A Clinical-Community Partnership to Address Food Insecurity and Reduce Emergency Department Utilization Among Medicaid-Insured Patients in North Carolina.

CONTEXT: Socioeconomic risk factors have the greatest impact on overall health trajectory. Patients with Medicaid insurance are more likely to experience food insecurity, in addition to poor health and increased health care utilization. Targeted food and produce prescription programs can reduce food insecurity, but sustainable implementation is challenging and evidence demonstrating the impact on clinical utilization outcomes is lacking. PROGRAM: In 2021, a cross-sector collaboration between Mecklenburg County Public Health, Reinvestment Partners, and Atrium Health initiated a food prescription program in urban North Carolina. A low-cost mass text message campaign was used to identify and enroll Medicaid-insured patients with a history of emergency department (ED) utilization. METHODS: A nonrandomized before/after evaluation design was used with a 12-month data collection window (6 months before/after program enrollment) for 711 patients enrolled between June 2021 and 2022. Changes in the odds of nonadmission ED utilization were modeled using logistic regression, adjusting for race/ethnicity, gender, age, comorbidity, and dose, along with interaction by comorbidity. RESULTS: A majority of the sample was non-Hispanic Black (61%; n = 436), female (90%; n = 643), with "none to mild" chronic disease comorbidity (81%; n = 573). The unadjusted and adjusted odds of nonadmission ED utilization significantly reduced between time periods, along with significant interaction by comorbidity. Among the subsamples, patients with "none to mild" comorbidity showed 34% reduction in odds of nonadmission ED utilization (OR = 0.64; 95% CI, 0.47-0.86). DISCUSSION: Food prescription programming targeting Medicaid-insured patients may reduce ED utilization, particularly among those without severe comorbidity. Retrospective data collection and sample homogeneity reduced the quality of evidence, but results offer a pragmatic example that can be replicated for further study. Additional research is needed to strengthen the body of evidence and support cross-sector investment in food and produce prescription programming.

School-Based Telemedicine and Reduced Avoidable Emergency Care Among Rural Pediatric Patients.

Objective: Children living in rural communities have disparate access to preventive health care, shifting the burden of care delivery to emergency services. This study examined the association of school-based telemedicine (SBT) and avoidable emergency department (ED) utilization in rural historically underserved pediatric patients served through an SBT program. Methods: A retrospective analysis was conducted using electronic medical records and claims data from a large integrated health care system serving as the majority health care provider in the area. Participants included all pediatric patients served through an SBT program between 2017 and 2020 across three rural North Carolina counties. The study was a quasi-experimental before/after design comparing 12-month time periods before and after a patient's index virtual care visit. A subset of patients served 12 months before the start of the coronavirus 2019 (COVID-19) pandemic in 2020 was extracted and analyzed separately for a sensitivity analysis. Results: The complete sample included 1,236 patients. The odds of having an avoidable ED visit were reduced by 33% between time periods, and the estimated count of visits was reduced by 26%. (Models were adjusted for race/ethnicity, gender, age, and insurance payer.) No significant differences in unavoidable ED utilization were observed. The sensitivity analysis showed similar trends. Conclusions: Results demonstrate that telemedicine can improve access to health care and may offset the burden of avoidable care through emergency health services. Policy changes and increased use during the COVID-19 pandemic have created an optimal environment for telemedicine expansion to reduce health care access disparities.

An equity-focused approach to improving access to COVID-19 vaccination using mobile health clinics.

This article describes the implementation of an equity-focused strategy to increase the uptake of COVID-19 vaccination among communities of color and in traditionally underserved geographic areas using mobile health clinics (MHCs). The MHC Vaccination Program was implemented through a large integrated healthcare system in North Carolina using a grassroots development and engagement strategy along with a robust model for data-informed decision support to prioritize vulnerable communities. Several valuable lessons from this work can replicated for future outreach initiatives and community-based programming: •Health systems can no longer operate under the assumption that community members will come to them, particularly those experiencing compounding social and economic challenges. The MHC model had to be a proactive outreach to community members, rather than a responsive delivery mechanism. •Barriers to access included financial, legal, and logistical challenges, in addition to mistrust among historically underserved and marginalized communities. •A MHC model can be adaptable and responsive to data-informed decision-making approaches for targeted service delivery. •A MHC model is not a one-dimensional solution to access, but part of a broader strategy to create diverse points of entry into the healthcare system that fall within the rhythm of life of community members.

Residential Segregation and Emergency Department Utilization Among an Underserved Urban Emergency Department Sample in North Carolina.

