Evaluating and Comparing Methods for Measuring Spatial Access to Mammography Centers in Appalachia (Re-Revised)

A Qualitative Exploration of Institutional Betrayals in Rural Communities: An Emerging Typology

To explore individuals' personal narratives of perceived betrayals and injustices committed by institutions, their representatives, or other authority figures and discern in what spheres of life they commonly manifest. 157 adults from largely rural, low-income communities in southern Appalachia participated in semi-structured qualitative interviews that asked them to describe key points in their life experiences, including high points, low points, and turning points. These were reviewed for episodes of institutional betrayals. Interview transcripts were analyzed using a grounded thematic analysis. Participants mentioned numerous instances of betrayals that occurred from interactions with institutions or their representatives. These were grouped into four categories: professional betrayals involving mistreatment from an employer, health care provider, or other authority figure; professional-organizational betrayals where a professional perpetrator was able to get support from a problematic organizational culture; corporate malfeasance involving misdeeds by business entities; and systemic injustices involving the sociopolitical architecture of society. The findings identified a range of institutional betrayal experiences that were unnecessary, unwanted, intentional, and harmful. They could be distinguished by the type of perpetrators and often led to notable harms, including unwanted system involvement and unemployment. Although participants seldom explicitly mentioned the rural setting in their descriptions of institutional betrayal, it is likely that limited options for health care providers, schools, and other institutions exacerbated some harms. Institutional betrayals need to be considered in people's trauma dosage, their cumulative lifetime burden of trauma.

Spatial Accessibility of Primary Care in the Dual Public-Private Health System in Rural Areas, Malaysia

Disparities in access to health services in rural areas represent a global health issue. Various external factors contribute to these disparities and each root requires specific remedial action to alleviate the issue. This study elucidates an approach to assessing the spatial accessibility of primary care, considering Malaysia's dual public-private system specifically in rural areas, and identifies its associated ecological factors. Spatial accessibility was calculated using the Enhance 2-Step Floating Catchment Area (E2SFCA) method, modified as per local context. Data were secondary sourced from Population and Housing Census data and administrative datasets pertaining to health facilities and road network. The spatial pattern of the E2SFCA scores were depicted using Hot spot Analysis. Hierarchical multiple linear regression and geographical weight regression were performed to identify factors that affect E2SFCA scores. Hot spot areas revolved near the urban agglomeration, largely contributed by the private sector. Distance to urban areas, road density, population density dependency ratios and ethnic composition were among the associated factors. Accurate conceptualization and comprehensive assessment of accessibility are crucial for evidence-based decision making by the policymakers and health authorities in identifying areas that need attention for a more specific and localized planning and development.

Spatial access to public hospitals during COVID-19 in Nottinghamshire, UK

We intend to tackle two under-addressed issues in access to healthcare services during the COVID-19 pandemic: first, the spatiotemporal dynamic of access during the pandemic of acute communicable disease; second, the demographic and socioeconomic access disparities. We used the two-step floating catchment area (2SFCA) method to measure the spatial access to public hospitals during the second COVID-19 wave (September 28th-February 28th, 2021) in Nottinghamshire, UK. To investigate the temporal variation in access along with the development of the pandemic, we divided our study period into 11 sections and applied the 2SFCA to each of them. The results indicate that western Nottinghamshire is better than the eastern part from a spatial perspective and the north-western urban area represents the highest spatial access; temporally, the accessibility of the public hospitals generally decreased when the number of cases increased. Particular low accessibility was observed at the beginning of the pandemic when the outbreak hit the university region and its vicinities during the back-to-school season. Our disparity analysis found that i) the access of the senior population to public hospitals deviated from that of the general population, ii) the access was positively associated with socioeconomic status, and iii) all disparities were related to the urban-rural discrepancy. These findings can help to plan temporary clinics or hospitals during epidemic emergencies. More generally, they provide scientific support to pandemic-related healthcare resource allocation and policy- making, particularly for people in vulnerable areas.

