Uninsured Residents Research Articles

Digital Reimbursement Systems in a Student-Run Clinic.

The increasing reliance on digital tools for standard healthcare practices in uninsured populations is poorly understood. This study aims to assess the impacts of a newly implemented digital reimbursement system at a student-run primary care clinic associated with an academic medical institution serving uninsured New York City residents. Pharmacy records of 94 unique patients receiving a total of 2770 reimbursements between October 17th, 2016, and May 18th, 2023, were analyzed. Patients were divided into two groups (in-person vs. digital) based on their reimbursement preferences type. Demographic analyses were performed in addition to assessing reimbursement volumes, number of refunds, and duration until receipt of payment for each group. The clinic's total monthly reimbursement volume, number of prescriptions, and number of patients for the period before introduction of digital refunds was compared to the period after. The mean age (in-person = 52.7 ± 14.7 years, digital = 54.9 ± 12.9 years) was not statistically different between the groups. Patients in the digital group requested on average more refunds (digital = 47 refunds, in-person = 14 refunds), received higher total reimbursement amount (digital = $1131.24, in-person = $289.36), and they were reimbursed faster (digital = 56 days, in-person = 62 days). Since the introduction of the digital reimbursement option, our three-month reimbursement volume more than doubled from $481 to $1298. The average number of monthly reimbursements increased from 27 to 45 refunds, and the number of monthly patients increased from 6 to 9 patients. In summary, digital reimbursement options can facilitate medication reimbursement among uninsured patients. These results suggest that digital reimbursement systems result in higher utilization, faster refunds, and larger total reimbursements amount for uninsured and underserved patients.

A Study Examining the Impact of County-Level Demographic, Socioeconomic, and Political Affiliation Characteristics on COVID-19 Vaccination Patterns in Indiana.

The COVID-19 vaccination campaign resulted in uneven vaccine uptake throughout the United States, particularly in rural areas, areas with socially and economically disadvantaged groups, and populations that exhibited vaccine hesitancy behaviors. This study examines how county-level sociodemographic and political affiliation characteristics differentially affected patterns of COVID-19 vaccinations in the state of Indiana every month in 2021. We linked county-level demographics from the 2016-2020 American Community Survey Five-Year Estimates and the Indiana Elections Results Database with county-level COVID-19 vaccination counts from the Indiana State Department of Health. We then created twelve monthly linear regression models to assess which variables were consistently being selected, based on the Akaike Information Criterion (AIC) and adjusted R-squared values. The vaccination models showed a positive association with proportions of Bachelor's degree-holding residents, of 40-59 year-old residents, proportions of Democratic-voting residents, and a negative association with uninsured and unemployed residents, persons living below the poverty line, residents without access to the Internet, and persons of Other Race. Overall, after April, the variables selected were consistent, with the model's high adjusted R2 values for COVID-19 cumulative vaccinations demonstrating that the county sociodemographic and political affiliation characteristics can explain most of the variation in vaccinations. Linking county-level sociodemographic and political affiliation characteristics with Indiana's COVID-19 vaccinations revealed inherent inequalities in vaccine coverage among different sociodemographic groups. Increased vaccine uptake could be improved in the future through targeted messaging, which provides culturally relevant advertising campaigns for groups less likely to receive a vaccine, and increasing access to vaccines for rural, under-resourced, and underserved populations.

“Don't fuss at our staff”: A moral economy of volunteerism in South Carolina safety net clinics

