A Qualitative Study of A Health Center-Based Mobile Produce Market.

Healthcare-based food assistance programs have the potential to improve patients' food security, but are underutilized. We conducted a qualitative study of user and staff perceptions of an on-site mobile market at a federally-qualified health center (FQHC). Five themes were identified: 1) financial need drives the decision to use the market, 2) people attend specifically to receive healthy food, 3) users feel a connection to the FQHC, which increases participation, 4) social networks increase usage of the program, and 5) long lines, inclement weather, inaccessibility, and inconsistent marketing and communication are attendance barriers. Findings should inform implementation of future healthcare-based food assistance programs.

Factors Associated With Uptake of an Open Access Health Center-Based Mobile Produce Market: A Case for Expanded Eligibility.

BACKGROUND: Health care-based food assistance programs show promise but are underutilized. Strict eligibility requirements and program scheduling may dampen reach and outcomes. OBJECTIVE: To explore factors associated with uptake of a health center-based mobile produce market with no eligibility requirements and few barriers to entry. DESIGN: A cross-sectional analysis of medical record, sociodemographic, environmental, and market attendance data was used. PARTICIPANTS/SETTING: The study sample consisted of 3071 adults (18+ years) who were patients of an urban health center in eastern Massachusetts and registered for the mobile market during the study period of August 2016 to February 2020. MAIN OUTCOME MEASURES: The main outcome measure was monthly market attendance over the study period. STATISTICAL ANALYSES: T-tests and χ2 tests were used to compare market users and never-users. Multiple logistic regression was used to analyze variables associated with market attendance each month. RESULTS: In multiple variable analyses, Supplemental Nutrition Assistance Program enrollment was associated with slightly less frequent monthly market use (odds ratio [OR], 0.989; 95% CI, 0.984-0.994). Day-of, on-site market registration was associated with more frequent monthly use than self-registration on nonmarket days (OR, 1.08; 95% CI, 1.07-1.08). Having a psychiatric or substance use disorder diagnosis was associated with slightly less frequent market attendance (OR, 0.99; 95% CI, 0.98-0.99; and OR, 0.96; 95% CI, 0.95-0.97, respectively) compared with registrants without these diagnoses. CONCLUSIONS: Individual, community-level, and organizational factors are associated with uptake of a free mobile produce market and should be considered when designing programs.

Food Insecurity and Social Policy: A Comparative Analysis of Welfare State Regimes in 19 Countries.

We sought to determine whether a country's social policy configuration-its welfare state regime-is associated with food insecurity risk. We conducted a cross-sectional study of 2017 U.N. Food and Agriculture Organization individual-level food insecurity survey data from 19 countries (the most recent data available prior to COVID-19). Countries were categorized into three welfare state regimes: liberal (e.g., the United States), corporatist (e.g., Germany), or social democratic (e.g., Norway). Food insecurity probability, calibrated to an international reference standard, was calculated using a Rasch model. We used linear regression to compare food insecurity probability across regime types, adjusting for per-capita gross domestic product, age, gender, education, and household composition. There were 19,008 participants. The mean food insecurity probability was 0.067 (SD: 0.217). In adjusted analyses and compared with liberal regimes, food insecurity probability was lower in corporatist (risk difference: -0.039, 95% CI -0.066 to -0.011, p = .006) and social democratic regimes (risk difference: -0.037, 95% CI -0.062 to -0.012, p = .004). Social policy configuration is strongly associated with food insecurity risk. Social policy changes may help lower food insecurity risk in countries with high risk.

Mental Health Care Use by Ethnicity and Preferred Language in a National Cohort of Community Health Center Patients.

OBJECTIVE: Disparities in U.S. mental health care by race and ethnicity have long been documented. The authors sought to compare specialty mental health service use among non-Hispanic White, English-preferring Hispanic, and Spanish-preferring Hispanic patients who accessed care in community health centers (CHCs). METHODS: Retrospective electronic medical records data were extracted for patients ages ≥18 years who received care in 2012-2020 at a national CHC network. Zero-inflated Poisson regression models were used to estimate the likelihood of receiving mental health services, which was compared with expected annual rates of mental health service use. RESULTS: Of the 1,498,655 patients who received care at a CHC during the study, 14.4% (N=215,098) received any specialty mental health services. English- and Spanish-preferring Hispanic patients were less likely to have had a mental health visit (OR=0.69, 95% CI=0.61-0.77, and OR=0.65, 95% CI=0.54-0.78, respectively). Compared with non-Hispanic White patients, Spanish-preferring Hispanic patients had an estimated annualized rate of 0.59 (95% CI=0.46-0.76) mental health visits. CONCLUSIONS: Among patients who were likely to receive specialty mental health services, Spanish-preferring patients had a significantly lower rate of mental health care use. Although overall access to mental health care is improving, unequal access to recurring specialty mental health care remains among patients who do not prefer to use English.

