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.

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.

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.

Using Community-Based Participatory Research to Develop Geospatial Models Toward Improving Community Health for Disadvantaged Hispanic Populations in Charlotte, NC.

Hispanic immigrant communities across the U.S. experience persistent health disparities and barriers to primary care. We examined whether community-based participatory research (CBPR) and geospatial modeling could systematically and reproducibly pinpoint neighborhoods in Charlotte, North Carolina with large proportions of Hispanic immigrants who were at-risk for poor health outcomes and health disparities. Using a CBPR framework, we identified 21 social determinants of health measures and developed a geospatial model from a subset of those measures to identify neighborhoods with large proportions of Hispanic immigrant populations at risk for poor health outcomes. The geospatial model included four measures-poverty, English ability, acculturation and violent crime-which comprised our Hispanic Health Risk Index (HHRI). We developed a Primary Care Barrier Index (PCBI) to determine (1) how well the HHRI correlated with a statistically derived composite measure incorporating all 21 measures identified through the CBPR process as being associated with access to primary care; (2) whether the HHRI predicted primary care access as well as the statistically-derived composite measure in a statistical model; and (3) whether the HHRI identified similar neighborhoods as the statistically derived composite measure. We collapsed 17 of the 21 social determinants using principal components analysis to develop the PCBI. We determined the correlation of each index with inappropriate emergency department (ED) visits, a proxy for primary care access, using logistic generalized estimating equations. Results from logistic regression models showed positive associations of both the HHRI and the PCBI with the use of the ED for primary care treatable conditions. Enhanced by the knowledge of the local community, the CBPR process with geospatial modeling can guide the multi-tiered validation of social determinants of health and identify neighborhoods that are at-risk for poor health outcomes and health disparities.

Using CBPR to Decrease Health Disparities in a Suburban Latino Neighborhood.

INTRODUCTION: This project tested the feasibility of using a community-based participatory research (CBPR) approach to deliver health and social resources in two high-risk, suburban neighborhoods. METHOD: An established research network was used to engage stakeholders to design and deliver a neighborhood-based intervention targeting a Latino immigrant population. The intervention provided screenings for hypertension, diabetes, and depression; primary care provider visits; and information about navigating health care delivery systems and related community-based resources. Participants ( N = 216) were consented for participation and their subsequent use of health and social services were measured at baseline and 1 year post intervention. RESULTS: At baseline, 5.1% of participants had health insurance, 16.7% had a primary care provider, and 38.4% had a chronic illness. SF-12 scores showed a majority of participants with low perceived health status (56%) and high risk for clinical depression (33%). Self-reported use of primary care services increased from 33.8% at baseline to 48% 1 year after the intervention, and 62% reported use of social services. CONCLUSION: Neighborhood-based interventions informed by a CBPR approach are effective in both identifying community members who lack access to health care-related services and connecting them into needed primary care and social services.

Reducing the Impact of Immigration Enforcement Policies to Ensure the Health of North Carolinians: Statewide Community-Level Recommendations.

BACKGROUND: Research indicates that fear of immigration enforcement among Latinos in North Carolina results in limited access to and utilization of health services and negative health consequences. This project developed recommendations to mitigate the public health impact of immigration enforcement policies in North Carolina. METHODS: Our community-based participatory research partnership conducted 6 Spanish-language report-backs (an approach to sharing, validating, and interpreting data) and 3 bilingual forums with community members and public health leaders throughout North Carolina. The goals of these events were to discuss the impact of immigration enforcement on Latino health and develop recommendations to increase health services access and utilization. Findings from the report-backs and forums were analyzed using grounded theory to identify and refine common recommendations. RESULTS: A total of 344 people participated in the report-backs and forums. Eight recommendations emerged: increase knowledge among Latinos about local health services; build capacity to promote policy changes; implement system-level changes among organizations providing health services; train lay health advisors to help community members navigate systems; share Latinos' experiences with policy makers; reduce transportation barriers; increase schools' support of Latino families; and increase collaboration among community members, organizations, health care providers, and academic researchers. LIMITATIONS: Representatives from 16 of 100 North Carolina counties participated. These 16 counties represent geographically diverse regions, and many of these counties have large Latino populations. CONCLUSIONS: Immigration enforcement is a public health issue. Participants proposed developing new partnerships, identifying strategies, and implementing action steps for carrying out recommendations to reduce negative health outcomes among Latinos in North Carolina.