In South Carolina, a state that has foregone Medicaid expansion, working poor residents often rely on safety net clinics for medical care. This care often occurs far from major hospitals, in different, inferior, spaces where limited services are provided in lesser circumstances. The temporary and conditional aid provided in these clinics is meant as a last resort, but often serves as the only source of care for many working poor patients, who must manage the effects of sustained precarity and protracted immiseration with conditional aid provided by volunteers. Here I explore the function that volunteering plays in regulating patients' utilization, and ability to contest, the quality of safety net care. Using ethnographic examples and interview data I show how the needs of patients—referred to in the clinics as “clients”—are managed and contained by a moral economy of volunteer care. These reciprocal obligations of debt and duty preclude working poor patients from making demands of, or lodging complaints against, the free clinics' staff, due to their capacity as volunteers, and leaves the state's safety net effectively unassailable to accusations of inefficacy or neglect. Consequently, patients must defer care, ignore episodes of maltreatment, and ration and share prescription medications, lest they be considered recusant or deemed not sufficiently appreciative of the volunteer staff dedicating their time to them. As a result of this moral economy, the plight of the state's uninsured working poor residents goes under-recognized as the safety net absorbs their cases, hiding the attritional nature of the ostensibly free care they receive and ration.

Hospital- and county-level characteristics explain geographic variability in prices of cancer-related procedures: Implications for policy and interventions.

Healthcare costs in the U.S. are high and variable, which can hinder access and impact health outcomes across communities. This study examined hospital- and county-level characteristics to identify factors that explain geographic variation in prices for four cancer-related procedures. Data sources included Turquoise Health, which compiles publicly-available price data from U.S. hospitals. We examined list prices for four procedures: abdominal ultrasound, diagnostic colonoscopy, brain MRI, and pelvis CT scan, which we linked to characteristics of hospitals (e.g., number of beds) and counties (e.g., metropolitan status). We used multilevel linear regression models to assess multivariable relationships between prices and hospital- and county-level characteristics. Supplementary analyses repeated these models using procedures prices for commercial insurance plans. For each procedure, list prices varied across counties (intraclass correlation: abdominal ultrasound = 23.2%; colonoscopy = 17.1%; brain MRI = 37.2%; pelvis CT = 50.9%). List prices for each procedure were associated with hospital ownership (all p < 0.001) and percent of population without health insurance (all p < 0.05). For example, list prices for abdominal ultrasound were higher for proprietary versus Government-owned hospitals (β = 539.10, 95% confidence interval [CI]: 256.12, 822.08, p < 0.001) and for hospitals in counties with more uninsured residents (β = 23.44, 95% CI: 2.55, 44.33, p = 0.03). Commercial insurance prices were negatively associated with metropolitan status. Prices for cancer-related healthcare procedures varied substantially, with considerable heterogeneity associated with county location as well as county-level social determinants of health (e.g., health insurance coverage). Interventions and policy changes are needed to alleviate the financial burden of cancer care among patients, including geographic variation in prices for cancer-related procedures.

Young, Black/African American, and Latino communities are left behind despite legislative efforts in California to reduce HIV/STI disparities.

Sexually transmitted infections (STI) have been on the rise in the United States with racial/ethnic minority groups, gay and bisexual men, and youth experiencing the highest STI and HIV infection rates. In 2022, California became the first state in the nation to pass legislation, Senate Bill 306 (SB 306), requiring health care plans to cover the costs of home test kits for STIs, including HIV. This study examines provisions within SB 306 and its potential to reduce STI and HIV disparities among key demographic groups and geographic regions within California. Ecological cross-sectional study involving 58 California counties. Descriptive statistics and choropleth maps compared HIV/STI prevalence rates, uninsured rates, demographic composition, and healthcare provider coverage across California counties. Three geographically weighted Poisson regression analyses were conducted to separately examine the association between proportion of uninsured and HIV, gonorrhea, and chlamydia prevalence rates. HIV/STI rates were significantly and positively associated with the proportion of uninsured residents in Central and Southern California counties. These counties had a higher proportion of demographic groups vulnerable to HIV/STI including a large Latino, Black/African American, and younger (age 15-24) population but had a lower rate of healthcare providers with prescription authority for home testing kits, which is a requirement under SB 306. Cutting-edge solutions are needed to stem the rising tide of new STI and HIV infections. While SB 306 is novel and innovative in intent, its coverage gaps will increase disparities and inequities among historically underserved populations.

Creating and Activating an Implementation Community to Drive HPV Vaccine Uptake in Texas: The Role of an NCI-Designated Cancer Center.