Designing an implementation strategy to increase health-related social needs screening: Applying the PRISM framework in a resource-limited clinical setting.

Despite growing acceptability of health-related social needs (HRSN) screening and increasing policy incentives for adoption, clinical implementation of HRSN screening remains low. HRSN screening has been particularly difficult for Community Health Centers (CHCs), which have limited resources to implement and sustain new workflows. While CHCs provide care to patients with disproportionately high levels of unmet social needs, identifying HRSN screening implementation strategies that take CHC-specific contexts into account remains elusive. This study uses the Practical Robust Implementation and Sustainability Model (PRISM) to design an implementation strategy accounting for the unique context of CHCs. We used Rapid Ethnographic Assessment observations and stakeholder focus groups to identify current workflow barriers and facilitators to HRSN screening, and to develop implementation strategies that include multi-level contexts and perspectives. We identified eight themes contributing to low screening implementation: perceived stigma around screening; need for community-based solutions; re-confirming organizational priorities and values; Electronic Medical Record (EMR) limitations; multi-tasking pressures limiting implementation; staff turnover; limited knowledge of regulatory requirements; and community resource availability for referral. Based on the themes, we identified implementation strategies including non-EMR data collection; integration into the workflow for multiple staff members; creation of new training and educational modules; and identification of peer champions for retraining in real time. Administrative requirements are necessary but not sufficient for implementation of HRSN screening in CHCs. Resource-constrained settings benefit from context-specific stakeholder engagement to improve implementation success. The use of PRISM ensured contextual factors were central to the implementation strategy design.

Health care systems are encouraged to screen for health-related social needs (HRSN), such as housing and food insecurity, yet it has been difficult to implement these new screening workflows. This is especially true for Community Health Centers (CHCs) that have limited resources to implement new workflows. Using a framework that accounts for the unique environment of CHCs, we observed current workflows and conducted focus groups to develop an implementation strategy to facilitate HRSN screening. The new strategy used paper-based workflows to facilitate patient participation and identified clinical champions to engage staff. While these findings are useful in CHCs that might not have sufficient resources to develop screening processes in the Electronic Medical Record, they are also applicable to other low-resourced settings that might want to include HRSNs in patient care, but do not have resources or staff to do it.

Neighborhood-level social determinants of health measures independently predict receipt of living donor liver transplantation in the United States.

Disparities exist in the access to living donor liver transplantation (LDLT) in the United States. However, the association of neighborhood-level social determinants of health (SDoH) on the receipt of LDLT is not well-established. This was a retrospective cohort study of adult liver transplant recipients between January 1, 2005 and December 31, 2021 at centers performing LDLT using the United Network for Organ Sharing database, which was linked through patients' ZIP code to a set of 24 neighborhood-level SDoH measures from different data sources. Temporal trends and center differences in neighborhood Social Deprivation Index (SDI), a validated scale of socioeconomic deprivation ranging from 0 to 100 (0=least disadvantaged), were assessed by transplant type. Multivariable logistic regression evaluated the association of increasing SDI on receipt of LDLT [vs. deceased donor liver transplantation (DDLT)]. There were 51,721 DDLT and 4026 LDLT recipients at 59 LDLT-performing centers during the study period. Of the 24 neighborhood-level SDoH measures studied, the SDI was most different between the 2 transplant types, with LDLT recipients having lower SDI (ie, less socioeconomic disadvantage) than DDLT recipients (median SDI 37 vs. 47; p < 0.001). The median difference in SDI between the LDLT and DDLT groups significantly decreased from 13 in 2005 to 3 in 2021 ( p = 0.003). In the final model, the SDI quintile was independently associated with transplant type ( p < 0.001) with a threshold SDI of ~40, above which increasing SDI was significantly associated with reduced odds of LDLT (vs. reference SDI 1-20). As a neighborhood-level SDoH measure, SDI is useful for evaluating disparities in the context of LDLT. Center outreach efforts that aim to reduce disparities in LDLT could preferentially target US ZIP codes with SDI > 40.

Healthcare-based food assistance programmes in the United States: a scoping review and typology.

