The sample was from Louisiana, USA, M = 51.6 (SD = 9.5) years old, 76.1% female, 66.5% Black, 29.4% White, and 3.0% Hispanic. By design, more navigation (91.5%) vs. usual care (6.7%) participants had a care plan. Social needs persisted for both groups. No group differences in HbA1c tests and values were observed, though the large amount of missing HbA1c lab values reduced statistical power. No group differences were observed for other outcomes. Proactively eliciting and attempting to provide referrals and resources for social needs did not demonstrate significant health benefits or decrease healthcare utilization in this sample.

Separating the Effects of Transitions Into and Out of Social Isolation and Loneliness on Cognitive Function in Later Life

OBJECTIVES

This study investigates the effects of social isolation and loneliness on cognitive function, distinguishing between the effects of transitioning into and out of these states.

METHODS

This study analyzed data from 6,663 adults aged 65 or older collected over the course of 7 waves (12 years) of the Korean Longitudinal Study of Aging from 2006 to 2018. A novel asymmetric fixed effects model was utilized to separately estimate the effects of transitions into and out of social isolation or loneliness.

RESULTS

The association of transitions into social isolation due to a lack of informal social contact or loneliness with cognitive function (b = -1.387, p < .001 and b = -0.601, p < .001, respectively) was stronger than the association of transitions out of these states (b = 0.345, p < .05 and b = 0.353, p < .001, respectively). The magnitude of the negative and positive coefficients was statistically different (F-statistic = 45.29, p < .001 and F-statistic = 5.12, p < .05, respectively). In contrast, no such asymmetric effects were observed for social isolation due to a lack of formal activity (F-statistic = 0.06, p = .800).

DISCUSSION

The detrimental effects of transitioning into social isolation due to a lack of informal social contact (but not formal activity) or loneliness on cognitive function outweigh the beneficial effects of transitioning out of these states. Preventing the onset of social disconnection should be prioritized as an intervention to improve the cognitive function of older adults.

Screening tools for employment in clinical healthcare delivery systems: a content analysis

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.

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.

Social needs screening in primary care: A tool in the fight for health equity?

Progress on addressing health inequalities is slow and in many places around the world the gap between the privileged and the disadvantaged is widening. This is driven largely by an unfair and unequal distribution of the social determinants of health. While upstream policy and agenda commitment is needed to improve social determinants of health at a population level, healthcare also has a role. Currently social information is sporadically collected and used in healthcare. Improving our understanding of social problems is crucial in targeting services and to reduce the overreliance on area-level measures of deprivation. This has the potential to improve patient care as well as more accurately capture socio-economic disadvantage. Here we argue that there is a role for primary care in screening for social needs to help address inequalities. Social needs screening, more commonly used in North America than Europe, aims to systematically collect social information in health and care settings. Healthcare professionals ask patients about social issues including employment, finances, housing, education and social isolation and this information is used to prompt referral to community services to address any need identified. Social needs screening has potential to address negative impacts of social determinants of health at an individual and population level. Providing a reliable measure of social need, screening gives healthcare professionals an opportunity to tailor and improve quality of care for patients and offer individualised support. It has been shown to improve individual social and health outcomes and positively impact healthcare utilisation. At a population level, social needs screening can improve the data on social determinants of health and therefore support policy makers and service delivery leaders to target resources and services more effectively to the communities most in need. Implementing social needs screening must take account of local healthcare service capacity and available community resources but where sustainable, effective programmes can be introduced, the potential benefits are manifold. While primary care alone cannot solve the root causes of health inequalities, we argue it could be a powerful actor in the fight for health equity.

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.

Hypertension in Pregnancy: Current Challenges and Future Opportunities for Surveillance and Research

