How Do Social Needs Cluster Among Low-Income Individuals?

Patterns of Social Needs Predict Quality-of-Life and Healthcare Utilization Outcomes in Patients from a Large Hospital System

BACKGROUND

Unmet social needs (SNs) often coexist in distinct patterns within specific population subgroups, yet these patterns are understudied.

OBJECTIVE

To identify patterns of social needs (PSNs) and characterize their associations with health-related quality-of-life (HRQoL) and healthcare utilization (HCU).

DESIGN

Observational study using data on SNs screening, HRQoL (i.e., low mental and physical health), and 90-day HCU (i.e., emergency visits and hospital admission). Among patients with any SNs, latent class analysis was conducted to identify unique PSNs. For all patients and by race and age subgroups, compared with no SNs, we calculated the risks of poor HRQoL and time to first HCU following SNs screening for each PSN.

PATIENTS

Adult patients undergoing SNs screening at the Mass General Brigham healthcare system in Massachusetts, United States, between March 2018 and January 2023.

MAIN MEASURES

SNs included: education, employment, family care, food, housing, medication, transportation, and ability to pay for household utilities. HRQoL was assessed using the Patient-Reported Outcomes Measurement Information System Global-10.

KEY RESULTS

Six unique PSNs were identified: "high number of social needs," "food and utility access," "employment needs," "interested in education," "housing instability," and "transportation barriers." In 14,230 patients with HRQoL data, PSNs increased the risks of poor mental health, with risk ratios ranging from 1.07(95%CI:1.01-1.13) to 1.80(95%CI:1.74-1.86). Analysis of poor physical health yielded similar findings, except that the "interested in education" showed a mild protective effect (0.97[95%CI:0.94-1.00]). In 105,110 patients, PSNs increased the risk of 90-day HCU, with hazard ratios ranging from 1.09(95%CI:0.99-1.21) to 1.70(95%CI:1.52-1.90). Findings were generally consistent in subgroup analyses by race and age.

CONCLUSIONS

Certain SNs coexist in distinct patterns and result in poorer HRQoL and more HCU. Understanding PSNs allows policymakers, public health practitioners, and social workers to identify at-risk patients and implement integrated, system-wide, and community-based interventions.

What Do Medicaid Members Want From Their Health Plan? Insights From a Qualitative Study to Improve Engagement in Case Management

PURPOSE OF STUDY

Managed care organizations (MCOs) provide case management services to address unmet health and social needs among their members. Few studies have examined factors influencing members' decision to participate in these programs. The purpose of the present study was to describe the life circumstances of Medicaid members offered case management, what they wanted from their MCO, and their perceptions of case management and barriers to participation. Results will inform practice to raise the awareness, engagement, and impact of case management programs.

PRIMARY PRACTICE SETTINGS

Case management offered through a Midwestern Medicaid MCO.

METHODOLOGY AND SAMPLE

Adult members who had been offered case management services in the 6 months preceding the study were eligible for the study. Fifteen people from each strata were recruited: members who engaged with case management, declined it, or declined it initially but later engaged (N = 45). Participants completed a qualitative interview by phone and a brief health survey online.

RESULTS

Across strata, only 22 participants recalled engagement with case management. Members described a variety of life challenges (e.g., chronic health conditions, caregiver responsibilities, and limited finances) and services they desired from their MCO (e.g., stipends for over-the-counter health expenses, improved transportation services, and caregiver assistance). Participants identified direct communication, emotional support, and referrals for resources as benefits of case management.

Sleep, Stress, and Cardiometabolic Health in Women of Childbearing Age with Overweight and Obesity

Background

Sleep is important for health, but its relationship to cardiometabolic health in women of childbearing age remains unclear. Furthermore, stress, unmet basic needs, and lack of physical activity may be related to disrupted sleep and poor cardiometabolic health in women of childbearing age and these relationships may differ by ethnicity. The purposes of this study were to investigate the relationship between sleep, markers of cardiometabolic health, stress, unmet basic needs, and physical activity in women of childbearing age with overweight or obesity and identify if these relationships differed between women that identified as Latino/Hispanic and non-Latino/Hispanic ethnicity.