Disparities in geographic access to medical oncologists

OBJECTIVE

The objective of this study is to identify disparities in geographic access to medical oncologists at the time of diagnosis.

DATA SOURCES/STUDY SETTING

2014-2016 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 DESIGN

Spatial 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 METHODS

Medical 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 FINDINGS

Large 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.

CONCLUSIONS

Rurality 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.

Challenging terrains: socio-spatial analysis of Primary Health Care Access Disparities in West Virginia

Existing measures of health care access were inadequate for guiding policy decisions in West Virginia, as they identified the entire state as having limited access. To address this, we compiled a comprehensive database of primary health care providers and facilities in the state, developed a modified E2SFCA tool to measure spatial access in the context of West Virginia's rural and mountainous nature, and integrated this with an index of socio-economic barriers to access. The integrated index revealed that the rural areas, especially in the southern part of the state, have especially limited access to primary health care. 1. Introduction. An emerging public health issue which has been exacerbated by the COVID-19 pandemic, is that of healthcare deserts, which are places where basic affordable health care is not accessible for residents. This problem has become worse in rural areas as rural hospitals close. In these areas, including West Virginia, scattered populations suffer from limited access to primary healthcare services. Uneven geographic and socio-economic barriers to accessing primary health care are major contributing factors to these health disparities. West Virginia's unique rural and mountainous settlement patterns, aging population, and economic crisis over the past two decades have resulted in unequal access to the primary healthcare services for its residents. The rural nature of the state makes it difficult to maintain medical facilities accessible to much of the population, especially as rural hospitals have been closing, such as the one in Williamson, WV (Jarvie, 2020). The mountainous terrain slows down travel across winding roads, lengthening travel times to the nearest hospital, while an aging population has increased health care needs. Lastly, an economic crisis and higher poverty rate makes West Virginians less able to pay for health care. As a result, West Virginians are confronting a health crisis. According to a recent report by the West Virginia Health Statistics Center (2019), West Virginians rank first in the country for heart attacks, have the second-highest obesity rate and prevalence of mental health problems in the country, along with the fourth-highest rate of diabetes and fifth-highest rate of cancer. An issue faced by West Virginia's policymakers is the limitations of tools for identifying and assessing healthcare deserts, as they are poorly suited for the unique challenges in West Virginia. Academic research has not analyzed comprehensive primary healthcare accessibility in WV, although previous studies have focused on Appalachia (e.g., Behringer & Friedell 2006; Smith & Holloman, 2011; Elnicki et al., 1995; Donohoe et al., 2015, 2016a, 2016b), and others focus on access to more specialized services (Valvi et al., 2019; Donohoe, 2016a). Existing approaches to identify the healthcare deprived areas, such as Health Professional Shortage Areas (HPSA), are not suitable for guiding West Virginia policies, because every one of the 55 counties within the state has several HPSAs, which makes prioritizing resources difficult. The lack of easily accessible, comprehensive, and up-to-date physician and healthcare facility database creates additional difficulties. Physician license datasets were found to often include inconsistent, misleading, and out-of-date information. The last limitation of the HPSA designation is that it is based on zip code areas and census tracts, which are not ideal as zip code areas lack spatial context and much covariate data, while rural census tracts are too large to capture spatial variation of access. In this context, the WV HealthLink project was begun with joint effort with WV Rural Health Initiative (RHI) to fill gaps in research and support decision making for primary healthcare access in West Virginia. The goals of the projects are: (1) to help West Virginia's three medical schools provide specialized professional training in rural healthcare; (2) to address health disparities by investing in clinical projects in underserved areas; and (3) to retain health professionals in WV. In 2018, to support these goals, HealthLink was invited by the RHI's leadership to analyze disparities in primary health care access in West Virginia and develop tools for rural healthcare decision-making. These goals also create a comprehensive and up-to-date physician and facility database, new analysis tools, and new visualization tools for decision support. The goals of this paper are to assess the spatial and social accessibility of primary health care in West Virginia, and to understand spatial and social determinants that shape this access. To achieve these goals, this paper completes the following objectives: (1) define primary healthcare and access; (2) build an extensive and up-to-date primary healthcare database; (3) develop an assessment framework for WV; and (4) visualize the results for policy makers and practitioners. The structure of this paper is as follows. First, we describe three methodological problems encountered as we define primary health care access. Second, we present the methods used to resolve these problems, and conclude by presenting our modified enhanced two-step floating catchment area (E2FCA hereafter) approach and its results for WV. Our foci in this modification were improving the accuracy of the analysis regarding measuring distance, considering distance decay effect, and more precisely representing the location of supply and demand.