Hypertension in pregnancy (HP) includes eclampsia/preeclampsia, chronic hypertension, superimposed preeclampsia, and gestational hypertension. In the United States, HP prevalence doubled over the last three decades, based on birth certificate data. In 2019, the estimated percent of births with a history of HP varied from 10.1% to 15.9% for birth certificate data and hospital discharge records, respectively. The use of electronic medical records may result in identifying an additional third to half of undiagnosed cases of HP. Individuals with gestational hypertension or preeclampsia are at 3.5 times higher risk of progressing to chronic hypertension and from 1.7 to 2.8 times higher risk of developing cardiovascular disease (CVD) after childbirth compared with individuals without these conditions. Interventions to identify and address CVD risk factors among individuals with HP are most effective if started during the first 6 weeks postpartum and implemented during the first year after childbirth. Providing access to affordable health care during the first 12 months after delivery may ensure healthy longevity for individuals with HP. Average attendance rates for postpartum visits in the United States are 72.1%, but the rates vary significantly (from 24.9% to 96.5%). Moreover, even among individuals with CVD risk factors who attend postpartum visits, approximately 40% do not receive counseling on a healthy lifestyle. In the United States, as of the end of September 2023, 38 states and the District of Columbia have extended Medicaid coverage eligibility, eight states plan to implement it, and two states proposed a limited coverage extension from 2 to 12 months after childbirth. Currently, data gaps exist in national health surveillance and health systems to identify and monitor HP. Using multiple data sources, incorporating electronic medical record data algorithms, and standardizing data definitions can improve surveillance, provide opportunities to better track progress, and may help in developing targeted policy recommendations.

Social determinants of health correlations and resource usefulness at a Milwaukee free clinic for uninsured individuals: A cross-sectional study

Introduction

Addressing social determinants of health (SDOH) is fundamental to improving health outcomes. At a student-run free clinic, we developed a screening process to understand the SDOH needs and resource utilization of Milwaukee's uninsured population.

Methods

In this cross-sectional study, we screened adult patients without health insurance (N = 238) for nine traditional SDOH needs as well as their access to dental and mental health care between October 2021 and October 2022. Patients were surveyed at intervals greater than or equal to 30 days. We assessed correlations between SDOH needs and trends in patient-reported resource usefulness.

Results

Access to dental care (64.7%) and health insurance (51.3%) were the most frequently endorsed needs. We found significant correlations (P ≤ 0.05) between various SDOH needs. Notably, mental health access needs significantly correlated with dental (r = 0.41; 95% CI = 0.19, 0.63), medications (r = 0.51; 95% CI = 0.30, 0.72), utilities (r = 0.39; 95% CI = 0.17, 0.61), and food insecurity (r = 0.42; 95% CI = 0.19, 0.64). Food-housing (r = 0.55; 95% CI = 0.32, 0.78), housing-medications (r = 0.58; 95% CI = 0.35, 0.81), and medications-food (r = 0.53; 95% CI = 0.32, 0.74) were significantly correlated with each other. Longitudinal assessment of patient-reported usefulness informed changes in the resources offered.

Conclusions

Understanding prominent SDOH needs can inform resource offerings and interventions, addressing root causes that burden under-resourced patients. In this study, patient-reported data about resource usefulness prompted the curation of new resources and volunteer roles. This proof-of-concept study shows how longitudinally tracking SDOH needs at low-resource clinics can inform psychosocial resources.

Contextual Factors Relevant to Implementing Social Risk Factor Screening and Referrals in Cancer Survivorship: A Qualitative Study

Introduction

Social risk factors such as food insecurity and lack of transportation can negatively affect health outcomes, yet implementation of screening and referral for social risk factors is limited in medical settings, particularly in cancer survivorship.

Methods

We conducted 18 qualitative, semistructured interviews among oncology teams in 3 health systems in Washington, DC, during February and March 2022. We applied the Exploration, Preparation, Implementation, Sustainment Framework to develop a deductive codebook, performed thematic analysis on the interview transcripts, and summarized our results descriptively.

Results

Health systems varied in clinical and support staff roles and capacity. None of the participating clinics had an electronic health record (EHR)-based process for identifying patients who completed their cancer treatment ("survivors") or a standardized cancer survivorship program. Their capacities also differed for documenting social risk factors and referrals in the EHR. Interviewees expressed awareness of the prevalence and effect of social risk factors on cancer survivors, but none employed a systematic process for identifying and addressing social risk factors. Recommendations for increasing screening for social risk factors included designating a person to fulfill this role, improving data tracking tools in the EHR, and creating systems to maintain up-to-date information and contacts for community-based organizations.

Conclusion

The complexity of cancer care workflows and lack of reimbursement results in a limited ability for clinic staff members to screen and make referrals for social risk factors. Creating clinical workflows that are flexible and tailored to staffing realities may contribute to successful implementation of a screening and referral program. Improving ongoing communication with community-based organizations to address needs was deemed important by interviewees.

Reexamining Differences Between Black and White Veterans in Hospital Mortality and Other Outcomes in Veterans Affairs and Other Hospitals

OBJECTIVES

To examine Black-White patient differences in mortality and other hospital outcomes among Veterans treated in Veterans Affairs (VA) and non-VA hospitals.