Methods

A secondary cross-sectional analysis was conducted using baseline data from a trial that embeds healthy eating and activity into a national home visiting program, Parents as Teachers. The sample was stratified based on self-reported ethnicity (Hispanic/Latino or non-Hispanic/Latino). Pearson's and Spearman's correlations were used to determine bivariate relationships among sleep, cardiometabolic variables, stress, unmet basic needs, and physical activity.

Results

Two hundred seventy-six women, 46% of whom identified as Hispanic/Latino, were included in the analysis. Body mass index (BMI) was significantly correlated with sleep disturbance (ρ = 0.23, p = 0.01) in women who identify as Hispanic/Latino. Stress was positively related to sleep disturbance, sleep duration, and unmet needs for both groups of women. BMI was correlated with unmet basic needs in women who identified as non-Hispanic/Latino (ρ = 0.25, p = 0.01).

Conclusions

Our results suggest that sleep, stress, and basic needs are important in understanding cardiometabolic health in women of childbearing age and these relationships differ depending on ethnicity. Clinical Trial Registration Number: NCT03758638.

Cardiovascular Health of Middle-Aged U.S. Adults by Income Level, 1999 to March 2020 : A Serial Cross-Sectional Study

BACKGROUND

Although cardiovascular mortality has increased among middle-aged U.S. adults since 2011, how the burden of cardiovascular risk factors has changed for this population by income level over the past 2 decades is unknown.

OBJECTIVE

To evaluate trends in the prevalence, treatment, and control of cardiovascular risk factors among low-income and higher-income middle-aged adults and how social determinants contribute to recent associations between income and cardiovascular health.

DESIGN

Serial cross-sectional study.

SETTING

NHANES (National Health and Nutrition Examination Survey), 1999 to March 2020.

PARTICIPANTS

Middle-aged adults (aged 40 to 64 years).

MEASUREMENTS

Age-standardized prevalence of hypertension, diabetes, hyperlipidemia, obesity, and cigarette use; treatment rates for hypertension, diabetes, and hyperlipidemia; and rates of blood pressure, glycemic, and cholesterol control.

RESULTS

The study population included 20 761 middle-aged adults. The prevalence of hypertension, diabetes, and cigarette use was consistently higher among low-income adults between 1999 and March 2020. Low-income adults had an increase in hypertension over the study period (37.2% [95% CI, 33.5% to 40.9%] to 44.7% [CI, 39.8% to 49.5%]) but no changes in diabetes or obesity. In contrast, higher-income adults did not have a change in hypertension but had increases in diabetes (7.8% [CI, 5.0% to 10.6%] to 14.9% [CI, 12.4% to 17.3%]) and obesity (33.0% [CI, 26.7% to 39.4%] to 44.0% [CI, 40.2% to 47.7%]). Cigarette use was high and stagnant among low-income adults (33.2% [CI, 28.4% to 38.0%] to 33.9% [CI, 29.6% to 38.3%]) but decreased among their higher-income counterparts (18.6% [CI, 13.5% to 23.7%] to 11.5% [CI, 8.7% to 14.3%]). Treatment and control rates for hypertension were unchanged in both groups (>80%), whereas diabetes treatment rates improved only among the higher-income group (58.4% [CI, 44.4% to 72.5%] to 77.4% [CI, 67.6% to 87.1%]). Income-based disparities in hypertension, diabetes, and cigarette use persisted in more recent years even after adjustment for insurance coverage, health care access, and food insecurity.

LIMITATION

Sample size limitations could preclude detection of small changes in treatment and control rates.

CONCLUSION

Over 2 decades in the United States, hypertension increased in low-income middle-aged adults, whereas diabetes and obesity increased in their higher-income counterparts. Income-based disparities in hypertension, diabetes, and smoking persisted even after adjustment for other social determinants of health.

PRIMARY FUNDING SOURCE

National Institutes of Health.