Por Nuestros Ojos: understanding social determinants of health through the eyes of youth.

BACKGROUND: Understanding the social determinants underlying health disparities benefits from a mixed-methods, participatory research approach. OBJECTIVES: Photovoice was used in a research project seeking to identify and validate existing data and models used to address socio-spatial determinants of health in at-risk neighborhoods. METHODS: High-risk neighborhoods were identified using geospatial models of pre-identified social determinants of health. Students living within these neighborhoods were trained in Photovoice, and asked to take pictures of elements that influence their neighborhood's health and to create narratives explaining the photographs. RESULTS: Students took 300 photographs showing elements that they perceived affected community health. Negative factors included poor pedestrian access, inadequate property maintenance, pollution, and evidence of gangs, criminal activity, and vagrancy. Positive features included public service infrastructure and outdoor recreation. Photovoice data confirmed and contextualized the geospatial models while building community awareness and capacity. CONCLUSIONS: Photovoice can be a useful research tool for building community capacity and validating quantitative data describing social determinants of health.

Comparing the effect of a decision aid plus patient navigation with usual care on colorectal cancer screening completion in vulnerable populations: study protocol for a randomized controlled trial.

BACKGROUND: Screening can reduce colorectal cancer (CRC) incidence and mortality. However, screening is underutilized in vulnerable patient populations, particularly among Latinos. Patient-directed decision aids can increase CRC screening knowledge, self-efficacy, and intent; however, their effect on actual screening test completion tends to be modest. This is probably because decision aids do not address some of the patient-specific barriers that prevent successful completion of CRC screening in these populations. These individual barriers might be addressed though patient navigation interventions. This study will test a combined decision aid and patient navigator intervention on screening completion in diverse populations of vulnerable primary care patients. METHODS/DESIGN: We will conduct a multisite, randomized controlled trial with patient-level randomization. Planned enrollment is 300 patients aged 50 to 75 years at average CRC risk presenting for appointments at two primary clinics in North Carolina and New Mexico. Intervention participants will view a video decision aid immediately before the clinic visit. The 14 to 16 minute video presents information about fecal occult blood tests and colonoscopy and will be viewed on a portable computer tablet in English or Spanish. Clinic-based patient navigators are bilingual and bicultural and will provide both face-to-face and telephone-based navigation. Control participants will view an unrelated food safety video and receive usual care. The primary outcome is completion of a CRC screening test at six months. Planned subgroup analyses include examining intervention effectiveness in Latinos, who will be oversampled. Secondarily, the trial will evaluate the intervention effects on knowledge of CRC screening, self-efficacy, intent, and patient-provider communication. The study will also examine whether patient ethnicity, acculturation, language preference, or health insurance status moderate the intervention effect on CRC screening. DISCUSSION: This pragmatic randomized controlled trial will test a combined decision aid and patient navigator intervention targeting CRC screening completion. Findings from this trial may inform future interventions and implementation policies designed to promote CRC screening in vulnerable patient populations and to reduce screening disparities. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT02054598.

A trans-disciplinary approach to the evaluation of social determinants of health in a Hispanic population.

BACKGROUND: Individual and community health are adversely impacted by disparities in health outcomes among disadvantaged and vulnerable populations. Understanding the underlying causes for variations in health outcomes is an essential step towards developing effective interventions to ameliorate inequalities and subsequently improve overall community health. Working at the neighborhood scale, this study examines multiple social determinates that can cause health disparities including low neighborhood wealth, weak social networks, inadequate public infrastructure, the presence of hazardous materials in or near a neighborhood, and the lack of access to primary care services. The goal of this research is to develop innovative and replicable strategies to improve community health in disadvantaged communities such as newly arrived Hispanic immigrants. METHODS/DESIGN: This project is taking place within a primary care practice-based research network (PBRN) using key principles of community-based participatory research (CBPR). Associations between social determinants and rates of hospitalizations, emergency department (ED) use, and ED use for primary care treatable or preventable conditions are being examined. Geospatial models are in development using both hospital and community level data to identify local areas where interventions to improve disparities would have the greatest impact. The developed associations between social determinants and health outcomes as well as the geospatial models will be validated using community surveys and qualitative methods. A rapidly growing and underserved Hispanic immigrant population will be the target of an intervention informed by the research process to impact utilization of primary care services and designed, deployed, and evaluated using the geospatial tools and qualitative research findings. The purpose of this intervention will be to reduce health disparities by improving access to, and utilization of, primary care and preventative services. DISCUSSION: The results of this study will demonstrate the importance of several novel approaches to ameliorating health disparities, including the use of CBPR, the effectiveness of community-based interventions to influence health outcomes by leveraging social networks, and the importance of primary care access in ameliorating health disparities.