Epidemiological characteristics of mumps from 2004 to 2020 in Jiangsu, China: a flexible spatial and spatiotemporal analysis

The mumps resurgence has frequently been reported around the world in recent years, especially in many counties mumps vaccines have been widely used. This study aimed to describe the spatial epidemiological characteristics of mumps in Jiangsu, and provide a scientific basis for the implementation and adjustment of strategies to prevent and control mumps. The epidemiological characteristics were described with ratio or proportion. Spatial autocorrelation, Tango's flexible spatial scan statistics, and Kulldorff's elliptic spatiotemporal scan statistics were applied to identify the spatial autocorrelation, detect hot and cold spots of mumps incidence, and aggregation areas. A total of 172 775 cases were reported from 2004 to 2020 in Jiangsu. The general trend of mumps incidence is declining with a bimodal seasonal distribution identified mainly in summer and winter, respectively. Children aged 5–10 years old are the main risk group. A migration trend of hot spots from southeast to northwest over time was found. Similar high-risk aggregations were detected in the northwestern parts through spatial-temporal analysis with the most likely cluster time frame around 2019. Local medical and health administrations should formulate and implement targeted health care policies and allocate health resources more appropriately corresponding to the epidemiological characteristics of mumps.

Using GIS to Understand the Influence of Hurricane Harvey on Spatial Access to Primary Care

Hurricanes can have a significant impact on the functioning and capacity of healthcare systems. However, little work has been done to understand the extent to which hurricanes influence local residents' spatial access to healthcare. Our study evaluates the change in spatial access to primary care physicians (PCPs) between 2016 and 2018 (i.e., before and after Hurricane Harvey) in Harris County, Texas. We used an enhanced 2-step floating catchment area (E2SFCA) method to measure spatial access to PCPs at the census tract level. The results show that, despite an increased supply of PCPs across the county, most census tracts, especially those in the northern and eastern fringe areas, experienced decreased access during this period as measured by the spatial access ratio (SPAR). We explain this decline in SPAR by the shift in the spatial distribution of PCPs to the central areas of Harris County from the fringe areas after Harvey. We also examined the socio-demographic impact in the SPAR change and found little variation in change among different socio-demographic groups. Therefore, public health professionals and disaster managers may use our spatial access measure to highlight the geographic disparities in healthcare systems. In addition, we recommend considering other social and institutional dimensions of access, such as users' needs, preferences, resource capacity, mobility options, and quality of healthcare services, in building a resilient and inclusive post-hurricane healthcare system.

National optimisation of accessibility to emergency obstetrical and neonatal care in Togo: a geospatial analysis

OBJECTIVES

Improving access to emergency obstetrical and neonatal care (EmONC) is a key strategy for reducing maternal and neonatal mortality. Access is shaped by several factors, including service availability and geographical accessibility. In 2013, the Ministry of Health (MoH) of Togo used service availability and other criteria to designate particular facilities as EmONC facilities, facilitating efficient allocation of limited resources. In 2018, the MoH further revised and rationalised this health facility network by applying an innovative methodology using health facility characteristics and geographical accessibility modelling to optimise timely access to EmONC services. This study compares the geographical accessibility of the network established in 2013 and the smaller network developed in 2018.

