Facilitators and Barriers to Patient Attendance at a Free Health Center Produce Market

Identification of Social Risk-Related Referrals in Discrete Primary Care Electronic Health Record Data: Lessons Learned From a Novel Methodology

OBJECTIVE

To assess the utility of using discrete primary care electronic health record (EHR) data to identify social risk referrals in a national network of community-based clinics.

DATA SOURCES AND STUDY SETTING

Primary data were abstracted from the OCHIN network EHR (June 2016 to February 2022) of 1459 community-based clinics across the United States.

STUDY DESIGN

Structured data elements included 913 commonly used smartphrases and 53 procedure codes that were considered potential indicators of social risk referrals. Using stratified purposive sampling, we compared these discrete data with clinical notes to assess concordance of social risk referral documentation, and of the prevalence, types, and outcomes of such referrals.

DATA COLLECTION/EXTRACTION METHODS

Smartphrases were classified into three categories (likely, possible, or unlikely to indicate a social risk referral); 50 chart notes were sampled for each of the 25 most frequently used smartphrases in each category, and for 53 of the most frequently used procedure codes. A total of 6104 chart notes were reviewed.

PRINCIPAL FINDINGS

In 59% of chart notes where discrete data suggested a social risk referral occurred, there was no documentation of this in the note. Primary domains addressed were food insecurity (38%), financial stress (18%) and housing needs (18%). Common referral activities included providing contact information (26%), help with assistance applications (17%), and direct provision of resources (16%). Documentation indicated the patient received resources in 29% of notes.

CONCLUSIONS

EHR documentation of social risk referrals in structured data fields is inconsistent. Further work should establish best practices, especially given emerging policies that tie payments to documentation of social risk screening and intervention provision. Community health centers may struggle to use data elements such as smartphrases and procedure codes to monitor and report on their social risk referrals until standardized coding practices are established and effectively implemented.

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.

Predictors of Food Insecurity and Food Assistance Program Usage Among Puerto Ricans Before and During the COVID-19 Pandemic in Holyoke, Massachusetts

BACKGROUND/OBJECTIVES

Puerto Rican households often face elevated rates of food insecurity. Frequently, households experiencing food insecurity turn to federal and emergency nutrition assistance for urgent or prolonged aid. This study analyzes factors influencing food insecurity and food assistance program involvement among Puerto Ricans in Holyoke, Massachusetts, amidst the COVID-19 pandemic.

METHODS

Using a combination of community-based participatory recruitment, purposive sampling, and web-based tools, we collected 284 survey responses. Our paper employed Pearson's chi-square, logistic regression, and hierarchical linear models to assess relationships between demographic and household attributes and food access outcomes.

RESULTS

Variables such as having children in the household and age significantly influenced food relief participation and food insecurity outcomes. Puerto Rican heritage and low educational attainment were strong predictors of obtaining federal food aid. Low-income participants disproportionately faced food shortages and depended on emergency food initiatives. Our findings indicate that demographic and household factors significantly influence food insecurity and accessibility.

CONCLUSIONS

Our study demonstrates that the pandemic made it challenging for households to obtain consistent, safe, and affordable nourishment. The impacts were unequally spread; hence, Puerto Rican communities and low-income groups were most affected.

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.

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.

Food Pantry Referral and Utilization in a Pediatric Primary Care Clinic

INTRODUCTION

This study aimed to characterize progression from screening for food insecurity risk to on-site food pantry referral to food pantry utilization in pediatric primary care.

METHODS

This retrospective study included 14,280 patients aged 0-21 years with ≥1 pediatric primary care visit from March 2018 to February 2020. Analyses were conducted in 2020-2022 using multivariable regression to examine patient-level demographic, clinical, and socioeconomic characteristics and systems-related factors associated with progression from screening positive for food insecurity risk to food pantry referral to completing ≥1 food pantry visit.

RESULTS

Of patients screened for food insecurity risk, 31.9% screened positive; 18.5% of food-insecure patients received an on-site food pantry referral. Among patients referred, 28.9% visited the food pantry. In multivariable models, higher odds of referral were found for patients living near the clinic (AOR=1.28; 95% CI=1.03, 1.59), for each additional health-related social need reported (AOR=1.23; 95% CI=1.16, 1.29), and when the index clinic encounter occurred during food pantry open hours (AOR=1.62; 95% CI=1.30, 2.02). Higher odds of food pantry visitation were found for patients with a preferred language of Haitian Creole (AOR=2.16; 95% CI=1.37, 3.39), for patients of Hispanic race/ethnicity (AOR=3.67; 95% CI=1.14, 11.78), when the index encounter occurred during food pantry open hours (AOR=1.96; 95% CI=1.25, 3.07), for patients with a clinician letter referral (AOR=6.74; 95% CI=3.94, 11.54), or for patients with a referral due to a screening-identified food emergency (AOR=2.27; 95% CI=1.30, 3.96).

CONCLUSIONS

There was substantial attrition along the pathway from screening positive for food insecurity risk to food pantry referral and utilization as well as patient-level characteristics and systems-related factors associated with successful referrals and utilization.