Medically Underserved Area Research Articles

Associations of geographic-based socioeconomic factors and HPV vaccination among male and female children in five US states

BackgroundWe assessed whether five geographic-based socioeconomic factors (medically underserved area (MUA); healthcare provider shortage area (HPSA); persistent poverty; persistent child poverty; and social vulnerability index (SVI)) were associated with the odds of HPV vaccination initiation, series completion, and parental vaccine hesitancy, and whether the observed relationships varied by gender of the child.MethodsAn online panel service, administered through Qualtrics®, was used to recruit parents of adolescents 9–17 years of age to complete a one-time survey in 2021. Coverage of the panel included five US states: Arkansas, Mississippi, Missouri, Tennessee, and Southern Illinois. Generalized estimating equation (GEE) models were used to assess population-level associations between five geographic-based socioeconomic factors (MUA; HPSA; persistent poverty; persistent child poverty; and SVI) and three HPV vaccination outcomes (initiation, series completion, and hesitancy). All GEE models were adjusted for age of child and clustering at the state level.ResultsAnalyses were conducted using responses from 926 parents about their oldest child in the target age range (9–17 years). The analytic sample consisted of 471 male children and 438 female children across the five states. In adjusted GEE models, persistent child poverty and HPSA were negatively associated with HPV vaccination initiation and series completion among female children, respectively. Among male children, high social vulnerability was negatively associated with HPV vaccine series completion. Additionally, persistent poverty and high social vulnerability were negatively associated with HPV vaccine hesitancy in male children.ConclusionsThe results of this cross-sectional study suggest that geographic-based socioeconomic factors, particularly, HPSA, persistent poverty, and SVI, should be considered when implementing efforts to increase HPV vaccine coverage for adolescents. The approaches to targeting these geographic factors should also be evaluated in future studies to determine if they need to be tailored for male and female children.

Joint exposure to urban-rural status and medically underserved area residence and risk of severe COVID-19 outcomes in 2020.

The purpose of this study is to estimate the risk of severe COVID-19 among individuals residing in rural, medically underserved counties compared to those living in other counties. Individual-level COVID-19 hospitalization and death data and demographic variables were downloaded from the Centers for Disease Control and Prevention. The 2013 National Center for Health Statistics Urban-Rural Classification Scheme was used to classify urban and rural counties. Health Resources and Services Administration's medically underserved area (MUA) designation was used to identify underserved counties. County-level data were drawn from the 2015-2019 American Community Survey 5-year estimates. Analytic samples included data from Minnesota and Montana in 2020. Urban-rural/MUA joint exposure categories were created: rural/MUA, rural/non-MUA, urban/MUA, urban/non-MUA. Hierarchical logistic regression models estimated associations (odds ratios and 95% confidence intervals (CI)) between rurality, MUA status, joint urban-rural/MUA status, and severe COVID-19, overall and stratified by age and state. Models were adjusted for individual- and county-level demographics. The odds of severe outcomes among those living in rural counties were 13% lower (95%CI: 0.83-0.91) than those in urban counties. The odds of severe outcomes among those living in MUA counties were 24% higher (95%CI: 1.18-1.30) than those in non-MUA counties. For joint exposure analyses, the odds of severe outcomes were highest among those living in urban/MUA counties compared to those in rural/non-MUA counties (adjusted odds ratio: 1.36, 95%CI: 1.27-1.44). In 2020, the risk of severe COVID-19 was more pronounced in urban counties and underserved areas. Results highlight the need for locality-based public health recommendations that account for rural and underserved areas and may inform future pandemic preparedness by identifying counties most in need of resources and education at various stages of the pandemic.