DESIGN

We used data regarding travel modes and speeds, geographical barriers and topographical and urban constraints, to estimate travel times to the nearest EmONC facilities. We compared the EmONC network of 109 facilities established in 2013 with the one composed of 73 facilities established in 2018, using three travel scenarios (walking and motorised, motorcycle-taxi and walking-only).

RESULTS

When walking and motorised travel is considered, the 2013 EmONC network covers 81% and 96.6% of the population at the 1-hour and 2-hour limit, respectively. These figures are slightly higher when motorcycle-taxis are considered (82.8% and 98%), and decreased to 34.7% and 52.3% for the walking-only scenario. The 2018 prioritised EmONC network covers 78.3% (1-hour) and 95.5% (2-hour) of the population for the walking and motorised scenario.

CONCLUSIONS

By factoring in geographical accessibility modelling to our iterative EmONC prioritisation process, the MoH was able to decrease the designated number of EmONC facilities in Togo by about 30%, while still ensuring that a high proportion of the population has timely access to these services. However, the physical access to EmONC for women unable to afford motorised transport remains inequitable.

Assessing consistency among indices to measure socioeconomic barriers to health care access

Many places within rural America lack ready access to health care facilities. Barriers to access can be both spatial and non-spatial. Measurements of spatial access, such as the Enhanced Floating 2-Step Catchment Area and other floating catchment area measures, produce similar patterns of access. However, the extent to which different measurements of socioeconomic barriers to access correspond with each other has not been examined. Using West Virginia as a case study, we compute indices based upon the literature and measure the correlations among them. We find that all indices positively correlate with each other, although the strength of the correlation varies. Also, while there is broad agreement in the general spatial trends, such as fewer barriers in urban areas, and more barriers in the impoverished southwestern portion of the state, there are regions within the state that have more disagreement among the indices. These indices are to be used to support decision-making with respect to placement of rural residency students from medical schools within West Virginia to provide students with educational experiences as well as address health care inequalities within the state. The results indicate that for decisions and policies that address statewide trends, the choice of metric is not critical. However, when the decisions involve specific locations for receiving rural residents or opening clinics, the results can become more sensitive to the selection of the index. Therefore, for fine-grained policy decision-making, it is important that the chosen index best represents the processes under consideration.

A comparison of methods for measuring spatial access to health care

OBJECTIVE

To compare measures of spatial access to care commonly used by policy makers and researchers with the more comprehensive enhanced two-step floating catchment area (E2SFCA) method.

STUDY SETTING

Fourteen southwestern Pennsylvania counties.

STUDY DESIGN

We estimated spatial access to buprenorphine-waivered prescribers using three commonly used measures-Euclidean travel distance to the closest prescriber, travel time to the closest provider, and provider-to-population ratios-and the E2SFCA. Unlike other measures, the E2SFCA captures provider capacity, potential patient volume, and travel time to prescribers.

DATA COLLECTION/EXTRACTION METHODS

We measured provider capacity as the number of buprenorphine prescribers listed at a given address in the Drug Enforcement Agency's 2020 Controlled Substances Act Registrants Database, and we measured potential patient volume as the number of nonelderly adults in a given census tract as reported by the 2018 American Community Survey. We estimated travel times between potential patients and prescribers with Bing Maps and Mapbox application programming interfaces. We then calculated each spatial access measure using the R programming language. We used each measure of spatial access to identify census tracts in the lowest quintile of spatial access to prescribers.

PRINCIPAL FINDINGS

The Euclidean distance, travel time, and provider-to-population ratio measures identified 48.3%, 47.2%, and 69.9% of the census tracts that the E2SFCA measure identified as being in the lowest quintile of spatial access to care, meaning that these measures misclassify 30%-52% of study area census tracts as having sufficient spatial access to buprenorphine prescribers.

CONCLUSIONS

Measures of spatial access commonly used by policy makers do not sufficiently accurately identify geographic areas with relatively low access to prescribers of buprenorphine. Using the E2SFCA in addition to the commonly used measures would allow policy makers to precisely target interventions to increase spatial access to opioid use disorder treatment and other types of health care services.