Using Geographic Information Systems (GIS) to understand a community's primary care needs.

INTRODUCTION: A key element for reducing health care costs and improving community health is increased access to primary care and preventative health services. Geographic information systems (GIS) have the potential to assess patterns of health care utilization and community-level attributes to identify geographic regions most in need of primary care access. METHODS: GIS, analytical hierarchy process, and multiattribute assessment and evaluation techniques were used to examine attributes describing primary care need and identify areas that would benefit from increased access to primary care services. Attributes were identified by a collaborative partnership working within a practice-based research network using tenets of community-based participatory research. Maps were created based on socioeconomic status, population density, insurance status, and emergency department and primary care safety-net utilization. RESULTS: Individual and composite maps identified areas in our community with the greatest need for increased access to primary care services. CONCLUSIONS: Applying GIS to commonly available community- and patient-level data can rapidly identify areas most in need of increased access to primary care services. We have termed this a Multiple Attribute Primary Care Targeting Strategy. This model can be used to plan health services delivery as well as to target and evaluate interventions designed to improve health care access.

Geographic Information Systems (GIS) demonstrating primary care needs for a transitioning hispanic community.

BACKGROUND: Hispanics are the largest and fastest growing minority group in the United States. Charlotte, NC, had the 4th fastest growing Hispanic community in the nation between 1990 to 2000. Gaining understanding of the patterns of health care use for this changing population is a key step toward designing improved primary care access and community health. METHODS: The Multiple Attribute Primary Care Targeting Strategy process was applied to key patient- and community-level attributes describing the Charlotte Hispanic community. Maps were created based on socioeconomic status, population density, insurance status, and use of the emergency department as a primary care safety net. Each of these variables was weighed and added to create a single composite map. RESULTS: Individual attribute maps and the composite map identified geographic locations where Hispanic community members would most benefit from increased access to primary care services. CONCLUSIONS: Using the Multiple Attribute Primary Care Targeting Strategy process we were able to identify geographic areas within our community where many Hispanic immigrants face barriers to accessing appropriate primary care services. These areas can subsequently be targeted for interventions that improve access to primary care and reduce emergency department use. The geospatial model created through this process can be monitored over time to determine the effectiveness of these interventions.

Evaluation for community-based programs: the integration of logic models and factor analysis.

PURPOSE: To discuss the utility of and value of the use of logic models for program evaluation of community-based programs and more specifically, the integration of logic models and factor analysis to develop and revise a survey as part of an effective evaluation plan. PRINCIPAL RESULTS: Diverse stakeholders with varying outlooks used a logic model as a framework to reach agreement on a plan for a state-wide evaluation. This evaluation plan utilized a survey of sixth grade students, administered before and after exposure to a year-long abstinence education program. Components of the logic model were linked to specific survey questions. Exploratory factor analysis was then used to assess whether and how the questions in the survey fit with the constructs of the model; confirmatory factor analysis was used to test the hypothesis that the factors identified in the exploratory analysis were consistently represented in the survey. MAJOR CONCLUSIONS: A logic model is a tool that engages stakeholders to link evaluation instruments more closely to specific program objectives. Thus, stakeholders can more closely assess the extent to which project outcomes have been achieved. In addition, use of factor analysis in the evaluation process can help the stakeholders better understand whether evaluation instruments such as a survey adequately assess program effectiveness. Lastly, a logic model process can help to achieve consensus among diverse stakeholders, by allowing them to focus on objectives that are concrete, measurable, and mutually acceptable.