Expanding rural access to phase I clinical trials.

e18525 Background: Rural cancer patients (RCPs) represent 15-20% of those diagnosed with cancer in the United States (US). RCPs experience decreased access to oncology specialists, increased travel burden, and limited access to clinical trials, as well as unique socioeconomic factors that adversely impact their cancer outcomes. Phase I clinical trials often require complex coordination, frequent follow-up visits, and specialized support staff traditionally limiting access to larger, urban centers. Inclusion of RCPs on these trials can broaden understanding of these therapeutics early in their development. Methods: Starting in 2015, our community oncology program initiated a phase I center dedicated to improving access to RCPs. We evaluated enrollments, patient characteristics, residential location (metro vs. non-metro) as defined by the US Federal Office of Rural Health Policy (FORHP), medically underserved area (MUA) status as defined by the US Health Resources & Services Administration (HRSA), and clinical trial characteristics from April 2015-January 2023. Trials included were phase I, phase IB, or phase I/II trials with safety and/or dosing as the primary endpoint, as well as pharmacokinetic and/or pharmacodynamic secondary endpoints. Our primary outcome was the proportion of FORHP-defined rural participants enrolled. Secondary outcomes included treatment-related deaths and percentage of participants lost to follow-up. Descriptive analysis of patient and clinical trial characteristics was performed. Results: During the analysis period, 21 clinical trials meeting the inclusion criteria were opened. 218 participants were enrolled. Of these participants, 114 (52.3%) resided in FORHP-defined rural locations (89.5% non-metro and 10.5% metro). 23.9% resided in HRSA MUAs. Average distance traveled to our center was 76.1 miles (range 0.4-483 miles). Of these participants, there were no treatment-related deaths. 5 patients (2.3%) were lost to follow-up on study, all during long-term follow-up. Median age of participants was 62 years (range 33-85). 59.2% were male and 40.8% female. Races represented in the studies included: 95% White non-Latino, 2.3% Native American, 0.9% White Latino, 0.5% African American, 1.4% declined/not reported. Common disease sites treated included: 39.9% head and neck, 17.4% non-small cell lung, 11% pancreas, 5.5% melanoma, 5% colorectal, 4.6% breast, and 3.7% ovarian. Of the 21 clinical trials, 38.1% were phase I, 19% were phase IB, and 2.9% were phase I/II. Conclusions: Our center successfully and safely implemented a community-based phase I program with over half the participants enrolled from rural areas. Despite long distances traveled and high rates of rural residency, there were no treatment-related deaths and excellent follow-up rates. These findings support efforts to expand access to phase I trials in a rural setting.

Drive-Through Mass Vaccination Center Operations in a Rural, Medically Underserved Area Using Military Civilian Partnership During the COVID-19 Pandemic.

During the coronavirus disease (COVID-19) pandemic, mass vaccination centers became an essential element of the public health response. This drive-through mass vaccination operation was conducted in a rural, medically underserved area of the United States, employing a civilian-military partnership. Operations were conducted without traditional electronic medical record systems or Internet at the point of vaccination. Nevertheless, the mass vaccination center (MVC) achieved throughput of 500 vaccinations per hour (7200 vaccinations in 2 days), which is comparable with the performance of other models in more ideal conditions. Here, the study describes the minimum necessary resources and operational practicalities in detail required to implement a successful mass vaccination event. This has significant implications for the generalizability of our model to other rural, underserved, and international settings.

Perceptions About Discrimination in a Rural, Older, Racially and Ethnically Diverse Cohort.

The purpose of this pilot study was to examine perceptions of discrimination among a small cohort of rural older, retired minority Florida farmworkers. Potential sources of discrimination were explored, such as health literacy, age, sex, gender, racial/ethnic background, or rural residency. The study occurred in a rural area that is designated as a "hot zone" due to its HRSA designation as a medically underserved area (MUA), health provider shortage area (HPSA), and medically underserved population, despite lying only 50 miles due west of the affluent town of Palm Beach, Florida. More than 40% of residents live below the poverty level, and only 65% have received a high school diploma. A descriptive, correlational pilot study was conducted to investigate potential contributors to discrimination. Independent variables examined were age, sex, gender, rural residency, racial/ethnic background, and health literacy, using the Rapid Estimate of Health Literacy in Medicine, short form (REALM-SF) (Arozullah, 2007). The incidence of self-reported discrimination was investigated. Chi-square and Pearson correlation analysis were employed to examine survey results. Findings were supplemented with a brief narrative inquiry, and responses were analyzed using Saldaña's (2015) model of cyclical coding. Twenty-five residents in a subsidized housing unit agreed to participate in this study. This convenience sample was 96% racially/ethnically diverse (68% African American, 24% Haitian Creole, and 4% Hispanic American.) Most (78%) were retired field workers, and largely self-identified as female (72%). The residents' average reading level was 4th-6th grade. Health literacy (44%) and rural residency (24%) were the greatest sources of discrimination. Female gender discrimination was associated with ethnicity discrimination (r = 0.6, p = .002). Providers are strongly encouraged to assess their patients' health literacy levels and experiences with discrimination to inform effective care delivery.