Spatial accessibility assessment of COVID-19 patients to healthcare facilities: A case study of Florida

During the COVID-19 pandemic, healthcare facilities worldwide have been overwhelmed by the amount of coronavirus patients needed to be served. Similarly, the U.S. also experienced a shortage of healthcare resources, which led to a reduction in the efficiency of the whole healthcare system. In order to evaluate this from a transportation perspective, it is critical to understand the extent to which healthcare facilities with intensive care unit (ICU) beds are available in both urban and rural areas. As such, this study aims to assess the spatial accessibility of COVID-19 patients to healthcare facilities in the State of Florida. For this purpose, two methods were used: the two-step floating catchment area (2SFCA) and the enhanced two-step floating catchment area (E2SFCA). These methods were applied to identify the high and low access areas in the entire state. Furthermore, a metric, namely the Accessibility Ratio Difference (ARD), was developed to evaluate the spatial access difference between the models. Results revealed that many areas in the northwest and southern Florida have lower access compared to other locations. The residents in central Florida (e.g., Tampa and Orlando cities) had the highest level of accessibility given their higher access ratios. We also observed that the 2SFCA method overestimates the accessibility in the areas with a lower number of ICU beds due to the "equal access" assumption of the population within the catchment area. The findings of this study can provide valuable insights and information for state officials and decision makers in the field of public health.

Mapping the Accessibility of Medical Facilities of Wuhan during the COVID-19 Pandemic

In December 2019, the coronavirus disease 2019 (COVID-19) pandemic attacked Wuhan, China. The city government soon strictly locked down the city, implemented a hierarchical diagnosis and treatment system, and took a series of unprecedented pharmaceutical and non-pharmaceutical measures. The residents’ access to the medical resources and the consequently potential demand–supply tension may determine effective diagnosis and treatment, for which travel distance and time are key indicators. Using the Application Programming Interface (API) of Baidu Map, we estimated the travel distance and time from communities to the medical facilities capable of treating COVID-19 patients, and we identified the service areas of those facilities as well. The results showed significant differences in service areas and potential loading across medical facilities. The accessibility of medical facilities in the peripheral areas was inferior to those in the central areas; there was spatial inequality of medical resources within and across districts; the amount of community healthcare centers was insufficient; some communities were underserved regarding walking distance; some medical facilities could be potentially overloaded. This study provides reference, in the context of Wuhan, for understanding the spatial aspect of medical resources and residents’ relevant mobility under the emergency regulation, and re-examining the coordination of emergency to improve future planning and utilization of medical facilities at various levels. The approach can facilitate policymakers to assess potential loading of medical facilities, identify low-accessibility areas, and deploy new medical facilities. It also implies that the accessibility analysis can be rapid and relevant even only with open-source data.

Facility Attractiveness and Social Vulnerability Impacts on Spatial Accessibility to Opioid Treatment Programs in South Carolina

Opioid dependence and opioid-related mortality have been increasing in recent years in the United States. Available and accessible treatments may result in a reduction of opioid-related mortality. This work describes the geographic variation of spatial accessibility to opioid treatment programs (OTPs) and identifies areas with poor access to care in South Carolina. The study develops a new index of access that builds on the two-step floating catchment area (2SFCA) method, and has three dimensions: a facility attractiveness index, defined by services rendered incorporated into the Huff Model; a facility catchment area, defined as a function of facility attractiveness to account for variable catchment size; and a Social Vulnerability Index (SVI) to account for nonspatial factors that mitigate or compound the impacts of spatial access to care. Results of the study indicate a significant variation in access to OTPs statewide. Spatial access to OTPs is low across the entire state except for in a limited number of metropolitan areas. The majority of the population with low access (85%) live in areas with a moderate-to-high levels of social vulnerability. This research provides more realistic estimates of access to care and aims to assist policymakers in better targeting disadvantaged areas for OTP program expansion and resource allocation.

