Geographic access to United States SARS-CoV-2 testing sites highlights healthcare disparities and may bias transmission estimates.
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ABSTRACT:
SUBMITTER: Rader B
PROVIDER: S-EPMC7239151 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Publications
Geographic access to United States SARS-CoV-2 testing sites highlights healthcare disparities and may bias transmission estimates.
Rader Benjamin B Astley Christina M CM Sy Karla Therese L KTL Sewalk Kara K Hswen Yulin Y Brownstein John S JS Kraemer Moritz U G MUG
Journal of travel medicine 20201101 7
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Project description:ObjectiveIt is important to identify gaps in access and reduce health outcome disparities, understanding access to intensive care unit (ICU) beds, especially by race and ethnicity, is crucial. Our objective was to evaluate the race and ethnicity-specific 60-minute drive time accessibility of ICU beds in the United States (US).DesignWe conducted a cross-sectional study using road network analysis to determine the number of ICU beds within a 60-minute drive time, and calculated adult intensive care bed ratios per 100,000 adults. We evaluated the US population at the Census block group level and stratified our analysis by race and ethnicity and by urbanicity. We classified block groups into four access levels: no access (0 adult intensive care beds/100,000 adults), below average access (>0-19.5), average access (19.6-32.0), and above average access (>32.0). We calculated the proportion of adults in each racial and ethnic group within the four access levels.SettingAll 50 US states and the District of Columbia.ParticipantsAdults ≥15 years old.Main outcome measuresAdult intensive care beds/100,000 adults and percentage of adults national and state) within four access levels by race and ethnicity.ResultsHigh variability existed in access to ICU beds by state, and substantial disparities by race and ethnicity. 1.8% (n = 5,038,797) of Americans had no access to an ICU bed, and 26.8% (n = 73,095,752) had below average access, within a 60-minute drive time. Racial and ethnic analysis showed high rates of disparities (no access/below average access): American Indians/Alaskan Native 12.6%/28.5%, Asian 0.7%/23.1%, Black or African American 0.6%/16.5%, Hispanic or Latino 1.4%/23.0%, Native Hawaiian and other Pacific Islander 5.2%/35.0%, and White 2.1%/29.0%. A higher percentage of rural block groups had no (5.2%) or below average access (41.2%), compared to urban block groups (0.2% no access, 26.8% below average access).ConclusionICU bed availability varied substantially by geography, race and ethnicity, and by urbanicity, creating significant disparities in critical care access. The variability in ICU bed access may indicate inequalities in healthcare access overall by limiting resources for the management of critically ill patients.
| S-EPMC10619775 | biostudies-literature
Project description:ObjectiveThe objective of this study is to identify disparities in geographic access to medical oncologists at the time of diagnosis.Data sources/study setting2014-2016 Pennsylvania Cancer Registry (PCR), 2019 CMS Base Provider Enrollment File (BPEF), 2018 CMS Physician Compare, 2010 Rural-Urban Commuting Area Codes (RUCA), and 2015 Area Deprivation Index (ADI).Study designSpatial regressions were used to estimate associations between geographic access to medical oncologists, measured with an enhanced two-step floating catchment area measure, and demographic characteristics.Data collection/extraction methodsMedical oncologists were identified in the 2019 CMS BPEF and merged with the 2018 CMS Physician Compare. Provider addresses were converted to longitude-latitude using OpenCage Geocoder. Newly diagnosed cancer patients in each census tract were identified in the 2014-2016 PCR. Census tracts were classified based on rurality and socioeconomic status using the 2010 RUCA Codes and the 2015 ADI.Principal findingsLarge towns and rural areas were associated with spatial access ratios (SPARs) that were 6.29 lower (95% CI -16.14 to 3.57) and 14.76 lower (95% CI -25.14 to -4.37) respectively relative to urban areas. Being in the fourth ADI quartile (highest disadvantage) was associated with a 12.41 lower SPAR (95% CI -19.50 to -5.33) relative to the first quartile. The observed difference in a census tract's non-White population from the 25th (1.3%) to the 75th percentile (13.7%) was associated with a 13.64 higher SPAR (Coefficient = 1.10, 95% CI 11.89 to 15.29; p < 0.01), roughly equivalent to the disadvantage associated with living in the fourth ADI quartile, where non-White populations are concentrated.ConclusionsRurality and low socioeconomic status were associated with lower geographic access to oncologists. The negative association between area deprivation and geographic access is of similar magnitude to the positive association between larger non-White populations and access. Policies aimed at increasing geographic access to care should be cognizant of both rurality and socioeconomic status.