BACKGROUND Residential segregation is a spatial manifestation of structural racism. Racial disparities in emergency department (ED) utilization mirror social inequity in the larger community. We evaluated associations between residential segregation and ED utilization in a community with known disparities and geographically concentrated social and health risk.METHODS Cross-sectional data were collected from electronic medical records of 101 060 adult ED patients living in Mecklenburg County, North Carolina in 2017. Community context was measured as residential segregation using the dissimilarity index, categorized into quintiles (Q1-Q5) using 2013-2017 American Community Survey estimates, and residency in a public health priority area (PHPA). The outcome was measured as total ED visits during the study period. Associations between community context and ED utilization were modeled using Anderson's behavioral model of health service utilization, and estimated using negative binomial regression, including interaction terms by race.RESULTS Compared to areas with the lowest proportions of Black residents (Q1), living in Q4 was associated with higher rates of ED utilization among Black/Other (AME = 0.11) and White (AME = 0.23) patients, while associations with living in Q5 were approximately equivalent (AME = 0.12). PHPA residency was associated with higher rates of ED utilization among Black/Other (AME = 0.10) and White patients (AME = 0.22).LIMITATIONS Associations should not be interpreted as causal, or be generalized to the larger community without ED utilization. Health system leakage is possible but limited.CONCLUSIONS Residential segregation is associated with higher rates of ED utilization, as are PHPA residency and other individual-level determinants.

Racial/Ethnic Disparities in Health Care Setting Choice for Adults Seeking Severe Acute Respiratory Syndrome Coronavirus 2 Testing.

OBJECTIVES: Equitable access to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing is important for reducing disparities. We sought to examine differences in the health care setting choice for SARS-CoV-2 testing by race/ethnicity and insurance. Options included traditional health care settings and mobile testing units (MTUs) targeting communities experiencing disproportionately high coronavirus disease 2019 (COVID-19) rates. METHODS: We conducted a retrospective, observational study among patients in a large health system in the Southeastern US. Descriptive statistics and multinomial logistic regression analyses were employed to evaluate associations between patient characteristics and health care setting choice for SARS-CoV-2 testing, defined as: (1) outpatient (OP) care; (2) emergency department (ED); (3) urgent care (UC); and (4) MTUs. Patient characteristics included race/ethnicity, insurance, and the existence of an established relationship with the health care system. RESULTS: Our analytic sample included 105,386 adult patients tested for SARS-CoV-2. Overall, 55% of patients sought care at OP, 24% at ED, 12% at UC, and 9% at MTU. The sample was 58% White, 24% Black, 11% Hispanic, and 8% other race/ethnicity. Black patients had a higher likelihood of getting tested through the ED compared with White patients. Hispanic patients had the highest likelihood of testing at MTUs. Patients without a primary care provider had a higher relative risk of being tested through the ED and MTUs versus OP. CONCLUSIONS: Disparities by race/ethnicity were present in health care setting choice for SARS-CoV-2 testing. Health care systems may consider implementing mobile care delivery models to reach vulnerable populations. Our findings support the need for systemic change to increase primary care and health care access beyond short-term pandemic solutions.

A Replicable, Solution-Focused Approach to Cross-Sector Data Sharing for Evaluation of Community Violence Prevention Programming.

CONTEXT: Community violence is a public health problem that erodes social infrastructure. Structural racism contributes to the disparate concentration of violence in communities of color. In Mecklenburg County, North Carolina, increasing trends in community violence show racial and geographic disparities that emphasize the need for cross-sector, data-driven approaches to program and policy change. Cross-sector collaborations are challenged by data sharing barriers that hinder implementation. PROGRAM: In response to community advocacy, Mecklenburg County Public Health (MCPH) launched a Community Violence Prevention Plan with evidence-based programming. The Cure Violence (CV) model, a public health approach to disrupting violence through equitable resource provision, network building, and changing norms, was implemented at the community level. The Health Alliance for Violence Intervention (HAVI) model, a hospital-based screening and case management intervention for victims of violence, was implemented at Carolinas Medical Center in Charlotte, the region's only level I trauma center. METHODS: A data collaborative was created to optimize evaluation of CV and HAVI programs including MCPH, the city of Charlotte, Atrium Health, Charlotte-Mecklenburg Schools, Johnson C. Smith University, and the University of North Carolina Charlotte. A comprehensive approach to facilitate data sharing was designed with a focus on engaging stakeholders and generating solutions to commonly reported barriers. Structured interviews were used to inform a solution-focused strategy. RESULTS: Stakeholders reported perceptions of their organization's barriers and facilitators to cross-sector data sharing. Common technology, legal, and governance barriers were addressed through partnership with a local integrated data system. Solutions for trust and motivational challenges were built into ongoing collaborative processes. DISCUSSION: Data silos inhibit the understanding of complex public health issues such as community violence, along with the design and evaluation of collective impact efforts. This approach can be replicated and scaled to support cross-sector collaborations seeking to influence social and health inequities stemming from structural racism.