67 Risk-Based Assessment of the Opioid Crisis in Philadelphia, Pennsylvania Utilizing Global Information Systems as a Template for Public Health Reform

Philadelphia, Pennsylvania has the highest opioid overdose fatality rate in the United States. The collective progress of combating the opioid crisis in Philadelphia is halted because the tactics imposed, and viewpoints held by numerous public service standpoints have far more differences than similarities. Working together to bridge the gaps between prevention tactics, policies, education, and treatment is imperative for successful mitigation of this ubiquitous problem. Geographic Information Systems (GIS), a mapping software, has made it possible to view comprehensive maps that layer tangible data. This study elucidates risk factors prohibiting Philadelphia from staunching the damage, identifies the impact of prevention strategies, and analyzes treatment success. Open-source data was collected from federal, state, and county health agencies was analyzed using PolicyMap. Individual Pennsylvania (PA) counties’ rate of deaths from all opioid overdoses per 100,000 people in 2019 was assessed in relation to the national rate (15) and the PA rate (23). areas with rates less than 20 were shown as “insufficient data.” County rates of opioid prescriptions per 100 people were compared with the national rate (46.7) and PA rate (47). The reported Index of Medical Underservice Score (IMU) data for only Philadelphia was visualized by census tract with the upper limit adjusted to 62, to reflect the US Health Resources and Services Administration definition of a Medically Underserved Area (MUA). Non-MUA and Governor are shown as “insufficient data.” Buprenorphine providers, drug and alcohol treatment facilities, and hospitals were plotted on the IMU and poverty maps. The Philadelphia estimated percent of people living in poverty between 2015-2019 was mapped using ranges based on census tracts. These ranges were compared to the whole number national poverty average (13) and average for Pennsylvania (12). Philadelphia’s rate of deaths from opioid overdose per 100,000 people in 2019 is 50.4, two times the PA average and over three times the national average. It is the only PA county with an opioid rate over 50. The rate of opioid prescriptions per 100 people in 2019 is 49.9, similar to the national rate (46.7) and the PA rate (47). Treatment resources, 428 buprenorphine prescribers, 84 drug and alcohol treatment facilities, and 33 hospitals, were spread out unequally within Philadelphia. Central, East, and Southwest regions of Philadelphia are MUAs with a moderate concentration of buprenorphine prescribers and alcohol and drug treatment facilities. Hospitals were sparse in regions with very low IMU scores and consolidated in Central Philadelphia. Poverty rates varied throughout Philadelphia with a notable absence in hospitals in the areas with highest percentages of poverty. GIS provides dynamic public health measures that underscore critical data and correlate terrain with strategic outcomes. This comparative data tool was utilized to both highlight the detrimental impact of the opioid crisis in Philadelphia and evaluate the inadequate deployment of various prevention and treatment tactics. The evidence that this region is prescribing opioids at slightly above the state and national averages while simultaneously having much more fatal opioid overdoses, highlights the need for new harm reduction strategies to reverse the pernicious trends that have devastated Philadelphia.

COVID-19 and Telehealth Operations in Texas Primary Care Clinics: Disparities in Medically Underserved Area Clinics.