Spatial accessibility to colonoscopy and its role in predicting late-stage colorectal cancer

OBJECTIVE

To better determine the relationship between spatial access to colonoscopy and colorectal cancer (CRC) outcomes, our objective was to examine the agreement of the classic, enhanced, and variable two-step floating catchment area (2SFCA) methods in evaluating spatial access to colonoscopy and to compare the predictive validity of each method related to late-stage CRC. 2SFCA methods simultaneously consider supply/demand of services and impedance (ie, travel time).

DATA SOURCES

Colonoscopy provider locations were obtained from the South Carolina Ambulatory Surgery Database. ZIP code tabulation area (ZCTA) level population estimates and area-level poverty level were obtained from the American Community Survey. Rurality was determined by the United States Department of Agriculture's Rural-Urban Commuting Area codes. Individual-level CRC data were obtained from the South Carolina Central Cancer Registry.

STUDY DESIGN

Using the classic, enhanced, and variable 2SFCA methods, we calculated ZCTA-level spatial access to colonoscopy. We assessed agreement between the three methods by calculating Spearman's rank coefficients and weighted Kappas (Κ). Global and Local Moran's I were used to assess spatial clustering of accessibility scores across 2SFCA methods. We performed multilevel logistic regression analyses to examine the association between spatial accessibility to colonoscopy, area- and individual-level factors, and late-stage CRC.

PRINCIPAL FINDINGS

We found strong agreement (Weighted Κ = 0.82; 95% CI = 0.79-0.86) and identified similar clustering patterns with the classic and enhanced 2SFCA methods. There was negligible agreement among the classic/enhanced 2SFCA and the variable 2SFCA. Across all 2SFCA methods, regression models showed that spatial access to colonoscopy, rurality, and poverty level were not associated with greater odds of late-stage CRC, though Black race was associated with late-stage CRC across all models.

CONCLUSIONS

None of the 2SFCA methods showed an association with late-stage CRC. Future studies should explore which elements (spatial or nonspatial) of access to care have the greatest impact on CRC outcomes.

Skin Cancer and UV Exposure-Related Behaviors Among Appalachian and Non-Appalachian Adults

INTRODUCTION

Appalachian communities experience elevated rates of cancer incidence and mortality relative to other regions in the U.S. Specifically, melanoma mortality rates are higher in Appalachia compared to the national average, despite comparable incidence rates.

PURPOSE

To examine differences in self-reported history of skin cancer and prevalence of two UV exposure behaviors between Appalachian and non-Appalachian adults in a nationally representative sample.

METHODS

Data are from four cross-sectional cycles of the Health Information National Trends Survey (2011-2014) (N=14,451). We examined sunscreen use and tanning bed use, and self-reported history of melanoma and non-melanoma skin cancer. Descriptive and weighted multivariable analyses were conducted to examine sunscreen and tanning bed use, controlling for sociodemographic characteristics.

RESULTS

Approximately 8% of the study sample resided in Appalachia (n=1,015). Self-reported melanoma (0.6%) and non-melanoma (3.2%) skin cancer histories were low among Appalachians and did not differ statistically from non-Appalachians (p>0.05). Only 21.2% of Appalachians reported using sunscreen often or always when going outside for more than one hour on a warm, sunny day compared to 27.4% of non-Appalachians (pp=0.04), but there were no regional differences in tanning bed use (OR=1.48, p=0.23) when controlling for sociodemographics and general health status.

IMPLICATIONS

Appalachians had comparable histories of self-reported melanoma and non-melanoma skin cancer but were less likely to report sunscreen use than non-Appalachians. Enhanced communication efforts to promote sunscreen use and other UV protection behaviors in Appalachia may be valuable.

Spatial Accessibility to Mammography Services in the Lower Mississippi Delta Region States

PURPOSE

To characterize spatial access to mammography services across 8 Lower Mississippi Delta Region (LMDR) states. These states include the Delta Region, a federally designated, largely rural, and impoverished region with a high proportion of black residents and low mammography utilization rates.