Helping low-income smokers quit: findings from a randomized controlled trial comparing specialized quitline services with and without social needs navigation

Background

Quitting smoking is especially challenging for low-income smokers due to high stress, high smoking prevalence around them, and limited support for quitting. This study aimed to determine whether any of three interventions designed specifically for low-income smokers would be more effective than standard tobacco quitline services: a specialized quitline, the specialized quitline with social needs navigation, or the standard quitline with social needs navigation.

Methods

Using a randomized 2 × 2 factorial design, low-income daily cigarette smokers (n = 1944) in Missouri, USA who called a helpline seeking assistance with food, rent or other social needs were assigned to receive Standard Quitline alone (n = 485), Standard Quitline + Social Needs Navigation (n = 484), Specialized Quitline alone (n = 485), or Specialized Quitline + Social Needs Navigation (n = 490). The target sample size was 2000, 500 per group. The main outcome was 7-day self-reported point prevalence abstinence at 6-month follow-up. Multiple imputation was used to impute outcomes for those missing data at 6-month follow-up. Binary logistic regression analyses were used to assess differences between study groups.

Findings

Participants were recruited from June 2017 to November 2020; most were African American (1111 [58%]) or White (666 [35%]), female (1396 [72%]), and reported <$10,000 (957 [51%]) or <$20,000 (1529 [82%]) annual pre-tax household income. At 6-month follow-up (58% retention), 101 participants in the Standard Quitline group reported 7-day point prevalence abstinence (20.8% of those assigned at baseline, 38.1% after imputation). Quit rates in the Specialized Quitline (90 quitters, 18.6%, 38.1%) and Specialized Quitline + Social Needs Navigation (103 quitters, 21.0%, 39.8%) were not different from the Standard Quitline. Quit rates for Standard Quitline + Social Needs Navigation (74 quitters, 15.3%, 30.1%) were significantly lower than Standard Quitline (OR = 0.70, 95% CI = 0.50-0.98).

Interpretation

A specialized version of a state tobacco quitline was no more effective than standard quitline services in helping low-income smokers quit. Adding social needs navigation to a standard quitline decreased its effectiveness.

Trial registration

ClinicalTrials.gov Identifier: NCT03194958.

Funding

National Cancer Institute: R01CA201429.

Appeal of Tobacco Quitline Services Among Low-Income Smokers

INTRODUCTION

State tobacco quitlines are delivering cessation assistance through an increasingly diverse range of channels. However, offerings vary from state to state, many smokers are unaware of what is available, and it is not yet clear how much demand exists for different types of assistance. In particular, the demand for online and digital cessation interventions among low-income smokers, who bear a disproportionate burden of tobacco-related disease, is not well understood.

METHODS

We examined interest in using 13 tobacco quitline services in a racially diverse sample of 1,605 low-income smokers in 9 states who had called a 2-1-1 helpline and participated in an ongoing intervention trial from June 2020 through September 2022. We classified services as standard (used by ≥90% of state quitlines [eg, calls from a quit coach, nicotine replacement therapy, printed cessation booklets]) or nonstandard (mobile app, personalized web, personalized text, online chat with quit coach).

RESULTS

Interest in nonstandard services was high. Half or more of the sample reported being very or somewhat interested in a mobile app (65%), a personalized web program (59%), or chatting online with quit coaches (49%) to help them quit. In multivariable regression analyses, younger smokers were more interested than older smokers in digital and online cessation services, as were women and smokers with greater nicotine dependence.

CONCLUSION

On average, participants were very interested in at least 3 different cessation services, suggesting that bundled or combination interventions might be designed to appeal to different groups of low-income smokers. Findings provide some initial hints about potential subgroups and the services they might use in a rapidly changing landscape of behavioral interventions for smoking cessation.

Factors associated with meeting physical activity guidelines during the COVID-19 pandemic

INTRODUCTION

The COVID-19 pandemic impacted individual physical activity levels. Less is known regarding how factors such as sociodemographic and built environment were associated with physical activity engagement during the pandemic. Understanding these factors is critical to informing future infectious disease mitigation policies that promote, rather than hinder physical activity. The purpose of this study was to assess predictors of physical activity levels during the beginning of the pandemic (April-June 2020), including Stay-at-Home length and orders, neighborhood safety, and sociodemographic characteristics.