The COVID-19 pandemic has dramatically altered the landscape of health care delivery, prompting a rapid, widespread adoption of telehealth in primary care practices. Using a pooled sample of 1,344 primary care clinics in Texas, we examined the adoption of telehealth in Texas during the initial months of the COVID-19 pandemic, by comparing medically underserved area (MUA) clinics and non-medically underserved area (non-MUA) clinics. Our analysis suggests that compared with MUA clinics, clinics in non-MUAs were more likely to conduct a majority of their visits via telehealth before May 1st, 2020. However, later surveys indicated that differences in telehealth use between MUA and non-MUA clinics lessened, suggesting that some of the barriers that MUA clinics initially faced might have resolved over time. This research provides an additional perspective in discussions about telehealth adoption on a widespread, permanent basis in Texas and the U.S.

Rural-Urban Disparities in Pancreatic Cancer Stage of Diagnosis: Understanding the Interaction With Medically Underserved Areas.

To estimate differences in pancreatic cancer diagnosis stage by rurality of patient residence and residence in a medically underserved area (MUA). Using 2010-2016 Pennsylvania Cancer Registry data, we restrict our analysis to adults diagnosed with pancreatic cancer. We categorize each patient's residence by Rural-Urban Continuum Codes (RUCC): (1) metro; (2) nonmetro adjacent with population ≥20,000; (3) nonmetro adjacent with population <20,000; (4) nonmetro nonadjacent, and (5) completely rural; also by whether the county was a full MUA, partial MUA, or non-MUA. We examine the percent of patients diagnosed with local and locoregional stage of disease for each residential rurality and MUA status grouping. We estimate multivariate linear probability models of local and locoregional stage of diagnosis while controlling for demographics, insurance type, year, rurality, and MUA status. Finally, we estimate models interacting rurality with MUA status to disentangle the relative impact of each on diagnostic stage. We find that no pancreatic patients living in completely rural areas were diagnosed at the local stage, the lowest of all categories of rurality. In adjusted models, we find that patients living in completely rural areas have significantly lower rates of local and local/regional stage of diagnosis. The estimates are attenuated slightly when controlling for MUA. We find significantly lower rates of early stage pancreatic cancer diagnosis for patients living in completely rural areas. While lack of primary medical care resources is an important factor, rural residence remains an important independent predictor in later stage of diagnosis.

Improvement of Working Memory is a Mechanism for Reductions in Delay Discounting Among Mid-Age Individuals in an Urban Medically Underserved Area.

Delay discounting, or the tendency to devalue rewards as a function of their delayed receipt, is associated with myriad negative health behaviors. Individuals from medically underserved areas are disproportionately at risk for chronic health problems. The higher rates of delay discounting and consequent adverse outcomes evidenced among low-resource and unstable environments suggest this may be an important pathway to explain health disparities among this population. The current study examined the effectiveness of a computerized working memory training program to decrease rates of delay discounting among residents of a traditionally underserved region. Participants (N = 123) were recruited from a community center serving low income and homeless individuals. Subjects completed measures of delay discounting and working memory and then took part in either an active or control working memory training. Analyses indicated that participants in the active condition demonstrated significant improvement in working memory and that this improvement mediated the relation between treatment condition and reductions in delay discounting. Results suggest that a computerized intervention targeting working memory may be effective in decreasing rates of delay discounting in adults from medically underserved areas (ClinicalTrials.gov number NCT03501706).

Addressing medically underserved populations through maternal-fetal transport: a geographic analysis

Objective: Despite regionalization of maternal care in the USA, there is little contemporary information on characteristics and utilization of maternal–fetal transport. We used geographic analysis to investigate referral and transportation patterns of the maternal–fetal transport service at our institution.Methods: This is a retrospective cohort study of all calls taken by our maternal–fetal transfer service. Call logs were abstracted, and diagnoses, gestational ages, referring hospital, and mode of transportation were analyzed. The United States Health Resources and Services Administration’s Medically Underserved Area (MUA) designations were used to identify hospitals in these areas. Geographic information system software was used to analyze and map geographic variables, including frequency of transfers from each hospital, distance traveled, mode of transfer, and MUAs.Results: From November 2012 to March 2017, there were 835 telephone consults without transfer and 1682 patients transferred from 103 hospitals. Preterm labor was the most common diagnosis (n = 338, 20%), followed by hypertensive disorders (n = 231, 14%). There were 738 transfers (44%) from MUAs, and 20 (19%) of hospitals were critical access hospitals, accounting for 121 (7%) transfers. One-way trips from a referring hospital accounted for 659 patients, and the transport team was dispatched in 1023 cases. The median distance traveled was 24 mi. For hospitals within 50 mi, the mean difference in transport time between air and ground was <1 h, yet there were 73 air round trips for hospitals <50 mi from our hospital.Conclusion: The transfer system is robust and supports underserved hospitals; however, the service could be deployed more efficiently.