METHODS

Using the enhanced 2-step floating catchment area method, we calculated spatial accessibility scores for mammography services across LMDR census tracts. We compared accessibility scores between the Delta and non-Delta Regions of the LMDR. We also performed hotspot analysis and constructed spatial lag models to detect clusters of low spatial access and to identify sociodemographic factors associated with access, respectively. We obtained mammography facility locations data from the Food and Drug Administration and sociodemographic variables from the American Community Survey and the US Department of Agriculture.

RESULTS

Overall, there were no differences in spatial accessibility scores between the Delta and non-Delta Regions, though there was some state-to-state variation. Clusters of low spatial access were found in parts of the Arkansas, Mississippi, and Tennessee Delta. Spatial lag models found that poverty was associated with greater spatial access to mammography.

CONCLUSIONS

The lack of identified differences in spatial access to mammography in the Delta and non-Delta Regions suggests that psychosocial or financial barriers play a larger role in lower mammography utilization rates. Identifying clusters of low spatial access to mammography services can help inform resource allocation. Further, our study underscores the value of using coverage-based methods rather than travel time or container measures to evaluate spatial access to care.

Geographic disparities in accessing community pharmacies among vulnerable populations in the Greater Toronto Area

OBJECTIVES

Geographic accessibility to community pharmacies (CPs) plays an increasingly important role for the well-being of a community. This study examines the geographic distribution of CPs within the Greater Toronto Area (GTA) relative to the residential patterns of vulnerable populations, including older adults (65+ years), infants and children (0-9 years), and low-income households.

METHODS

The study develops a geographic accessibility index at a dissemination area (DA) level by employing the enhanced two-step floating catchment area (E2SFCA) method to measure geographic accessibility to pharmacies. A vulnerability index is also developed to assess and visualize the residential patterns of vulnerable groups. A combined vulnerability-accessibility index is then constructed to identify low-access areas associated with high levels of socio-economic vulnerability. A range of geo-referenced datasets are analyzed within a geographical information system.

RESULTS

The study reveals geographical disparities in accessing pharmacies between urban and suburban areas and across different neighbourhoods, while accounting for population density and distance decay. About 19% of the population (or 15% of DAs) are under-serviced, with very poor geographic access to CPs (1.7 CPs per 10,000 persons), compared to 29.6% of the DAs that are well-/over-serviced, with an average score of 2.8 CPs per 10,000 persons.

CONCLUSION

The spatial-quantitative analysis at a small geography (DA) allows for improved accuracy for identifying specific neighbourhoods that are in need of greater access to pharmacies by vulnerable residents and areas that have an excessive supply of pharmacies. It provides implications for addressing barriers to accessing pharmacies among high-needs groups, including the rapidly growing older adult population in the GTA.

A multi-modal relative spatial access assessment approach to measure spatial accessibility to primary care providers

Two-step floating catchment area (2SFCA) methods that account for multiple transportation modes provide more realistic accessibility representation than single-mode methods. However, the use of the impedance coefficient in an impedance function (e.g., Gaussian function) introduces uncertainty to 2SFCA results. This paper proposes an enhancement to the multi-modal 2SFCA methods through incorporating the concept of a spatial access ratio (SPAR) for spatial access measurement. SPAR is the ratio of a given place's access score to the mean of all access scores in the study area. An empirical study on spatial access to primary care physicians (PCPs) in the city of Albuquerque, NM, USA was conducted to evaluate the effectiveness of SPAR in addressing uncertainty introduced by the choice of the impedance coefficient in the classic Gaussian impedance function. We used ESRI StreetMap Premium and General Transit Specification Feed (GTFS) data to calculate the travel time to PCPs by car and bus. We first generated two spatial access scores-using different catchment sizes for car and bus, respectively-for each demanding population location: an accessibility score for car drivers and an accessibility score for bus riders. We then computed three corresponding spatial access ratios of the above scores for each population location. Sensitivity analysis results suggest that the spatial access scores vary significantly when using different impedance coefficients (p < 0.05); while SPAR remains stable (p = 1). Results from this paper suggest that a spatial access ratio can significantly reduce impedance coefficient-related uncertainties in multi-modal 2SFCA methods.