The University of Texas MD Anderson Cancer Center, a comprehensive cancer center designated by the National Cancer Institute (NCI), defines its service population area as the State of Texas (29.1 M), the second most populous state in the country and the state with the greatest number of uninsured residents in the United States. Consistent with a novel and formal commitment to prevention as part of its core mission, alongside clear opportunities in Texas to drive vaccine uptake, MD Anderson assembled a transdisciplinary team to develop an institutional Framework to increase adolescent HPV vaccination and reduce HPV-related cancer burden. The Framework was developed and activated through a four-phase approach aligned with the NCI Cancer Center Support Grant Community Outreach and Engagement component. MD Anderson identified collaborators through data-driven outreach and constructed a portfolio of collaborative multi-sector initiatives through review processes designed to assess readiness, impact and sustainability. The result is an implementation community of 78 institutions collaboratively implementing 12 initiatives within a shared measurement framework impacting 18 counties. This paper describes a structured and rigorous process to set up the implementation of a multi-year investment in evidence-based strategies to increase HPV vaccination that solves challenges preventing implementation of recommended strategies and to encourage similar initiative replication.

Defining Vascular Deserts to Describe Access to Care and Identify Sites for Targeted Limb Preservation Outreach

Access to care plays a critical role in limb salvage in chronic limb-threatening ischemia (CLTI). A "medical desert" describes a community lacking access to medical necessities, resulting in increased morbidity and mortality. We sought to describe vascular deserts, which we defined as regions with decreased access to specialty care. All California providers performing vascular surgery procedures were identified through online provider and health care facility searches. Facility participation in the Society for Vascular Surgery (SVS) Vascular Quality Initiative (VQI) lower extremity bypass (LEB) and peripheral vascular intervention (PVI) modules was also determined. Addresses were geocoded with a 30-mile surrounding buffer using ArcGIS (Geographic information systems), creating maps based on care type, including all providers performing vascular procedures, board-certified vascular surgeons, and facilities participating in VQI modules. Public census data overlayed on the maps demonstrated population composition in desert versus nondesert regions. Subsequently, data from the Healthy Places Index (HPI) was overlayed, providing data regarding 25 social factors, comprising an overall HPI score and percent, with lower scores corresponding to poorer health and outcomes. Maps depicting care regions demonstrated decreased provider coverage with increasing specialty care, with the VQI provider map showing the most prominent "desert" regions. When comparing nondesert versus desert regions by care type, demographics including race, the percentage of the population 200% below the poverty line, and the rate of uninsured residents were described. Social determinants of health were then described for desert and nondesert regions by care type, including the HPI percentage and specific domain factors. The percentage of uninsured residents was significant only in the desert and nondesert areas served by board-certified vascular surgeons (19.6 vs. 16.8%, P<0.001). The mean HPI percentile was significantly lower in board-certified provider and VQI facility deserts than nondeserts (50.48% vs. 40.65%, P<0.001 and 52.68% vs. 43.12%, P<0.001, respectively). The economic and education factor percentiles were significantly lower in all desert populations, while the housing, social, and pollution factors were significantly higher in nondesert regions. Health care access, transportation, and neighborhood factor percentiles were significantly lower in board-certified and VQI facility deserts than in the nondesert areas. Access to vascular care plays a significant role in limb salvage. Through mapping vascular deserts, patient demographics, and social factors in desert regions are better understood, and areas that would benefit most from targeted outreach and limb preservation programs for CLTI are identified.