Educational Intervention in a Medically Underserved Area.

Medical students from rural and medically underserved areas (MUAs) are more likely than their peers to practice medicine in rural areas and MUAs. However, students from MUAs are also more likely to face socioeconomic barriers to a career in medicine. To determine whether a week-long summer enrichment experience (SEE) at Edward Via College of Osteopathic Medicine-Carolinas could successfully teach high school students from MUAs basic biomedical concepts and foster an interest in medicine and the health sciences. The SEE program is open to high school students in the Spartanburg, South Carolina, area. The program includes interactive lectures, laboratories, demonstrations on gross anatomy prosections, demonstrations on medical simulation models, tours of emergency vehicles, an introduction to osteopathic manipulative medicine, and student-led research projects. Participants were asked to complete a 15-question quiz that assessed their knowledge of basic biomedical concepts and a 10-question survey that assessed their attitudes toward careers in medicine and health sciences. Both the quiz and the survey were completed on both the first and final days of the program. The data were analyzed using paired t tests. Participant knowledge of basic biomedical concepts, as determined by the quiz scores, increased after completion of the program (9.1 average correct answers vs 12.6 average correct answers) (P<.001). Participant attitude toward medicine and the health sciences improved in 9 of the 10 items surveyed after completion of the program (P<.05). Participant knowledge of basic biomedical concepts and their knowledge of and interest in careers in the health sciences improved after completing the SEE program. These findings suggest that educational interventions for high school students could help to develop primary care physicians for rural areas and MUAs and that there is a role for osteopathic medical schools to nurture these students as early as possible.

School-Based Interprofessional Asthma Self-Management Education Program for Middle School Students: A Feasibility Trial.

Asthma is the most common chronic disease among school-aged children under 18 years of age and is a major cause of morbidity, loss of school days, and increased hospitalizations. Asthma disproportionately affects low-income, minority youth in Alabama. The benefits of improving asthma control and self-management have significance for improving health, preventing disease, and reducing health disparities by addressing social, behavioral, environmental, economic, and medical determinants of health. This collaborative community partnership between the Mobile County Public School System, University of South Alabama (USA), and USA Children's and Women's Hospital involved nursing students, respiratory therapy students, and medical residents from three colleges and the hospital. The research question was whether a school-based asthma self-management education program presented by an interprofessional team was feasible for teens with asthma in a medically underserved area (MUA). Middle school students with a diagnosis of asthma participated in this institutional review board-approved study. Asthma assessments, one-on-one coaching, and group education were done over five sessions, using Power Breathing for teens curriculum. Instruments were the Childhood Asthma Control Test (ACT), the Asthma Responsibility Questionnaire (ARQ), the Self-Efficacy Scale, the Pediatric Asthma Quality of Life Questionnaire (PAQLQ), peak flow monitoring, and spirometry. Eighteen students with moderate to severe persistent asthma completed the program with reduced asthma symptoms and increased asthma control, medication knowledge/skills, self-efficacy, and asthma responsibility. Adolescents with asthma need education in medication management, spacer use, peak flow, trigger avoidance, and coaching to take on the responsibility of asthma care. This multidimensional, interprofessional approach can strengthen asthma self-management in a middle school medically underserved community population.