METHODS

Data included 517 participants who responded to an anonymous online survey. Physical activity was assessed with a modified Godin Leisure-time exercise questionnaire. We used logistic regression models to estimate unadjusted and adjusted odds ratios (aOR) and their 95% confidence intervals (CI) for the associations between independent variables (e.g., demographic variables, neighborhood safety, COVID Stay-at-Home order and length of time) and physical activity levels that did not meet (i.e., < 600 metabolic equivalents of task [MET]-minutes/week) or met guidelines (i.e., ≥ 600 MET-minutes/week). We used R-Studio open-source edition to clean and code data and SAS V9.4 for analyses.

RESULTS

Most participants were 18-45 years old (58%), female (79%), Hispanic (58%), and college/post-graduates (76%). Most (70%) reported meeting physical activity guidelines. In multivariate-adjusted analyses stratified by income, in the highest income bracket (≥ $70,000) pet ownership was associated with higher odds of meeting physical activity guidelines (aOR = 2.37, 95% CI: 1.23, 4.55), but this association did not persist for other income groups. We also found lower  perceived neighborhood safety was associated with significantly lower odds of meeting physical activity guidelines (aOR = 0.15, 95% CI:0.04-0.61), but only among individuals in the lowest income bracket (< $40,000). Within this lowest income bracket, we also found that a lower level of education was associated with reduced odds of meeting physical activity guidelines.

DISCUSSION

We found that perceived neighborhood safety, education and pet ownership were associated with meeting physical activity guidelines during the early months of the COVID-19 pandemic, but associations differed by income. These findings can inform targeted approaches to promoting physical activity during subsequent waves of COVID-19 or future pandemics.

Association of Social Needs and Healthcare Utilization Among Medicare and Medicaid Beneficiaries in the Accountable Health Communities Model

BACKGROUND

Integration of health-related social needs (HRSNs) data into clinical care is recognized as a driver for improving healthcare. However, few published studies on HRSNs and their impact are available. CMS sought to fill this gap through the Accountable Health Communities (AHC) Model, a national RCT of HRSN screening, referral, and navigation. Data from the AHC Model could significantly advance the field of HRSN screening and intervention in the USA.

OBJECTIVE

To present data from the Greater Houston AHC (GH-AHC) Model site on HRSN frequency and the association between HRSNs, sociodemographic factors, and self-reported ED utilization using a cross-sectional design. Analyses included descriptive statistics and multinomial logistic regression.

PARTICIPANTS (OR PATIENTS OR SUBJECTS)

All community-dwelling Medicare, Medicaid, or dually covered beneficiaries at participating GH-AHC clinical delivery sites were eligible.

MAIN MEASURES

Self-reported ED utilization in the previous 12 months served as the outcome; demographic characteristics including race, ethnicity, age, sex, income, education level, number of people living in the household, and insurance type were treated as covariates. HRSNs included food insecurity, housing instability, transportation, difficulty paying utility bills, and interpersonal safety. Clinical delivery site type was used as the clustering variable.

KEY RESULTS

Food insecurity was the most common HRSN identified (38.7%) followed by housing instability (29.0%), transportation (28.0%), and difficulty paying utility bills (26.7%). Interpersonal safety was excluded due to low prevalence. More than half of the beneficiaries (56.9%) reported at least one of the four HRSNs. After controlling for covariates, having multiple co-occurring HRSNs was strongly associated with increased risk of two or more ED visits (OR 1.8-9.47 for two to four needs, respectively; p < 0.001). Beneficiaries with four needs were at almost 10 times higher risk of frequent ED utilization (p < 0.001).

CONCLUSIONS

To our knowledge, this is only the second published study to report screening data from the AHC Model. Future research focused on the impact of multiple co-occurring needs on health outcomes is warranted.