Spatial accessibility to healthcare services in Shenzhen, China: improving the multi-modal two-step floating catchment area method by estimating travel time via online map APIs

BACKGROUND

Shenzhen has rapidly grown into a megacity in the recent decades. It is a challenging task for the Shenzhen government to provide sufficient healthcare services. The spatial configuration of healthcare services can influence the convenience for the consumers to obtain healthcare services. Spatial accessibility has been widely adopted as a scientific measurement for evaluating the rationality of the spatial configuration of healthcare services.

METHODS

The multi-modal two-step floating catchment area (2SFCA) method is an important advance in the field of healthcare accessibility modelling, which enables the simultaneous assessment of spatial accessibility via multiple transport modes. This study further develops the multi-modal 2SFCA method by introducing online map APIs to improve the estimation of travel time by public transit or by car respectively.

RESULTS

As the results show, the distribution of healthcare accessibility by multi-modal 2SFCA shows significant spatial disparity. Moreover, by dividing the multi-modal accessibility into car-mode and transit-mode accessibility, this study discovers that the transit-mode subgroup is disadvantaged in the competition for healthcare services with the car-mode subgroup. The disparity in transit-mode accessibility is the main reason of the uneven pattern of healthcare accessibility in Shenzhen.

CONCLUSIONS

The findings suggest improving the public transit conditions for accessing healthcare services to reduce the disparity of healthcare accessibility. More healthcare services should be allocated in the eastern and western Shenzhen, especially sub-districts in Dapeng District and western Bao'an District. As these findings cannot be drawn by the traditional single-modal 2SFCA method, the advantage of the multi-modal 2SFCA method is significant to both healthcare studies and healthcare system planning.

Does the edge effect impact on the measure of spatial accessibility to healthcare providers?

BACKGROUND

Spatial accessibility indices are increasingly applied when investigating inequalities in health. Although most studies are making mentions of potential errors caused by the edge effect, many acknowledge having neglected to consider this concern by establishing spatial analyses within a finite region, settling for hypothesizing that accessibility to facilities will be under-reported. Our study seeks to assess the effect of edge on the accuracy of defining healthcare provider access by comparing healthcare provider accessibility accounting or not for the edge effect, in a real-world application.

METHODS

This study was carried out in the department of Nord, France. The statistical unit we use is the French census block known as 'IRIS' (Ilot Regroupé pour l'Information Statistique), defined by the National Institute of Statistics and Economic Studies. The geographical accessibility indicator used is the "Index of Spatial Accessibility" (ISA), based on the E2SFCA algorithm. We calculated ISA for the pregnant women population by selecting three types of healthcare providers: general practitioners, gynecologists and midwives. We compared ISA variation when accounting or not edge effect in urban and rural zones. The GIS method was then employed to determine global and local autocorrelation. Lastly, we compared the relationship between socioeconomic distress index and ISA, when accounting or not for the edge effect, to fully evaluate its impact.

RESULTS

The results revealed that on average ISA when offer and demand beyond the boundary were included is slightly below ISA when not accounting for the edge effect, and we found that the IRIS value was more likely to deteriorate than improve. Moreover, edge effect impact can vary widely by health provider type. There is greater variability within the rural IRIS group than within the urban IRIS group. We found a positive correlation between socioeconomic distress variables and composite ISA. Spatial analysis results (such as Moran's spatial autocorrelation index and local indicators of spatial autocorrelation) are not really impacted.

CONCLUSION

Our research has revealed minor accessibility variation when edge effect has been considered in a French context. No general statement can be set up because intensity of impact varies according to healthcare provider type, territorial organization and methodology used to measure the accessibility to healthcare. Additional researches are required in order to distinguish what findings are specific to a territory and others common to different countries. It constitute a promising direction to determine more precisely healthcare shortage areas and then to fight against social health inequalities.