Social and demographic characteristics of frequent or high-charge emergency department users: A quantile regression application.

OBJECTIVE: Heavy users of the emergency department (ED) are a heterogeneous population. Few studies have captured the social and demographic complexity of patients with the largest burden of ED use. Our objective was to model associations between social and demographic patient characteristics and quantiles of the distributions of ED use, defined as frequent and high-charge. METHODS: We conducted a cross-sectional analysis of electronic health and billing records of 99 637 adults residing in an urban North Carolina county who visited an ED within Atrium Health, a large integrated health care system, in 2017. Mid-quantile and standard quantile regression models were used for count and continuous responses, respectively. Frequent and high-charge use outcomes were defined as the median (0.50) and upper quantiles (0.75, 0.95, 0.99) of the outcome distributions for total billed ED visits and associated charges during the study period. Patient characteristic predictors were: insurance coverage (Medicaid, Medicare, private, uninsured), total visits to ambulatory care during the study period (0, 1, >1), and patient demographics: age, gender, race, ethnicity, and living in an underprivileged community called a public health priority area (PHPA). RESULTS: Results showed heterogeneous relationships that were stronger at higher quantiles. Having Medicaid or Medicare insurance was positively associated with ED visits and ED charges at most quantiles. Racial and geographic disparities were observed. Black patients had more ED visits and lower ED charges than their White counterparts at most quantiles of the outcome distributions. Patients living in PHPAs, had lower charges than their counterparts at the median but higher charges at the 0.95 and 0.99 quantiles. CONCLUSIONS: The relationships between patient characteristics and frequent and high-charge use of the ED vary based on the level of use. These findings can be used to inform targeted interventions, tailored policy, and population health management initiatives.

Ambulatory care, insurance, and avoidable emergency department utilization in North Carolina.

OBJECTIVE: To examine whether and how avoidable emergency department (ED) utilization is associated with ambulatory or primary care (APC) utilization, insurance, and interaction effects. DESIGN AND SAMPLE: A cross-sectional analysis of electronic health records from 70,870 adults residing in Mecklenburg County, North Carolina, who visited an ED within a large integrated healthcare system in 2017. METHODS: APC utilization was measured as total visits, categorized as: 0, 1, and > 1. Insurance was defined as the method of payment for the ED visit as: Medicaid, Medicare, private, or uninsured. Avoidable ED utilization was quantified as a score (aED), calculated as the sum of New York University Algorithm probabilities multiplied by 100. Quantile regression models were used to predict the 25th, 50th, 75th, 95th, and 99th percentiles of avoidable ED scores with APC visits and insurance as predictors (Model 1) and with an interaction term (Model 2). RESULTS: Having >1 APC visit was negatively associated with aED at the lower percentiles and positively associated at higher percentiles. A higher aED was associated with having Medicaid insurance and a lower aED was associated with having private insurance, compared to being uninsured. In stratified models, having >1 APC visit was negatively associated with aED at the 25th percentile for the uninsured and privately insured, but positively associated with aED at higher percentiles among the uninsured, Medicaid-insured, and privately insured. CONCLUSIONS: The association between APC utilization and avoidable ED utilization varied based on segments of the distribution of ED score and differed significantly by insurance type.

Development, Implementation, and Results from a COVID-19 Messaging Campaign to Promote Health Care Seeking Behaviors Among Community Clinic Patients.

Care-delays can further exacerbate racial and ethnic health disparities in novel coronavirus disease 2019 (COVID-19) related complications. The purpose of our study was to describe and evaluate a Patient Engagement Messaging campaign (PEM campaign) promoting health care seeking behaviors among community and rural clinic patients in North Carolina. Text and voice messages were delivered over 3-weeks. Messages encouraged patients to call a regional operation call center (ROC) line for information related to health care appointments and testing. A cross-sectional evaluation was conducted on the total population (n = 48,063) and a sample without recent health care contact (n = 29,214). Among the sample, logistic regression was used to model determinants of calls to the ROC-line and associations between calling the ROC-line and health care seeking behaviors (scheduling any health care appointment or receiving a COVID-19 test). 69.9% of text messages and 89% of voice messages were delivered. Overall, 95.4% of the total population received at least 1 message. Successful delivery was lower among Black patients and higher among patients with moderate health-risk comorbidities. Among the sample, 7.4% called the ROC-line, with higher odds of calling among minority patients (vs. White) and among Medicaid and uninsured (vs. private insurance). Calling the ROC-line was associated with higher odds of scheduling any health care appointment (OR: 4.14; 95% CI 2.93-5.80) and receiving a COVID-19 test (OR: 2.39; 95% CI 1.64-3.39). Messaging campaigns may help disconnected patients access health care resources and reduce disparities, but are likely still limited by existing barriers.