Screening Families in Primary Care for Social and Economic Needs: Patients' Urgency and Activation for Social Care Navigation

INTRODUCTION

Social determinants of health (SDoH) screening and intervention in primary care aim to alleviate adverse influences on health, but its efficacy may be diluted when offered supports are not well matched to families' desire for such services. The purpose of this prospective cohort study was to provide guidance to social care navigation teams regarding which families would be most likely to make use of services.

METHODS

Analysis of registry data collected in April 1-September 30, 2021 from a social care navigation program embedded in a medical home was conducted. Multivariable regression models explored (1) whether family-reported urgency of needs, number of needs, and/or specific types of needs predicted completing program intake and (2) whether the degree of family activation regarding social needs predicted subsequent interactions with the navigation team.

RESULTS

Of the 1,483 families reporting any social care needs (38% of all screens completed, mean of 2.5 needs per screen), 31% indicated that their needs were urgent. Accounting for program factors and the number and type of needs reported, families whose needs were urgent were more likely to complete intake (OR=1.34; 95% CI=1.01, 1.82; p=0.04) and remain engaged with the program over time (OR=2.25; 95% CI=1.62, 3.12; p<0.01). Those who were self-advocates were substantially less likely to desire follow-up or stay engaged (OR=0.40; 95% CI=0.17, 0.93; p<0.01).

CONCLUSIONS

Family-reported urgency of needs and activation for social care assistance predicted engagement with the navigation team. SDoH interventions should prioritize outreach to those families expressing an interest in help with any of their identified needs.

Associations Between Different Self-reported Social Risks and Neighborhood-level Resources in Medicaid Patients

BACKGROUND

Adverse social conditions are a key contributor to health disparities. Improved understanding of how social risk factors interact with each other and with neighborhood characteristics may inform efforts to reduce health disparities.

DATA

A questionnaire of 29,281 patients was collected through the enrollment of Medicaid beneficiaries in a large Northern California integrated health care delivery system between May 2016 and February 2020.

EXPOSURES

Living in the least resourced quartile of neighborhoods as measured by a census-tract level Neighborhood Deprivation Index score.

MAIN OUTCOMES

Five self-reported social risk factors: financial need, food insecurity, housing barriers, transportation barriers, and functional limitations.

RESULTS

Nearly half (42.0%) of patients reported at least 1 social risk factor; 22.4% reported 2 or more. Mean correlation coefficient between social risk factors was ρ=0.30. Multivariable logistic models controlling for age, race/ethnicity, sex, count of chronic conditions, and insurance source estimated that living in the least resourced neighborhoods was associated with greater odds of food insecurity (adjusted odds ratio=1.07, 95% confidence interval: 1.00-1.13) and transportation barriers (adjusted odds ratio=1.20, 95% confidence interval: 1.11-1.30), but not financial stress, housing barriers, or functional limitations.

CONCLUSIONS AND RELEVANCE

We found that among 5 commonly associated social risk factors, Medicaid patients in a large Northern California health system typically reported only a single factor and that these factors did not correlate strongly with each other. We found only modestly greater social risk reported by patients in the least resourced neighborhoods. These results suggest that individual-level interventions should be targeted to specific needs whereas community-level interventions may be similarly important across diverse neighborhoods.

Low housing quality, unmet social needs, stress and depression among low-income smokers

•

Over 60% of low-income smokers reported housing quality problems.

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Problems with housing quality were among the most common social needs.

•

Housing quality problems were associated with worse measures of health.

•

Poor housing quality may exacerbate health disparities for low-income smokers.