BACKGROUND

Lower hospital mortality has been documented in older Black patients relative to White patients, yet the mechanisms have not been determined. Comparing other hospital outcomes and multiple hospital systems may help inform the reasons for these differences.

METHODS

Repeated cross-sectional analysis of hospitalization records was conducted for Veterans discharged in VA and non-VA hospitals from January 1, 2013 to December 31, 2017 in 11 states. Hospital outcomes included 30-day mortality, 30-day readmissions, inpatient costs, and length of stay. Hospitalizations were for acute myocardial infarction, coronary artery bypass graft surgery, gastrointestinal bleeding, heart failure, pneumonia, and stroke. Differences in outcomes were estimated between Black and White patients for VA and non-VA hospitals and age groups younger than 65 years or 65 years and older in regression models adjusting for patient and hospital factors.

RESULTS

There were a total of 459,574 study patients. Older Black patients had lower adjusted mortality for acute myocardial infarction, gastrointestinal bleeding, heart failure, and pneumonia. Adjusted probability of readmission was higher and adjusted mean length of stay and costs were greater for older Black patients relative to White patients in non-VA hospitals for several conditions. Fewer differences were observed in younger patients and in VA hospitals.

CONCLUSION

While older Black patients had lower mortality, other outcomes compared poorly with White patients. Differences were not fully explained by observable patient and hospital factors although social determinants may contribute to these differences.

Swimming Together Upstream: How to Align MLP Services with U.S. Healthcare Delivery

Medical-legal partnership (MLP) embeds attorneys and paralegals into care delivery to help clinicians address root causes of health inequities. Notwithstanding decades of favorable outcomes, MLP is not as well-known as might be expected. In this essay, the authors explore ways in which strategic alignment of legal services with healthcare services in terms of professionalism, information collection and sharing, and financing might help the MLP movement become a more widespread, sustainable model for holistic care delivery.

Referrals to Community and State Agencies to Address Social Determinants of Health for Improving Mental Health, Functioning, and Quality of Care Outcomes for Diverse Adults

Objectives. To examine whether referral for social determinants of health (SDH) needs decreases psychological distress and posttraumatic stress disorder (PTSD) symptoms and improves level of functioning and quality of care among diverse adults. Methods. Data are from control participants (n = 503 adults) in a randomized controlled trial testing a mental health intervention in North Carolina and Massachusetts. We fitted multilevel mixed-effects models to repeated assessments (baseline, 3, 6, and 12 months) collected between September 2019 and January 2023. Results. After referral to services for trouble paying utility bills, participants reported lower PTSD symptoms. Participants reported better quality of care when receiving referrals to mental health care. After adjusting for income and employment status, we found that participants who were referred more often also had lower PTSD symptoms and better levels of functioning. Conclusions. Referrals for certain SDH needs might decrease PTSD symptoms and improve self-reported quality of care and functioning. However, referrals alone, without ensuring receipt of services, might be insufficient to affect other mental health outcomes. Research is needed on training and providing care managers time for offering interpersonal support, securing services, and understanding agencies' contexts for addressing high SDH needs. (Am J Public Health. 2024;114(S3):S278-S288. https://doi.org/10.2105/AJPH.2023.307442).

Disparities in Patient Family Social Determinants of Health in a Large Urban Pediatric Health System

INTRODUCTION

This analysis sought to identify disparities in social determinants of health (SDOH) outcomes at a Texas pediatric hospital.

METHODS

This retrospective study used electronic health records of pediatric patients families surveyed August -December 2022. Outcomes for health literacy, social support, food, transportation, energy, digital, and housing insecurity, and tobacco exposure were analyzed across demographic categories.

RESULTS

Among 15,294 respondents to the survey (mean child age, 8.73 years; 43.68% Hispanic, 29.73% non-Hispanic White, 18.27% non-Hispanic Black, 6.79% other race/ethnicity; 53.95% male), 50.25% of respondents reported at least one SDOH, whereas 23.39% reported two or more SDOH. The most prevalent SDOH was lack of social support (3,456, 23.91%). Hispanic, non-Hispanic Black, and other race/ethnicity respondents, non-English speakers, and public insurance users had higher odds of reporting almost all SDOH in logistic regression models adjusted for age, race/ethnicity, language, gender, and insurance type.

DISCUSSION

Race/ethnicity, language, and insurance type disparities were identified for all SDOH.