Behavioral determinants for vaccine acceptability among rurally located college students

ABSTRACTBackground: College-aged adults in a rural and medically-underserved area often struggle to receive proper vaccinations due to lower socioeconomic status coupled with life demands.Objectives: The Theory of Planned Behavior (TPB) was used as the theoretical basis to explore behavioral determinants associated with vaccination uptake in the population.Methods: This study used a questionnaire distributed to college students (n = 208) located in a rural area to assess the effects of social and behavioral factors on vaccination uptake.Results: Attitudes and normative beliefs towards vaccination uptake were positive but were largely impacted by work demands. Perceived behavioral control did not contribute towards the intent to receive necessary vaccines.Conclusions: Researchers conducting vaccination interventions, along with physician-patient communication, need to target attitudes and subjective norms in rural and medically underserved communities to increase vaccines, particularly HPV. In addition, results showed that promoting vaccine uptake among minorities is necessary to aid in vaccine acceptability in these communities.

Abstract P113: Pairing the Mobile Device: Does the Engagement of Student Health Coaches Help Patients Use Smart-phone Enabled Devices for Blood Pressure Monitoring?

Research Question: Does pairing of health coaches with smartphone-enabled blood pressure cuffs improve hypertension control and self-monitoring in a medically underserved area (MUA)? Introduction/Context: This pilot study aims to assess whether infusing tech-savvy youths trained as health technology coaches would (1) be a feasible approach in an MUA and (2) improve the frequency of self-monitoring, patient satisfaction, and blood pressure control of Stockton residents. Methods: Patients with hypertension were randomly assigned to 1 of 3 intervention arms. The “Cuff Alone" (CA) group was provided a QardioArm cuff only, and was encouraged to use the cuff at their convenience. The “Student Alone" (SA) group was instructed to meet for 30 minutes once a week for 5 weeks with a student health coach who had completed a 3-day health coach training. The third group “Student Plus Cuff" (SPC) group received both a QardioArm cuff and student coach. Student coaches and patients were surveyed about their experience in the project. Results: Participants (n=27) were randomly assigned (9:9:9). All 15 students completed training and 6/15 students (40%) completed all 5 meetings with their assigned patient. Barriers to feasibility included transportation and patient response drop-off at the end of the study. There was a statistically significant difference in frequency of cuff use (SPC vs CA groups, 37v17, p&lt;0.01). The initial blood pressures for SPC, SA and CA groups were 139/78, 142/84, and 149/85 mmHg, respectively. Final BP readings were 128/69, 150/85, and 145/85 mmHg, respectively. The SPC group was the only group that reached adequate BP control, though it was not statistically significant (p=0.89). 77% of the SPC group rated the project overall as excellent, compared to CA and SA (77% vs 55% vs 44%). 78% of SPC participants reported their blood pressure to be well controlled most days of the week, compared to CA (32%) and SA (22%). Conclusions: This pilot trial demonstrated feasibility of pairing technology with that young student coaches, though challenges existed. The SPC group used their cuff more than twice the frequency of the CA group. Patients were more engaged in the SPC group, resulting in better blood pressure control by both self-reported and objective measures.

Abstract WP271: Door to Page Time to Initiate a Telemedicine Consult Varies Among Spoke Hospitals for Acute Stroke

Introduction: Although telemedicine (TM) has increased tPA use for acute ischemic stroke (AIS), there are delays between when an AIS patient enters the ED and when the TM consultant is paged. We identified predictors of delayed door-to-page time (DTP) for AIS patients evaluated on TM. Hypothesis: We investigated spoke characteristics associated with the time between patient arrival and the TM code stroke page. Methods: We identified suspected AIS patients in our telestroke registry who were evaluated by video consultation at one of 15 spoke hospitals within six hours of symptom onset (9/2015-3/2016). We compared DTP among spokes and identified factors associated with prolonged DTP. Results: Median DTP was 22 minutes (12-38, Q1-Q3). Of 382 cases 44.0% had DTP ≤20 minutes and 13.5% &gt;60 minutes (Figure). There was no significant difference in DTP among patients of different age, gender, race/ethnicity, and stroke severity (Table). Hospitals with fewer beds, no pre-notification protocols, location in a medically underserved area (MUA), and less in-house neurology availability had delayed DTP. Conclusions: Bed capacity, pre-notification, location in a MUA, and in-house neurology availability are associated with prolonged DTP. While retrospective in nature, our study confirms the utility of pre-notification for spoke hospitals. Further investigation is needed to understand why smaller hospitals and spokes in a MUA have longer DTP, and how in-house neurology coverage affects DTP. In addition, standardized acute stroke metrics over TM are needed.