Smokers are at greater risk of multiple health conditions that are exacerbated by environmental hazards associated with low housing quality. However, little is known about the prevalence of low housing quality among low-income smokers. Using correlations and logistic regression, we examined associations among eight housing quality indicators – pests, water leaks, mold, lead paint, and working smoke detectors, appliances, heating, and air conditioning – and between housing quality and social needs, depressive symptoms, perceived stress, sleep problems, and self-rated health in a community-based sample of 786 low-income smokers from 6 states. Most participants were female (68%), and White (45%) or African-American (43%). One in four (27%) completed less than high school education, and 41% reported annual pre-tax household income of less than $10,000. Housing quality problems were common. Most participants (64%) reported at least one problem in their home, and 41% reported two or more problems, most commonly pest infestations (40%), water leaks (22%), lack of air conditioning (22%) and mold (18%). Lack of heat and air conditioning were correlated, as were water leaks and mold. Using logistic regression analyses controlling for participant demographic characteristics, we found that reporting more housing quality problems was associated with greater odds of worse mental and physical health outcomes. Multiple health threats, including housing quality, depressive symptoms, stress, poor sleep, and financial strain may be mutually reinforcing and compound the health consequence of smoking. Future research should seek to replicate these findings in other samples, and examine associations longitudinally to better understand causality.

Transportation and other social needs as markers of mental health conditions

Objective

The study sought to determine whether reporting a history of depression, anxiety, PTSD, bipolar disorder, drug or alcohol use disorder, ADHD, schizophrenia, or current depressive symptoms was associated with requesting help for any of 12 social needs.

Methods

A community-based sample of 1,944 low-income adult smokers in Missouri who had called a telephone helpline for social needs were recruited between June 1, 2017 and November 15, 2020. Helpline data on callers' requests for assistance with utilities, housing, food, household goods, healthcare, transportation, adult care, financial assistance, employment, legal assistance, personal safety and childcare were merged with self-reported mental health data collected in a subsequent phone survey with the same callers. Using binary logistic regression, we examined which mental health conditions were associated with each social need.

Results

Reporting mental health conditions were associated with greater odds of requests for assistance with transportation, food, healthcare and personal safety. Of these, the strongest and most consistent associations were with transportation needs. In post-hoc analyses, most associations between transportation needs and mental health remained significant after adjusting for possible confounders.

Conclusions

Compared to participants who did not report histories of mental health conditions, those who reported mental health conditions were more likely to call 2-1-1 seeking transportation assistance. Community-based agencies providing transportation or mental health services could partner to provide linkages between services and increase capacity to address transportation and mental health needs.

Associations among social needs, health and healthcare utilization, and desire for navigation services among US Medicaid beneficiaries with type 2 diabetes

The purpose of this study was to better understand the number and types of social needs experienced by Medicaid beneficiaries with type 2 diabetes, and how their social needs are associated with key health indicators. Also examined were factors that influence patients' interest in navigation services for health and social needs to inform future interventions and service delivery. The study expands upon prior research, much of which has focused on only one social need (e.g., food insecurity) or one health outcome. The hypothesis was that among individuals with type 2 diabetes, those with a greater number of social needs would report more health-related problems and be more interested in receiving social needs navigation services. Participants completed a cross-sectional survey by phone (n = 95) or online (n = 14). Most (85%) reported having at least one social need (M = 2.5, SD = 2.2), most commonly not having enough money for unexpected expenses (68%) or necessities like food, shelter and clothing (31%), medical costs (24%), and utilities (23%). Results supported our comprehensive conceptual model. Having more social needs was associated with greater perceived stress, diabetes distress, problems with sleep and executive and cognitive functioning, less frequent diabetes self-care activities, more days of poor mental health and activity limitations, worse self-reported health and more hospitalisations. Number of social needs also was positively associated with interest in having a social needs navigator. Social needs were not associated with days of poor physical health, BMI, self-reported A1C or smoking status. Social needs were associated with a wide range of indicators of poor health and well-being. Participants with the greatest social need burden were most open to intervention.

Correlates of smoking discarded cigarettes in a sample of low-income adults

INTRODUCTION

Unconventional smoking behaviors such as smoking used or discarded cigarettes may increase the risk of nicotine dependence and exposure to toxins. To better understand low-income smokers who smoke discarded cigarettes and to inform effective tobacco cessation strategies, the current study examined potential correlates not considered in prior studies.