| S-EPMC9441279 | biostudies-literature
Project description: Not available
| S-EPMC10658202 | biostudies-literature
Project description:Background Exercise-based cardiac rehabilitation (CR) is known to reduce morbidity and mortality for patients with cardiac conditions. Sociodemographic disparities in accessing CR persist and could be related to the distance between where patients live and where CR facilities are located. Our objective is to determine the association between sociodemographic characteristics and geographic proximity to CR facilities. Methods and Results We identified actively operating CR facilities across Los Angeles County and used multivariable Poisson regression to examine the association between sociodemographic characteristics of residential proximity to the nearest CR facility. We also calculated the proportion of residents per area lacking geographic proximity to CR facilities across sociodemographic characteristics, from which we calculated prevalence ratios. We found that racial and ethnic minorities, compared with non-Hispanic White individuals, more frequently live ≥5 miles from a CR facility. The greatest geographic disparity was seen for non-Hispanic Black individuals, with a 2.73 (95% CI, 2.66-2.79) prevalence ratio of living at least 5 miles from a CR facility. Notably, the municipal region with the largest proportion of census tracts comprising mostly non-White residents (those identifying as Hispanic or a race other than White), with median annual household income <$60 000, contained no CR facilities despite ranking among the county's highest in population density. Conclusions Racial, ethnic, and socioeconomic characteristics are significantly associated with lack of geographic proximity to a CR facility. Interventions targeting geographic as well as nongeographic factors may be needed to reduce disparities in access to exercise-based CR programs. Such interventions could increase the potential of CR to benefit patients at high risk for developing adverse cardiovascular outcomes.
| S-EPMC9683686 | biostudies-literature
Project description:ObjectiveTo characterize the quantity and quality of hospital capacity across the United States.Data sourcesWe combine a 2017 near-census of US hospital inpatient discharges from the Healthcare Cost and Utilization Project (HCUP) with American Hospital Association Survey, Hospital Compare, and American Community Survey data.Study designThis study produces local hospital capacity quantity and care quality measures by allocating capacity to zip codes using market shares and population totals. Disparities in these measures are examined by race and ethnicity, income, age, and urbanicity.Data collection/extraction methodsAll data are derived from pre-existing sources. All hospitals and zip codes in states, including the District of Columbia, contributing complete data to HCUP in 2017 are included.Principal findingsNon-Hispanic Black individuals living in zip codes supplied, on average, 0.11 more beds per 1000 population (SE = 0.01) than places where non-Hispanic White individuals live. However, the hospitals supplying this capacity have 0.36 fewer staff per bed (SE = 0.03) and perform worse on many care quality measures. Zip codes in the most urban parts of America have the least hospital capacity (2.11 beds per 1000 persons; SEM = 0.01) from across the rural-urban continuum. While more rural areas have markedly higher capacity levels, urban areas have advantages in staff and capital per bed. We do not find systematic differences in care quality between rural and urban areas.ConclusionsThis study highlights the importance of lower hospital care quality and resource intensity in driving racial and ethnic, as well as income, disparities in hospital care-related outcomes. This study also contributes an alternative approach for measuring local hospital capacity that accounts for cross-hospital service area flows. Adjusting for these flows is necessary to avoid underestimating the supply of capacity in rural areas and overestimating it in places where non-Hispanic Black individuals tend to live.
| S-EPMC9441275 | biostudies-literature
Project description: Not available
| S-EPMC9871799 | biostudies-literature
Project description:Human movement and population connectivity inform infectious disease management. Remote data, particularly mobile phone usage data, are frequently used to track mobility in outbreak response efforts without measuring representation in target populations. Using a detailed interview instrument, we measure population representation in phone ownership, mobility, and access to healthcare in a highly mobile population with low access to health care in Namibia, a middle-income country. We find that 1) phone ownership is both low and biased by gender, 2) phone ownership is correlated with differences in mobility and access to healthcare, and 3) reception is spatially unequal and scarce in non-urban areas. We demonstrate that mobile phone data do not represent the populations and locations that most need public health improvements. Finally, we show that relying on these data to inform public health decisions can be harmful with the potential to magnify health inequities rather than reducing them. To reduce health inequities, it is critical to integrate multiple data streams with measured, non-overlapping biases to ensure data representativeness for vulnerable populations.