Explaining the higher COVID-19 mortality rates among disproportionately Black counties: A decomposition analysis

BackgroundWhy is COVID-19 mortality higher in counties with a disproportionately large (>13.4%) share of Black residents (hereafter “Black counties”) relative to others (“non-Black counties”)? Existing literature points to six categories of determinants: (1) social distancing, (2) COVID-19 testing, (3) socioeconomic characteristics, (4) environmental characteristics, (5) prevalence of (pre-existing) chronic health conditions, and (6) demographic characteristics. The relative importance of these determinants has not yet been thoroughly examined. MethodsWe built a dataset consisting of 21 sub-indicators across the six categories of determinants for 3108 US counties and their COVID-19 mortality over the period of January 22, 2020–December 31, 2020. Applying the Gelbach's decomposition, we quantified which determinants were most (or least) associated with the COVID-19 mortality disparity between Black and non-Black counties. ResultsWe find that COVID-19 death rates were 26 percent higher in Black counties compared to non-Black counties. This disparity was almost completely explained by the six categories of determinants included in our model. Decomposition analyses indicate that county-level demographic and population health characteristics explained most of this disparity. Among all sub-indicators considered, the greater proportion of females and smaller proportion of rural residents in Black counties were the two largest contributors to the COVID-19 mortality gap between Black and non-Black counties. Proportions of diabetic residents, uninsured residents, and the degree of income inequality also significantly contributed to the gap in COVID-19 mortality. ConclusionThe COVID-19 mortality gap between Black and non-Black counties was largely explained by pre-pandemic differences in demographic and population health characteristics. Policies aiming to reduce the prevalence of chronic conditions and uninsured residents in Black counties would have helped narrow the COVID-19 mortality gap between Black and non-Black counties in 2020.

Population and Neighborhood Correlates of Cannabis Dispensary Locations in Oklahoma.

Cannabis dispensaries have proliferated exponentially in Oklahoma since the state legalized medical cannabis in 2018. Oklahoma is unique from many other legalized states given its high number of lower income, rural, and uninsured residents, who may seek medical cannabis as an alternative to traditional medical treatment. This study examined demographic and neighborhood characteristics associated with dispensary density (n = 1,046 census tracts) in Oklahoma. Compared to census tracts with no dispensaries, those with at least one dispensary had a higher proportion of uninsured individuals living below the poverty level and a greater number of hospitals and pharmacies. Almost half (42.35%) of census tracts with at least one dispensary were classified as a rural locale. In fully adjusted models, percent uninsured, percent of household rentals, and the number of schools and pharmacies were positively associated with greater number of cannabis dispensaries, while the number of hospitals was negatively associated. In the best fitting interaction models, dispensaries were predominant in areas with a higher percentage of uninsured residents and no pharmacies, suggesting that cannabis retailers may capitalize on the health needs of communities with limited healthcare outlets or access to medical treatment. Policies and regulatory actions that seek to decrease disparities in dispensary locations should be considered. Future studies should examine whether people living in communities with a scarcity of health resources are more likely to associate cannabis with medical uses than those living in communities with more resources.

Community Health, Health Care Access, And COVID-19 Booster Uptake In Massachusetts

Booster vaccination offers vital protection against COVID-19, particularly for communities in which many people have chronic conditions. Although vaccination has been widely and freely available, people who have experienced barriers to care might be deterred from being vaccinated. We examined the relationship between COVID-19 booster uptake and small area-level demographics, chronic disease prevalence, and measures of health care access in 462 Massachusetts communities during the period September 2021-April 2022. Unadjusted analyses found that booster uptake was higher in older and wealthier areas, lower in areas with more Hispanic and Black residents, and lower in areas with a high prevalence of chronic conditions. In both unadjusted and adjusted analyses, uptake was lower in communities with more uninsured residents and those in which fewer residents received routine medical check-ups. Adjusted analyses found that areas with more vaccine providers and primary care physicians had higher booster uptake, but this association was not significant in unadjusted analyses. Results suggest a need for innovative outreach efforts, as well as structural changes such as expansion of health care coverage and universal access to care to mitigate the inequitable burden of COVID-19.

1026. What Proportion of Infectious Diseases Physicians Have Buprenorphine Waivers to Treat Opioid Use Disorder in the United States?