METHODS

This secondary analysis examined baseline data from 1936 low-income smokers participating in a randomized cessation trial. To assess smoking discarded cigarettes, participants were asked: "In the past 30 days, have you smoked what's left of a cigarette that someone else left behind?" Unadjusted and adjusted logistic regression were used to explore associations between smoking discarded cigarettes and social needs, social environment, mental and physical health, other smoking-related behaviors, and demographic characteristics.

RESULTS

One in six participants reported smoking discarded cigarettes. Younger smokers, men, smokers with lower incomes and those who were not employed were more likely to smoke discarded cigarettes. Other correlates included having unmet social needs (transportation, food, housing, physical safety, and neighborhood safety), living with other smokers, worse mental health, greater perceived stress, heavier smoking, using other tobacco products, and bumming cigarettes from others. In a multivariable model, income, social environment, and other smoking behaviors emerged as significant correlates.

CONCLUSIONS

In addition to financial hardship, mental health, and nicotine dependence, the social needs, social environment, and other smoking behaviors of low-income smokers are important correlates of smoking discarded cigarettes. Future research to understand and address tobacco health disparities should examine these relationships longitudinally.

Association of Unmet Social Needs with Chronic Illness: A Cross-Sectional Study

Screening for social needs during routine medical visits is increasingly common. To date, there are limited data on which social needs are most predictive of health outcomes. The aim of this study is to build a predictive model from integrated social needs screening and health data to identify individual or clusters of social needs that are predictive of chronic illnesses. Using the electronic medical record data from a Federally Qualified Health Center collected from January 2016 to December 2020, demographic, diagnosis, and social needs screening data were used to look at adjusted and unadjusted associations of individual unmet social needs with chronic illnesses (n = 2497). The least absolute shrinkage and selection operator (LASSO) model was used to identify which social need(s) were associated with overall burden of chronic illness, and individual diagnoses of hypertension, obesity, diabetes, and psychiatric illness. The LASSO model identified age, race, language, gender, insurance, transportation, and food insecurity as significant predictors of any chronic illness. Using these variables in a multivariable model, transportation (adjusted odds ratio [aOR] 1.66) was the only social need that remained significantly associated with chronic illness diagnosis. Transportation need was also significantly associated with diabetes (aOR 1.44) and psychiatric illness (aOR 1.98). Food insecurity was associated with obesity (aOR 10.21). Using LASSO models to identify significant social needs, transportation was identified as a predictor in 3 of the 5 models. Further research is warranted to evaluate if addressing patients' transportation needs has the potential to mitigate chronic disease sequelae for vulnerable adults to advance health equity.

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

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

Implementing Health Related Social Needs Screening in an Outpatient Clinic

INTRODUCTION/OBJECTIVES

Health-related social needs (HRSN) screening efforts have reported high rates of identified social needs. Little is known if efforts to conduct HRSN screening in resource-constrained federally-qualified health centers (FQHC) successfully captures a representative patient population.

METHODS

This cross-sectional study extracted EMR data from 2016 to 2020 for 4731 screened patients from 7 affiliated clinics of a FQHC. Unscreened patients were pulled as a random sample from the study period. A multivariable logistic regression was used to identify sociodemographic traits, chronic disease diagnoses and burden, and clinic visit type and frequency associated with being screened for HRSN.

RESULTS

BHC screened 4731 unique patients or <1% of the total clinic population. Screened patients had a median of 3.3 (±2.5) unmet HRSN. Medicaid patients had higher odds of being screened (aOR = 1.38, CI 1.19-1.61) relative to Medicare patients. The odds of being screened for social needs increased with more provider visits per year: compared to fewer than 1 visit per year, patients with 1 to 3 provider visits (aOR = 2.06, CI 1.73-2.32), 4 to 6 provider visits (aOR = 3.34, CI 2.89-3.87), and more than 6 provider visits (aOR = 5.16, CI 4.35-6.12) all had higher odds of social needs screening. Patients with a higher comorbid disease burden (>2 conditions, aOR = 2.80, CI 2.07-3.79) had higher odds of screening.