This scoping review aimed to identify the breadth of healthcare-based food assistance programmes in the United States and organize them into a typology of programmes to provide implementation guidance to aspiring food assistance programmers in healthcare settings. We searched PubMed, Cochrane, and CINAHL databases for peer-reviewed articles published between 1 January 2010 and 31 December 2021, and mined reference lists. We used content analysis to extract programmatic details from each intervention and to qualitatively analyse intervention components to develop a typology for healthcare institutions in the United States. Eligible articles included descriptions of patient populations served and programmatic details. Articles were not required to include formal evaluations for inclusion in this scoping review. Our search resulted in 8706 abstracts, which yielded forty-three articles from thirty-five interventions. We identified three distinct programme types: direct food provision, referral, and voucher programmes. Programme type was influenced by programme goals, logistical considerations, such as staffing, food storage or refrigeration space, and existence of willing partner CBOs. Food provision programmes (n 13) were frequently permanent and leveraged partnerships with community-based organisations (CBOs) that provide food. Referral programmes (n 8) connected patients to CBOs for federal or local food assistance enrollment. Voucher programmes (n 14) prioritised provision of fruits and vegetables (n 10) and relied on a variety of clinic staff to refer patients to months-long programmes. Healthcare-based implementers can use this typology to design and maintain programmes that align with the needs of their sites and patient populations.

Answering calls for rigorous health equity research: a cross-sectional study leveraging electronic health records for data disaggregation in Latinos.

INTRODUCTION: Country of birth/nativity information may be crucial to understanding health equity in Latino populations and is routinely called for in health services literature assessing cardiovascular disease and risk, but is not thought to co-occur with longitudinal, objective health information such as that found in electronic health records (EHRs). METHODS: We used a multistate network of community health centres to describe the extent to which country of birth is recorded in EHRs in Latinos, and to describe demographic features and cardiovascular risk profiles by country of birth. We compared geographical/demographic/clinical characteristics, from 2012 to 2020 (9 years of data), of 914 495 Latinos recorded as US-born, non-US-born and without a country of birth recorded. We also described the state in which these data were collected. RESULTS: Country of birth was collected for 127 138 Latinos in 782 clinics in 22 states. Compared with those with a country of birth recorded, Latinos without this record were more often uninsured and less often preferred Spanish. While covariate adjusted prevalence of heart disease and risk factors were similar between the three groups, when results were disaggregated to five specific Latin countries (Mexico, Guatemala, Dominican Republic, Cuba, El Salvador), significant variation was observed, especially in diabetes, hypertension and hyperlipidaemia. CONCLUSIONS: In a multistate network, thousands of non-US-born, US-born and patients without a country of birth recorded had differing demographic characteristics, but clinical variation was not observed until data was disaggregated into specific country of origin. State policies that enhance the safety of immigrant populations may enhance the collection of health equity related data. Rigorous and effective health equity research using Latino country of birth information paired with longitudinal healthcare information found in EHRs might have significant potential for aiding clinical and public health practice, but it depends on increased, widespread and accurate availability of this information, co-occurring with other robust demographic and clinical data nativity.

Sources of exposure and risk among employees infected with severe acute respiratory coronavirus virus 2 (SARS-CoV-2) in a large, urban, tertiary-care hospital in the United States.

Objective: Hospital employees are at risk of SARS-CoV-2 infection through transmission in 3 settings: (1) the community, (2) within the hospital from patient care, and (3) within the hospital from other employees. We evaluated probable sources of infection among hospital employees based on reported exposures before infection. Design: A structured survey was distributed to participants to evaluate presumed COVID-19 exposures (ie, close contacts with people with known or probable COVID-19) and mask usage. Participants were stratified into high, medium, low, and unknown risk categories based on exposure characteristics and personal protective equipment. Setting: Tertiary-care hospital in Boston, Massachusetts. Participants: Hospital employees with a positive SARS-CoV-2 PCR test result between March 2020 and January 2021. During this period, 573 employees tested positive, of whom 187 (31.5%) participated. Results: We did not detect a statistically significant difference in the proportion of employees who reported any exposure (ie, close contacts at any risk level) in the community compared with any exposure in the hospital, from either patients or employees. In total, 131 participants (70.0%) reported no known high-risk exposure (ie, unmasked close contacts) in any setting. Among those who could identify a high-risk exposure, employees were more likely to have had a high-risk exposure in the community than in both hospital settings combined (odds ratio, 1.89; P = .03). Conclusions: Hospital employees experienced exposure risks in both community and hospital settings. Most employees were unable to identify high-risk exposures prior to infection. When respondents identified high-risk exposures, they were more likely to have occurred in the community.

Barriers to severe acute respiratory coronavirus virus 2 (SARS-CoV-2) testing reported by healthcare workers during the first pandemic wave at an academic center in Boston, Massachusetts.