Abstract Background Since the onset of the COVID-19 pandemic, opioid-related overdose deaths have increased. Buprenorphine, a medication for opioid use disorder (OUD), is safe and effective but is underutilized and requires qualifying physicians to obtain a waiver. Infectious diseases (ID) physicians are uniquely positioned to treat OUD, as persons with OUD may present with infectious complications from injection drug use. We sought to understand the proportion and distribution of ID physicians with waivers in the United States (US). Methods This was a cross-sectional study merging data from the Centers for Medicare &amp; Medicaid Services and the Drug Enforcement Agency Substance Abuse and Mental Health Services Agency. Our primary outcome was proportion of ID physicians who possess buprenorphine waivers. We used multivariable regression models to identify individual and county-level characteristics associated with buprenorphine waiver possession. We used geospatial analysis to describe county-level distribution of buprenorphine-waivered ID physicians. Results Among 6439 ID physicians in the US, 170 (2.6%) possessed buprenorphine waivers. Overall, 57.2% of ID physicians were male with a median 23 (IQR 15-33) years since medical school. Most (97.3%) practiced in metropolitan counties. In multivariable analysis, medical school graduation beyond 20 years was associated with lower odds of waiver possession compared to those graduating within 20 years (OR 0.59, 95% CI 0.43-0.80). ID physicians practicing in counties with median income &amp;gt; 50,000/year and in counties with higher proportion of uninsured residents also had lower odds of having a waiver (OR 0.58, 95% CI 0.35-0.97; OR 0.93, 95% CI 0.90-0.97). Among counties with at least one ID physician (n=519), 86.6% had no buprenorphine-waivered ID physicians (Figure 1). Figure 1County-Level Distribution of Infectious Diseases Physicians with Buprenorphine Waivers Conclusion Fewer than 3% of ID physicians in the US have obtained waivers to prescribe buprenorphine, highlighting missed opportunities to treat individuals with OUD, especially in rural America. Education on OUD management should be integrated into ID continuing medical education, and policies are urgently needed to expand buprenorphine access to persons without insurance. Disclosures All Authors: No reported disclosures.

Community sociodemographics and rural hospital survival.

To determine whether community sociodemographic factors are associated with the survival or closure of rural hospitals at risk of financial distress between 2010 and 2019. We use a national sample of 985 rural hospitals at risk of financial distress to analyze the relationship between community sociodemographic characteristics and hospital survival or closure. We control for financial distress using the Financial Distress Index developed by the Sheps Center for Health Services Research. Community characteristics are retrieved from the Census and the Robert Wood Johnson Foundation. We first use Wilcoxon rank-sum tests to demonstrate annual sociodemographic differences between rural communities with financially distressed hospitals that closed between 2010 and 2019, and those that remained open. Multilevel Weibull proportional hazards regressions then uncover which sociodemographic factors are significantly associated with survival. Our initial results confirm that closures of rural hospitals at risk of financial distress disproportionately affect communities with certain sociodemographic characteristics. However, most of these characteristics are not associated with higher rates of closure in the multivariate survival analysis. The final results suggest that financially distressed hospitals are more likely to experience closure if their communities have higher rates of unemployment (Hazard Ratio = 1.36, P < .05) or uninsured residents under 65 (Hazard Ratio = 1.13, P < .05). Among financially distressed rural hospitals, specific community-level sociodemographic characteristics (unemployment and uninsurance rates) are positively associated with the likelihood of closure. Social policies addressing these issues should emphasize their broader relationship with the local health sector.