Unmet Primary Care Needs in Diabetic Patients with Multimorbidity in a Medically Underserved Area.

Background:Diabetic patients with multimorbidity in medically underserved minority communities are less engaged in primary care and experience high emergency department (ED) utilization. This study assesses unmet primary care needs among diabetic patients in a medically underserved area (MUA).Community Context:A suburb of Memphis—Whitehaven, Tennessee (Shelby County, ZIP codes 38109 and 38116)—majority African American (96.6%) with 30.5% below the poverty level.Methods:Community case study using multiple data sources including diabetes registry, individual interviews, focus groups, and a survey of 30 ED patients with diabetes and multimorbidity.Results:Diabetes registry data indicated that 95.5% of 5723 diabetic patients had multimorbidity. Over 91.5% were uncontrolled at some point in 2014 to 2015. Only 83% of patients with diabetes and multimorbidity reported having a primary care provider (PCP) and those without a PCP were more likely to report delays in needed care. Patients expressed strong interest in health coaching (88%) and receiving text messages from the doctor’s office (73%). Individual patient interviews (n = 9) and focus groups (n = 11) revealed common primary care and self-care experiences and needs including diabetes education, improved patient–provider communication, health-care access and coverage, and strengthened primary care and community.Conclusion:This study demonstrates that almost 1 in 5 ED complex diabetic patients in an MUA do not have a PCP, and that difficulty accessing primary care often results in patients forgoing needed care. Qualitative findings support these conclusions. These results suggest that primary care capacity and infrastructure to support diabetes self-care need strengthening in MUAs.

Patient Navigation in Medically Underserved Areas study design: A trial with implications for efficacy, effect modification, and full continuum assessment

BackgroundThe Patient Navigation in Medically Underserved Areas study objectives are to assess if navigation improves: 1) care uptake and time to diagnosis; and 2) outcomes depending on patients' residential medically underserved area (MUA) status. Secondary objectives include the efficacy of navigation across 1) different points of the care continuum among patients diagnosed with breast cancer; and 2) multiple regular screening episodes among patients who did not obtain breast cancer diagnoses. Design/MethodsOur randomized controlled trial was implemented in three community hospitals in South Chicago. Eligible participants were: 1) female, 2) 18+years old, 3) not pregnant, 4) referred from a primary care provider for a screening or diagnostic mammogram based on an abnormal clinical breast exam. Participants were randomized to 1) control care or 2) receive longitudinal navigation, through treatment if diagnosed with cancer or across multiple years if asymptomatic, by a lay health worker. Participants' residential areas were identified as: 1) established MUA (before 1998), 2) new MUA (after 1998), 3) eligible/but not designated as MUA, and 4) affluent/ineligible for MUA. Primary outcomes include days to initially recommended care after randomization and days to diagnosis for women with abnormal results. Secondary outcomes concern days to treatment initiation following a diagnosis and receipt of subsequent screening following normal/benign results. DiscussionThis intervention aims to assess the efficacy of patient navigation on breast cancer care uptake across the continuum. If effective, the program may improve rates of early cancer detection and breast cancer morbidity.

Abstract IA38: Patient navigation in medically underserved areas

Abstract IA38: Patient navigation in medically underserved areas

Abstract B72: Timely breast cancer diagnostic resolution: Effects of individual and neighborhood characteristics