CONCLUSIONS

Our findings demonstrate an increased likelihood to screen patients who visit outpatient services more often and have a higher comorbid disease burden. To meet state-level Medicaid requirements, resource-constrained FQHCs that implement clinic wide HRSN screening may be well served to identify a priori strategies to ensure representative and equitable screening across the patient population.

Stress, depression, sleep problems and unmet social needs: Baseline characteristics of low-income smokers in a randomized cessation trial

BACKGROUND

Low-income Americans smoke cigarettes at higher rates and quit less than other groups.

METHODS

To increase their engagement in and success using evidence-based cessation methods, we tested two interventions using a 2x2 randomized factorial design: (1) telephone navigation to reduce financial strain and address social needs such as food, rent and utility payment; and (2) a specialized tobacco quitline designed for low-income smokers. From June 2017 to November 2020, we enrolled 1,944 low-income smokers in Missouri, USA, recruited through the Missouri 2-1-1 helpline, into the trial. This paper describes recruitment, key characteristics and life circumstances of this high-risk population.

RESULTS

After eligibility screening, 1,944 participants completed baseline and were randomized. Participants were racially diverse (58% African American), poor (51% < $10,000 annual pre-tax household income) and many reported less than high school education (30%). They reported a mean of 2.5 unmet social needs, especially childcare and paying bills, had high rates of stress, depressive symptoms and sleep problems, and most were in fair or poor health. There were few differences between these variables, and no differences between tobacco use and cessation variables, across the four study groups and between participants recruited pre and during the COVID-19 pandemic.

CONCLUSIONS

Trial recruitment through the 2-1-1 helpline is feasible for reaching a population of low-income smokers. Low-income smokers face myriad daily challenges beyond quitting smoking. Cessation interventions need to account for and address these life circumstances.

TRIAL REGISTRATION

Clinicaltrials.gov NCT03194958.

Social Needs, Chronic Conditions, and Health Care Utilization among Medicaid Beneficiaries

Health care organizations are increasingly assessing patients' social needs (eg, food, utilities, transportation) using various measures and methods. Prior studies have assessed social needs at the point of care and many studies have focused on correlates of 1 specific need (eg, food). This comprehensive study examined multiple social needs and medical and pharmacy claims data. Medicaid beneficiaries in Louisiana (n = 10,275) completed a self-report assessment of 10 social needs during July 2018 to June 2019. Chronic health conditions, unique medications, and health care utilization were coded from claims data. The sample was predominantly female (72%), Black (45%) or White (32%), had a mean age of 42 years, and at least 1 social need (55%). In bivariate analyses, having greater social needs was associated with greater comorbidity across conditions, and each social need was consistently associated with mental health and substance use disorders. In multivariable logistic analyses, having ≥2 social needs was positively associated with emergency department (ED) visits (OR = 1.39, CI = 1.23 - 1.57) and negatively associated with wellness visits (OR = 0.87, CI = 0.77 - 0.98), inpatient visits (OR = 0.87, CI = 0.76 - 0.99), and 30-day rehospitalization (OR = 0.66, CI = 0.50 - 0.87). Findings highlight the greater concomitant risk of social needs, mental health, and substance use. Admission policies may reduce the impact of social needs on hospitalization. Chronic disease management programs offered by health plans may benefit from systematically assessing and addressing social needs outside point-of-care interactions to impact health outcomes and ED utilization. Behavioral health care management programs would benefit from integrating interventions for multiple social needs.

Addressing Social Needs in Health Care Settings: Evidence, Challenges, and Opportunities for Public Health

There has been an explosion of interest in addressing social needs in health care settings. Some efforts, such as screening patients for social needs and connecting them to needed social services, are already in widespread practice. These and other major investments from the health care sector hint at the potential for new multisector collaborations to address social determinants of health and individual social needs. This article discusses the rapidly growing body of research describing the links between social needs and health and the impact of social needs interventions on health improvement, utilization, and costs. We also identify gaps in the knowledge base and implementation challenges to be overcome. We conclude that complementary partnerships among the health care, public health, and social services sectors can build on current momentum to strengthen social safety net policies, modernize social services, and reshape resource allocation to address social determinants of health.