Patient Accessibility to Eye Care in the United States

The United States (US) federal government uses health provider shortage areas (HPSAs) to define patient accessibility to primary care physicians. It is unclear whether HPSAs can be applied to eye care providers (ECPs). Our study determined the applicability of federal HPSA designations to ECP availability in the US. Cross-sectional study. US general population and ophthalmologists/optometrists in the Medicare database. The primary care HPSA score, visual impairment prevalence, and ECP location were determined for each census tract or county using data from the US Department of Health and Human Services, the Centers for Disease Control and Prevention, and Centers for Medicare and Medicaid Services. Association of HPSA with vision loss and ECP density was examined. The 2-step floating catchment area approach was used to newly define eye care shortage areas (patient accessibility score [PAS], higher being worse accessibility) for every county in the US, by weighting the 2-step FCA scores by prevalence of vision loss and ECP density. Multivariable logistic regression was used to identify sociodemographic variables associated with areas of ECP shortage. Among 72 735 census tracts included, statistically significant but weak correlations of HPSA scorewith visual impairment (VI) (r= 0.38; P < 0.0001) and ECP density per county population (r= -0.18; P < 0.0001) werefound. Only 54.0% of census tracts with < 25th percentile ECP density per county were HPSAs (P < 0.0001). Of census tracts > than 75th percentile for VI only 58.0% were HPSAs (P < 0.0001). Multivariable regression found a higher odds of ECP PAS ≥ 75th percentile (worseaccessibility) in rural counties (adjusted odds ratio [aOR], 2.47; 95% confidence interval [CI], 1.93-3.67; P< 0.001) and counties with a greater prevalence of residents with less than a high school education (aOR, 1.21; 95% CI, 1.19-1.25; P < 0.001), residents ≥ 65 years of age (aOR, 1.10; 95% CI, 1.07-1.13; P < 0.001), and uninsured residents (aOR, 1.04; 95% CI, 1.01-1.06; P < 0.001). Counties with a greater proportion of men (aOR, 0.93; 95% CI, 0.89-0.967; P < 0.001) or White residents (aOR, 0.99; 95% CI, 0.98-0.99) had a lower odds of ECP PAS ≥ 75th percentile. Current HPSAs only weakly correlate with ECP supply. We propose a new approach to identify counties with high need but limited access to eye care. Proprietary or commercial disclosure may be found after the references.

Prevalence, Distribution, and Characteristics Associated With Possession of Buprenorphine Waivers Among Infectious Diseases Physicians in the United States.

Persons with opioid use disorder (OUD) may present with infectious complications from injection drug use; thus, infectious diseases (ID) physicians are uniquely positioned to treat OUD. Buprenorphine is safe and effective for OUD but remains underutilized. The prevalence and geographic distribution of ID physicians who are waivered to prescribe buprenorphine are unknown. This cross-sectional study merged data from several publicly available datasets from 1 November 2021 to 15 January 2022. Our primary outcome was the proportion of ID physicians possessing buprenorphine waivers in the United States. We identified individual- and county-level characteristics associated with buprenorphine waiver possession. We then used geospatial analysis to determine the geographic distribution of waivered ID physicians. We identified 6372 ID physicians in the United States, among whom 170 (2.7%) possessed waivers. Most ID physicians (97.3%) practiced in metropolitan counties. In our multivariable analysis, ID physicians had lower odds of having a waiver for every 10-year increase since graduating medical school (OR: .79; 95% CI: .68-.91). ID physicians practicing in counties with a higher proportion of uninsured residents had lower odds of having a waiver (OR: .75; 95% CI: .62-.90). Among counties with ≥1 ID physician (n = 729), only 11.2% had ≥1 waivered ID physician. We found an extremely low prevalence and skewed geographic distribution of ID physicians with buprenorphine waivers. Our findings suggest an urgent need to increase the workforce of ID physicians waivered to prescribe buprenorphine and a call for increased integration of OUD education into ID training and continuing medical education.

Designing an Interprofessional, Student-Led Clinic with the Patient-Centered Medical Home (PCMH) Model

Students and faculty at the University of Texas Medical Branch (UTMB) embarked on the novel undertaking of establishing a comprehensive, interprofessional clinic treating underserved, uninsured residents of Galveston County, Texas, and the surrounding area, modeled after the patient-centered medical home (PCMH). The need for such a community clinic is evident in relevant literature and patients’ suggestions, in addition to local demographic data. The comprehensive nature of this approach to clinic design is apparent in the intricate planning and documents produced by the steering committee, which outline a unique operational structure that optimizes clinic flow. This paper describes the planning, implementation, and future directions of an interprofessional, student-led free clinic operating under the PCMH model that offers a framework for other clinics.