| S-EPMC10325035 | biostudies-literature
Project description:Supported by the 10% set-aside funds in the Community Mental Health Block grant, distributed at the state level, coordinated specialty care (CSC) have been widely disseminated throughout the U.S. This study explores variations in the geographical accessibility of CSC programs by neighborhood level characteristics in Washington State. CSC locations were geocoded. Socioeconomic neighborhood deprivation (i.e., Area deprivation index) and rurality (i.e., Rural-Urban Commuting Area codes) were neighborhood level characteristics extracted from the 2018 American Community Survey. Geographic accessibility of CSC was assessed using a two-step floating catchment area technique and multilevel linear models were used to examine the association between specific neighborhood characteristics and geographic accessibility. The association between access and socioeconomically deprived neighborhoods varied differentially by neighborhood rurality (an interaction effect). Model estimates indicated that the least deprived, metropolitan neighborhoods had the best access (M = 0.38; CI: 0.34, 0.42) and rural neighborhoods in the second most deprived quartile had the worst access (M = 0.16; CI: 0.11, 0.21) to CSC. There was a clear decrease in accessibility for more rural neighborhoods, regardless of other neighborhood characteristics. In conclusions, findings provide important insight into how resource distribution contributes to geographic disparities in access to CSC. The use of spatial analytic techniques has the potential to identify specific neighborhoods and populations where there is a need to expand and increase availability of CSC to ensure access to rural and socioeconomically deprived neighborhoods.
| S-EPMC9119810 | biostudies-literature
Project description:ImportanceLiver disease is a leading cause of mortality in the US. Liver transplant can be a lifesaving procedure for patients with severe liver disease.ObjectiveTo assess temporal trends and geographic variance in liver-related mortality (LRM) and liver transplant in the US.Design, setting, and participantsIn this cohort study, the frequencies and geographic variance of LRM in 2018 and 2021 were obtained in a cross-sectional analysis of the Underlying Cause of Death data available on the Centers for Disease Control and Prevention's Epidemiologic Research database. The number of livers donated and transplanted according to the state of residence of each donor and recipient were obtained from the United Network for Organ Sharing.Main outcomes and measuresLiver-related mortality in 2018 and 2021, overall and by state, as well as the liver transplant rate according to state of residence of recipient and donor.ResultsOverall LRM in the US was 93 418 in 2021, with a crude rate of 28.1 per 100 000 individuals, an increase of 19.1% compared with rates seen immediately prior to the COVID-19 pandemic in 2018 (77 282 [23.6 per 100 000 individuals]). Liver-related mortality in 2021 varied several-fold between states, from 18.4 per 100 000 individuals per year in Utah to 65.9 per 100 000 individuals per year in New Mexico. The mean number of liver-related deaths per transplant from all donor sources (in state and out of state) was 7.2 in the lowest LRM quintile compared with 21.5 in the highest (95% CI, 12.1-16.6; SE, 1.1; P < .001). Ten states had no liver transplant center. Paradoxically, residents of states with the highest LRM had a much lower rate of liver transplant (at any location) from organs procured from in-state residents than states with the lowest LRM quintile (13.0% vs 35.2% in-state donors; 95% CI, 14.1%-30.3%; SE, 3.9%; P < .001).Conclusions and relevanceThis study suggests that rates of LRM have increased dramatically since the COVID-19 pandemic and vary several-fold between states. Rates of liver transplant are paradoxically lowest among residents living in states with the highest LRM. These findings highlight apparent geographic disparities in access to liver transplant that allocation policy cannot address.
| S-EPMC11581511 | biostudies-literature
Project description:A study on infertility in China found that while 543 health care institutions are approved for assisted reproductive technology (ART), only 10.1% offer all ART services, with a significant skew toward the eastern regions, highlighting the accessibility challenges faced by rural and remote populations; this study recommends government measures including travel subsidies and education initiatives to improve ART access for economically disadvantaged individuals.
| S-EPMC11208828 | biostudies-literature