Healthcare workers (HCWs) experience barriers to severe acute respiratory coronavirus virus 2 (SARS-CoV-2) testing specific to their perceptions of access, and employment factors. A survey was sent to all employees at one Boston hospital to examine their perceived barriers to testing. HCWs who reported difficulty paying their bills were less likely to receive a SARS-CoV-2 test.

"More than just checking the box": community-based organizations on their role in Medicaid redesigns.

New York and Massachusetts 1115 Medicaid demonstration waivers aimed to prioritize social determinants of health and engage community-based organizations to improve health outcomes. This is an evaluation of community-based organizations' public comments regarding their participation in social services delivery within the 1115 waivers. Both states solicited public comments on waiver implementation to date and potential improvements. The research team extracted all publicly available comments (n = 359) made by direct service providers between November 2016 and April 2019. The sample was then limited to only comments that discussed social service provision and health care-social service partnerships (n = 58). Findings are presented in 2 stages: (1) concerns regarding delivery system reform incentive payments funding levels, timing, and flow and (2) perspectives on how states and Medicaid administrators could improve health care-community organization relationships. Resource-dependent, community-based organizations protested insufficient funding. Additional comments identified specific design, structure, and implementation aspects of the 1115 waiver that could improve partnerships. Despite 1115 waivers prioritizing social service integration, community-based organizations still feel underfunded and disenfranchised. Aligning with health care standards requires significant time and effort. Given resource constraints, the state must facilitate these investments. Community organizations' feedback can also offer guidance on waiver strategies in other states.

To address Medicaid enrollees' social needs, New York and Massachusetts have led the way in aiming to integrate community-based organizations into Medicaid policy and financing. In an evaluation examining public comments submitted by community-based organizations to state Medicaid offices, perspectives on participating in 1115 Medicaid demonstration waivers revealed 2 themes (1) financial concerns about funding, timing, and flow of payments and (2) nonfinancial suggestions for enhancing health care and community-based organization partnerships through standardized partnership standards, enhanced governance, and tailored metrics to better address social determinants of health.

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.

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

INTRODUCTION: Federally Qualified Health Centers serve 29.8 million low-income patients across the U.S., many of whom have unaddressed social risks. In 2019, for the first time, data on social risk screening capabilities were collected from every U.S. Federally Qualified Health Center. The objectives of this study were to describe the national rates of social risk screening capabilities across Federally Qualified Health Centers, identify organizational predictors of screening, and assess between-state heterogeneity. METHODS: Using a 100% sample of U.S. Federally Qualified Health Centers (N=1,384, representing 29.8 million patients) from the 2019 Uniform Data System, the primary outcome was whether a Federally Qualified Health Center collected data on patients' social risk factors (yes/no). Summary statistics on the rates of social risk screening capabilities were generated in aggregate and by state. Linear probability models were then used to estimate the relationship between the probability of social risk screening and 7 key Federally Qualified Health Center characteristics (e.g., Federally Qualified Health Center size, Medicaid MCO contract, Medicaid accountable care organization presence). Data were analyzed in 2020‒2021. RESULTS: Most (71%) Federally Qualified Health Centers collected social risk data, with a between-state variation. The most common screener was the Protocol for Responding to and Assessing Patients' Assets Risks and Experiences (43% of Federally Qualified Health Centers that screened), whereas 22% collected social risk data using a nonstandardized screener. After adjusting for other characteristics, Federally Qualified Health Centers with social risk screening capabilities served more total patients, were more likely to be located in a state with a Medicaid accountable care organization, and were less likely to have an MCO contract. CONCLUSIONS: There has been widespread adoption of social risk screening tools across U.S. Federally Qualified Health Centers, but between-state disparities exist. Targeting social risk screening resources to smaller Federally Qualified Health Centers may increase the adoption of screening tools.

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.

Diabetes Control During Massachusetts Insurance Reform.

Racial/ethnic disparities in glycemic control-a key diabetes outcome measure-continue to widen, even though the overall prevalence of glycemic control in the US has improved. Health insurance coverage may be associated with improved glycemic control, but few studies examine effects during a period of policy change. We assessed changes in glycemic control by racial/ethnic groups following the Massachusetts Health Insurance Reform for patients at two urban safety-net academic health systems between January 2005 and December 2013. We analyzed outcomes for three measures of poor glycemic control: 1) lack of a hemoglobin A1C (A1C) measure during a 6-month period; 2) A1C >8%; 3) A1C >9% before, during, and after implementation of insurance reform. We did not find increased rates of A1C monitoring or control following insurance reform overall or for specific racial/ethnic groups. We found evidence of worsened, not improved, glycemic control in some racial/ethnic groups in the post-reform period. The expansion of affordable insurance coverage was not associated with improved glycemic control in vulnerable populations.