Homelessness And Health: Factors, Evidence, Innovations That Work, And Policy Recommendations

On a single night in 2023, more than 653,000 people experienced homelessness in the United States. In this overview, we highlight structural and individual risk factors that can lead to homelessness, explore evidence on the relationship between homelessness and health, discuss programmatic and policy innovations, and provide policy recommendations. Health system efforts to address homelessness and improve the health of homeless populations have included interventions such as screening for social needs and medical respite programs. Initiatives using the Housing First approach to permanent supportive housing have a strong track record of success. Health care financing innovations using Medicaid Section 1115 waivers offer promising new approaches to improving health and housing for people experiencing homelessness. To substantially reduce homelessness and its many adverse health impacts, changes are needed to increase the supply of affordable housing for households with very low incomes. Health care providers and systems should leverage their political power to advocate for policies that scale durable, evidence-based solutions to reduce homelessness, including increased funding to expand housing choice vouchers and greater investment in the creation and preservation of affordable housing.

Social determinants of health and incident postoperative delirium: Exploring key relationships in the SAGES study

BACKGROUND

Examining the associations of social determinants of health (SDOH) with postoperative delirium in older adults will broaden our understanding of this potentially devastating condition. We explored the association between SDOH factors and incident postoperative delirium.

METHODS

A retrospective study of a prospective cohort of patients enrolled from June 18, 2010, to August 8, 2013, across two academic medical centers in Boston, Massachusetts. Overall, 560 older adults age ≥70 years undergoing major elective non-cardiac surgery were included in this analysis. Exposure variables included income, lack of private insurance, and neighborhood disadvantage. Our main outcome was incident postoperative delirium, measured using the Confusion Assessment Method long form.

RESULTS

Older age (odds ratio, OR: 1.01, 95% confidence interval, CI: 1.00, 1.02), income <20,000 a year (OR: 1.12, 95% CI: 1.00, 1.26), lack of private insurance (OR: 1.19, 95% CI: 1.04, 1.38), higher depressive symptomatology (OR: 1.02, 95% CI: 1.01, 1.04), and the Area Deprivation Index (OR: 1.02, 95% CI: 1.01, 1.04) were significantly associated with increased risk of postoperative delirium in bivariable analyses. In a multivariable model, explaining 27% of the variance in postoperative delirium, significant independent variables were older age (OR 1.01, 95% CI 1.00, 1.02), lack of private insurance (OR 1.18, 95% CI 1.02, 1.36), and depressive symptoms (OR 1.02, 95% CI 1.00, 1.03). Household income was no longer a significant independent predictor of delirium in the multivariable model (OR:1.02, 95% CI: 0.90, 1.15). The type of medical insurance significantly mediated the association between household income and incident delirium.

CONCLUSIONS

Lack of private insurance, a social determinant of health reflecting socioeconomic status, emerged as a novel and important independent risk factor for delirium. Future efforts should consider targeting SDOH factors to prevent postoperative delirium in older adults.

Improving food insecurity screening across a health system throughout the COVID-19 pandemic

BACKGROUND

Food insecurity has direct and indirect negative outcomes on the physical and mental health of children, with impacts throughout adult life. Rates of food insecurity have increased dramatically since the start of the COVID-19 pandemic. The American Academy of Pediatrics recommends paediatricians screen and intervene to address food insecurity. We aimed to increase the percentage of patient encounters with food insecurity screening completion at the paediatric medical home from 0% to 85% by July 2020 with extension to the paediatric emergency department (ED) and paediatric specialty clinic in the following year.

METHODS

This multicentre project occurred in three sites within our health system: a teaching safety-net, paediatric medical home; a paediatric ED; and five divisions within paediatric specialty medical clinics. A screening tool was created using the validated Hunger Vital Sign Questionnaire. A standard screening, documentation and referral process was developed. The Model for Improvement was used testing changes via Plan-Do-Study-Act cycles.

RESULTS

The percentage of households screened for food insecurity increased from a median of 0% to 30% for all sites combined. There was significant variability in screening with the ED screening a median of 24% and the medical home screening 80% by the end of the study period. A total of 9842 households (20.9%) screened were food insecure. During the study period, 895 families with 3925 household members received 69 791 pounds of food from our primary community resource using our clinic's food prescription. Of these families, 44% (398) also qualified for the US Department of Agriculture programme ensuring ongoing food distribution up to twice a month.

DISCUSSION

Using quality improvement methodology to address a critical community need, we implemented food insecurity screening across a hospital system including multiple sites and specialties and provided critical resources to households in need.