Abstract Background: Disparities occur throughout the breast cancer continuum. African American women are more likely to be diagnosed with cancer at later stages, which results in poorer outcomes. In fact, despite lower incidence, the mortality rates are higher among black women. While timely follow-up of abnormal breast cancer diagnostic test results could lead to early diagnosis and better treatment outcomes, a myriad of factors may influence timely diagnostic resolution, even with patient navigation in place. Individual and neighborhood socioeconomic characteristics affect access to care, quality, and timeliness of care, which consequently affect health outcomes. In this study, we focus on the effects of neighborhood racial composition and poverty on timeliness of diagnostic test in African American women living in relatively poor neighborhoods in Chicago, IL. Purpose: The purpose of this study is to examine the effects of individual and neighborhood characteristics on timely resolution of breast cancer diagnostic tests among African American women who received breast cancer screening and diagnostic tests from three community hospitals in disadvantaged neighborhoods in Chicago. Methods: The analysis utilized a total of 405 African American women who participated in the Patient Navigation in Medically Underserved Areas Project in Chicago. Participating women were recruited from three hospitals. We created an indicator variable for timely diagnostic resolution (completion of follow-up tests within 60 days). We geo-coded participants' home addresses, and calculated distance from home to clinic in miles. We added census tract level data from the American Community Survey 2005-2009, including racial composition and % poverty. In addition, we used Medically Underserved Area (MUA) designation (affluent; MUA designated poor; MUA undesignated poor). Individual characteristics were: age, education, distance to clinic, marital status, and health care distrust. We used Hierarchical Linear Model (HLM) to perform two-level models explaining diagnostic resolution timeliness. Results: The average age of participants was 60 years old. Over 92% completed high school education and 81% lived in MUA designated and undesignated but poor areas (vs. 19% living in affluent areas that are not eligible for MUA). On average, women traveled 5.5 miles to clinics. The mean % whites and % poverty were respectively 11% and 32%, respectively, which differed from overall % whites (32%) and % poverty in Chicago (21%). Women living in areas with a higher % of white residents were more likely to complete diagnostic tests within 60 days, controlling for all other variables. On the other hand, women living in areas with a higher % of African American residents were less likely to have timely diagnostic resolution, controlling for % poverty and all other individual level characteristics. Neighborhood poverty level was not significantly associated with diagnostic test completion. Conclusions: Even though all participants were African American women, living in neighborhoods with a higher proportion of whites was associated with timely diagnostic test resolution. Ethnic minority women seem to benefit from living in more racially integrated neighborhood environment, regardless of the level of poverty or MUA designation. While MUA designation and poverty are known to affect access to care, which is expected to influence timeliness of diagnostic test, racial composition of neighborhoods was shown to have a significant independent effect on timeliness of diagnostic test. The mechanisms of racial residential segregation on timeliness of diagnostic tests need to be further evaluated. Citation Format: Seijeoung Kim, Yamile Molina, Nerida Berriors, Elizabeth Calhoun. Timely breast cancer diagnostic resolution: Effects of individual and neighborhood characteristics. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr B72. doi:10.1158/1538-7755.DISP13-B72

Pregnancy and Birth Outcome Improvements for American Indians in the Healthy Start Project of the Inter-Tribal Council of Michigan, 1998–2008

American Indians living in Michigan experience disproportionately high rates of infant mortality. This 11-year (1998-2008) cohort study evaluated impacts of a Healthy Start (HS) program administered by the Inter-Tribal Council of Michigan (ITCM) on perinatal outcomes. Women who enrolled in ITCM's HS program ("exposed") were compared with non-enrolled ("unexposed") for four outcomes: low birth weight (LBW), small for gestational age, preterm birth, and inadequate prenatal care. To classify exposed and unexposed women and their children, Michigan vital records data were linked with HS enrollment records to identify participants and non-participants among all American Indian births. Logistic regression was used to calculate odds ratios for the four outcomes of interest. Analyses were stratified for high and low access to care based on Medically Underserved Area (MUA) designation for a woman's county of residence. Of 4,149 American Indian births during the period, 872 were to women who enrolled prenatally in HS. Although unstratified analysis showed no differences between HS participants and non-participants, stratified analyses demonstrated that participants from MUA counties had decreased odds of LBW and inadequate prenatal care. Results suggest that in MUA counties where participants and non-participants are at similar risk for poor outcomes, HS may be reducing barriers and improving outcomes. In non-MUA counties participants had similar outcomes as non-participants. These results may reflect a wider disparity in risk factors between the two groups in non-MUA counties. The complex interplay among need, access, and benefit complicates analyses and suggests the importance of more in-depth and focused studies.