Undergraduate Vaccine Hesitancy and the Influence of "Home" Locales.

In the US, the COVID-19 pandemic has exposed deeply rooted resistance to public health. This has important consequences for SARS-CoV-2 variant spread and for future uptake of influenza and other vaccines. We examine these phenomena in Missouri, where its low vaccination rates, high levels of uninsured residents, predominance of conservative values, and stark rural-urban divides are intricately connected to public health resistance. The Socio-Ecological model guides our approach. We use data from the Fall 2020 Midwestern University (MWU-a pseudonym) Study of Seropositivity and Risk for SARS-CoV-2 and COVID-19 which are harmonized with the American Community Survey, Missouri County-Level Study, and the USDA Rural-Urban Continuum Codes to estimate multi-level regression models on the relationship between undergraduate students' "home" locales and their own COVID-19 and influenza vaccine hesitancy. The availability of primary care physicians, the prevalence of influenza vaccinations, and location type at the county level, as well as the percentage of residents without health insurance at the zip code level differentially predict COVID-19 and influenza vaccine hesitancy. There is a link between county-level health and geographic characteristics, and individuals'-who were influenced by those counties because that is where their parents live-hesitancy towards vaccines. Identifying feasible, precise, local solutions to reducing vaccine hesitancy could take place if community members and other stakeholders would be open to changes in local-level health policy or practice.

Patterns of venous thromboembolism risk, treatment, and outcomes among patients with cancer from uninsured and vulnerable populations.

The epidemiology of cancer-associated thrombosis (CAT) among uninsured and vulnerable populations in the US is not well-characterized. We performed a retrospective cohort study for patients with newly diagnosed cancer from 2011 to 2020 at Harris Health System, which cares for uninsured residents in the Houston metropolitan area. Patient demographics, NCI comorbidity index, area of deprivation index (ADI), cancer histology, staging, and systemic therapy data were extracted. CAT included overall venous thromboembolism (VTE) or pulmonary embolism +/- lower extremity deep vein thrombosis (PE/LE-DVT) within 1 year of diagnosis. We used multivariable Fine-Gray models to assess the associations with CAT accounting for death as a competing risk. Among 15 342 patients, 74% were uninsured and 84% lived in socioeconomically disadvantaged neighborhoods. There were 16% Non-Hispanic White (NHW), 28% Non-Hispanic Black (NHB), 50% Hispanic (27% Mexican), and 6% Asian/Pacific Islanders (API). The 1-year CAT incidence rate was 14.6%. Overall VTE was lower for Hispanics versus NHW (SHR 0.87 [0.76-0.99]) and API versus NHW (SHR 0.58 [0.44-0.77]). PE/LE-DVT was higher for NHB versus NHW (SHR 1.18 [1.01-1.39]). CAT was also associated with chemotherapy-based regimens (+/- immunotherapy), age, obesity, cancer type/staging, VTE history, and recent hospitalization. NCI comorbidity and ADI scores were associated with mortality but not CAT. In a large cohort of underserved patients with cancer, we identified an elevated incidence of CAT with known and novel risk predictors. Hispanics had lower adjusted rates of CAT and mortality. Our findings highlight the need to investigate and incorporate vulnerable populations in clinical trials.

Geographic access to federally qualified health centers before and after the affordable care act