Using cloud-based, open-source technology to evaluate, improve, and rapidly disseminate community-based intervention data.

Building Uplifted Families (BUF) is a cross-sector community initiative to improve health and economic disparities in Charlotte, North Carolina. A formative evaluation strategy was used to support iterative process improvement and collaborative engagement of cross-sector partners. To address challenges with electronic data collection through REDCap Cloud, we developed the BUF Rapid Dissemination (BUF-RD) model, a multistage data governance system supplemented by open-source technologies, such as: Stage 1) data collection; Stage 2) data integration and analysis; and Stage 3) dissemination. In Stage 3, results were disseminated through an interactive dashboard developed in RStudio using RShiny and Shiny Server solutions. The BUF-RD model was successfully deployed in a 6-month beta test to reduce the time lapse between data collection and dissemination from 3 months to 2 weeks. Having up-to-date preliminary results led to improved BUF implementation, enhanced stakeholder engagement, and greater responsiveness and alignment of program resources to specific participant needs.

Postpartum Depression Screening and Referrals in Special Supplemental Nutrition Program for Women, Infants, and Children Clinics.

OBJECTIVES: To examine the relationships among participants' demographic, social, and health characteristics and positive screening scores for symptoms of postpartum depression (PPD); to examine the feasibility of referring to a case management program women with symptoms of PPD who are accessing Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) services; and to identify barriers to screening and treatment programs for women with symptoms of PPD. DESIGN: Descriptive, cross-sectional study followed by a process evaluation. SETTING: Two WIC clinics in a large southeastern U.S. city. PARTICIPANTS: One group (n = 302) included women with infants younger than 12 months who were screened for symptoms of PPD. The second group (n = 31) included case managers (n = 7), nutritionists (n = 12), advisory board members (n = 7), and student volunteers (n = 5) who participated in focus groups. METHODS: We conducted an initial screening of women for symptoms of PPD using the two-item Patient Health Questionnaire (PHQ-2). Participants with scores of 2 or greater (n = 73) were asked to complete the nine-item PHQ (PHQ-9) and the Edinburgh Postnatal Depression Scale. Participants were referred for case management services if they scored 10 or greater on the PHQ-9 or Edinburgh Postnatal Depression Scale (n = 29) and agreed to the referral (n = 19). We transcribed and analyzed the qualitative data recorded during focus groups. RESULTS: Participants with no health insurance and limited support in caring for their infants were more likely to report symptoms of PPD. Overall, 302 women were screened for PPD, indicating the feasibility of PPD screening in WIC clinics. Of the 19 participants referred to case management, 47% (n = 9) accessed care. The results of focus groups illuminated barriers to screening and treatment programs for women at the individual, local, and macrosystem levels. CONCLUSION: Our findings show the feasibility of PPD screening in WIC clinics. However, some participants did not receive mental health services after referral because of various barriers, which highlights the need to integrate mental health providers into WIC clinics.

Development and functionality of a handheld computer program to improve fruit and vegetable intake among low-income youth.

Mobile technologies hold promise for improving diet and physical activity, but little attention is given to creating programs that adolescents like and will use. This study developed a personal digital assistant (PDA) program to promote increased intake of fruits and vegetables (FV) in predominately low-income, ethnic minority girls. This study used a three-phase community-engaged process, including (i) engagement of a Student Advisory Board (SAB) to determine comfort with PDAs; (ii) early testing of Prototype I and rapid re-design by the SAB and (iii) feasibility testing of Prototype II in a new sample of girls. Phase 1 results showed that girls were comfortable with the PDA. Testing of Prototype I in Phase 2 showed that acceptability was mixed, with girls responding to 47.3% of the prompts. Girls wanted more reminders, accountability in monitoring FV, help in meeting daily goals and free music downloads based on program use. The PDA was reprogrammed and testing of Prototype II in Phase 3 demonstrated marked improvement in use (78.3%), increases in FV intake (1.8 ± 2.6 daily servings) and good overall satisfaction. Findings suggest that mobile technology designed with the early input of youth is a promising way to improve adolescent health behaviors.