BackgroundThe Affordable Care Act (ACA) increased funding for Federally Qualified Health Centers (FQHCs). We defined FQHC service areas based on patient use and examined the characteristics of areas that gained FQHC access post-ACA.MethodsWe defined FQHC service areas using total patient counts by ZIP code from the Uniform Data System (UDS) and compared this approach with existing methods. We then compared the characteristics of ZIP codes included in Medically Underserved Areas/Populations (MUA/Ps) that gained access vs. MUA/P ZIP codes that did not gain access to FQHCs between 2011–15.ResultsFQHC service areas based on UDS data vs. Primary Care Service Areas or counties included a higher percentage of each FQHC’s patients (86% vs. 49% and 71%) and ZIP codes with greater use of FQHCs among low-income residents (29% vs. 22% and 22%), on average. MUA/Ps that gained FQHC access 2011–2015 included more poor, uninsured, publicly insured, and foreign-born residents than underserved areas that did not gain access, but were less likely to be rural (p < .05).ConclusionsMeasures of actual patient use provide a promising method of assessing FQHC service areas and access. Post-ACA funding, the FQHC program expanded access into areas that were more likely to have higher rates of poverty and uninsurance, which could help address disparities in access to care. Rural areas were less likely to gain access to FQHCs, underscoring the persistent challenges of providing care in these areas.

Socioeconomic Determinants of COVID-19 Incidence and Mortality in Florida.

A wide variety of social determinants of health have been associated with various risks and impacts on quality of life. Specifically, poverty, lack of insurance coverage, large household sizes, and social vulnerability are all factors implicated in incidence and mortality rates of infectious disease. However, no studies have examined the relationship of these factors to the COVID-19 pandemic on a state-wide level in Florida. Thereby, the objective of this study is to examine the relationship between average household size, poverty, uninsured populations, social vulnerability index (SVI), and rates of COVID-19 cases and deaths in Florida counties.The objective was accomplished by analyzing the cumulative case and death reports from state and local health departments in Florida. The data was compiled into a single dataset by the CDC COVID-19 Task Force. Using US Census Bureau data, all Florida counties were classified into tertiles of the separate categories of poverty rate, average household size, uninsured rates, and SVI (Social Vulnerability Index). The poverty level was classified as low (0-12.3%), moderate (12.3-17.3%), and high (>17.3% below the federal poverty line). The uninsured population proportion was classified as low (0-7.1%), moderate (7.1-11.4%), and high (>11.4% uninsured residents). Average county household size was classified as low (0-2.4), moderate (2.4-2.6), and high (>2.6). The Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI) used US census data on 15 social determinants of vulnerability to evaluate and assist disadvantaged communities. SVI tertiles were low (0-0.333), moderate (0.334-0.666), and high (0.667-1) on a range of 0-1, with higher numbers signifying communities with many factors of social vulnerability. The mean cumulative cases and deaths per 100,000 inhabitants were calculated in each tertile for each category.Analysis of the data revealed that case and mortality rates due to COVID-19 in the high poverty counties were markedly higher in Florida than the national average. In contrast, moderate and low poverty rates were below average. Similarly, counties with a high SVI had case and mortality rates greatly above state and national averages. Counties with a high proportion of uninsured displayed the highest case rates. However, mortality rates were the highest in counties with a low proportion of uninsured individuals. No clear correlation was observed between COVID-19 rates and household size.It was concluded that compiled CDC and US census data suggests a significant correlation between poverty, social vulnerability, lack of insurance coverage, and increased incidence and mortality from COVID-19. Future research should statistically analyze the correlations and examine the individual factors of SVI as potential COVID-19 predictors.

How Do Housing Prices Affect Residents' Health? New Evidence From China.

This paper aims to explore the effect and mechanism of rising housing prices on residents' physical and mental health. Using data from the China Family Panel Studies from 2014 to 2018, we investigate the impact and mechanism of rising housing prices on the mental and physical health of urban residents through multiple grouping regression and analysis of variance. The study finds that overall, rising housing prices have a positive effect on residents' mental health but a negative effect on physical health, and those who do not own a house show the greatest adverse effect. The impact of rising housing prices on health is mainly reflected in three aspects: the wealth effect, cost effect, and comprehensive environmental expectation effect. Of these, the wealth effect and comprehensive environmental expectation effect play a role in promoting residents' health, whereas the cost effect has a strong inhibitory effect. This paper also analyzes how house prices impact health and finds that having health insurance reduces residents' active health behavior, thus affecting their physical and mental health levels, which has a positive effect on uninsured residents.