Quantifying the impact of hospital catchment area definitions on hospital admissions forecasts: COVID-19 in England, September 2020-April 2021.

BACKGROUND: Defining healthcare facility catchment areas is a key step in predicting future healthcare demand in epidemic settings. Forecasts of hospitalisations can be informed by leading indicators measured at the community level. However, this relies on the definition of so-called catchment areas or the geographies whose populations make up the patients admitted to a given hospital, which are often not well-defined. Little work has been done to quantify the impact of hospital catchment area definitions on healthcare demand forecasting. METHODS: We made forecasts of local-level hospital admissions using a scaled convolution of local cases (as defined by the hospital catchment area) and delay distribution. Hospital catchment area definitions were derived from either simple heuristics (in which people are admitted to their nearest hospital or any nearby hospital) or historical admissions data (all emergency or elective admissions in 2019, or COVID-19 admissions), plus a marginal baseline definition based on the distribution of all hospital admissions. We evaluated predictive performance using each hospital catchment area definition using the weighted interval score and considered how this changed by the length of the predictive horizon, the date on which the forecast was made, and by location. We also considered the change, if any, in the relative performance of each definition in retrospective vs. real-time settings, or at different spatial scales. RESULTS: The choice of hospital catchment area definition affected the accuracy of hospital admission forecasts. The definition based on COVID-19 admissions data resulted in the most accurate forecasts at both a 7- and 14-day horizon and was one of the top two best-performing definitions across forecast dates and locations. The "nearby" heuristic also performed well, but less consistently than the COVID-19 data definition. The marginal distribution baseline, which did not include any spatial information, was the lowest-ranked definition. The relative performance of the definitions was larger when using case forecasts compared to future observed cases. All results were consistent across spatial scales of the catchment area definitions. CONCLUSIONS: Using catchment area definitions derived from context-specific data can improve local-level hospital admission forecasts. Where context-specific data is not available, using catchment areas defined by carefully chosen heuristics is a sufficiently good substitute. There is clear value in understanding what drives local admissions patterns, and further research is needed to understand the impact of different catchment area definitions on forecast performance where case trends are more heterogeneous.

A framework and process for community-engaged, mixed-methods cancer needs assessments.

PURPOSE: Community health needs assessments are required for most state and local public health agencies and non-profit hospitals. Typically based on community health improvement planning models, these assessments encompass overall community health and multiple diseases to inform program planning. National Cancer Institute (NCI)-designated Cancer Centers and community-based cancer-focused programs share the goal of reducing cancer burden in the catchment areas they serve. However, to date, no published models exist to guide cancer-specific needs assessments for a determined geographic area that can inform both public health and research initiatives. The purpose of this article is to outline a cancer needs assessment (CNA) framework and community-engaged, mixed-methods process, along with a case study of how we applied it in Kentucky. METHODS: We convened a steering committee of key organizational partners to provide input throughout the process. We developed a conceptual framework of multi-level determinants affecting cancer-related outcomes. We incorporated both quantitative and qualitative data gathered through a variety of means, including a novel application of group concept mapping to guide definition of priorities. RESULTS: The resulting CNA has helped guide strategic planning and priorities for Kentucky's Cancer Action Plan, Markey Cancer Center, state agencies, and community-based organizations. CONCLUSION: This framework and process can be used collaboratively by cancer center Community Outreach and Engagement offices, public health agencies, oncology programs, and community partners to plan impactful cancer control programs and research in their catchment areas. Universities can also use them to inform the planning of community engagement and health equity research efforts.

Measuring Spatial Access of Vulnerable Population to HIV Testing Facilities in the Baton Rouge Metropolitan Statistical Area, Louisiana.

Ensuring adequate and equitable access to affordable HIV testing is a crucial step toward ending the HIV epidemic (EHE). Using the high-burden Baton Rouge Metropolitan Statistical Area (MSA) as an example, we measure spatial access to HIV testing facilities for vulnerable populations and assess whether their access would improve if eliminating a considerable barrier-costs. Locations and status (free, low-cost, and full cost) of HIV testing facilities are searched on the Internet and confirmed through a field survey. Vulnerable populations include the uninsured and people living with HIV (PLWH), disaggregated from county-level HIV prevalence data. Spatial access is computed by a normalized urban-rural two-step floating catchment area (NUR2SFCA) method. Our survey confirms that only 11% and 37% of the 103 Internet-searched HIV testing facilities are indeed free and low-cost. Making more facilities cheaper or free increases the average access of PLWH, the uninsured, and the entire population but their geographic patterns vary. Free testing facilities, clustered in Baton Rouge city, are highly accessible to 82.6%, 69.4%, and 70.2% of three population groups living in East and West Baton Rouge Parish. In comparison, making all low-cost facilities free increases access in most outlying parishes but at the cost of reducing access in East Baton Rouge Parish, leaving west Livingston, north Iberville, and east Pointe Coupee Parish with the poorest access. Making all full-cost facilities cheaper or free exhibits a similar pattern. The study has important policy implications for where and how to improve access to HIV testing for vulnerable populations.

RESUMEN: Medimos el acceso espacial a las instalaciones de pruebas de VIH para poblaciones vulnerables y evaluamos si su acceso mejoraría si se eliminaran las barreras de costos, utilizando como ejemplo el área estadística metropolitana de Baton Rouge, que tiene una alta carga. Nuestra encuesta confirma que el 11% y el 37% de los 103 centros de pruebas de VIH buscados en Internet son efectivamente gratuitos y de bajo costo. Hacer que más instalaciones sean más baratas o gratuitas aumenta el acceso promedio de las PLWH, las personas sin seguro y toda la población, pero sus patrones geográficos varían. Las instalaciones de pruebas gratuitas, agrupadas en la ciudad de Baton Rouge, son muy accesibles para el 82,6%, el 69,4% y el 70,2% de los tres grupos de población del este y oeste de Baton Rouge. En comparación, hacer que las instalaciones de bajo costo sean gratuitas aumenta el acceso en las parroquias periféricas, pero a costa de reducir el acceso en East Baton Rouge. Hacer que las instalaciones de costo total sean más baratas o gratuitas muestra un patrón similar. El estudio tiene importantes implicaciones políticas para mejorar el acceso a las pruebas del VIH para las poblaciones vulnerables.

Efficiency effects of public hospital closures in the context of public hospital reform: a multistep efficiency analysis.

In the wake of hospital reforms introduced in 2011 in Turkey, public hospitals were grouped into associations with joint management and some shared operational and administrative functions, similar in some ways to hospital trusts in the English National Health Service. Reorganization of public hospitals effect hospital and market area characteristics and existence of hospitals. The objective of this study is to examine the effect of closure on competitive hospital performances. Using administrative data from Turkish Public Hospital Statistical Yearbooks for the years 2005 to 2007 and 2014 to 2017, we conducted a three-step efficiency analysis by incorporating data envelopment analysis (DEA) and propensity score matching techniques, followed by a difference-in-differences (DiD) regression. First, we used bootstrapped DEA to calculate the efficiency scores of hospitals that were located near hospitals that had been closed. Second, we used nearest neighbour propensity score matching to form control groups and ensure that any differences between these and the intervention groups could be attributed to being near a hospital that had closed rather than differences in hospital and market area characteristics. Lastly, we employed DiD regression analysis to explore whether being near a closed hospital had an impact on the efficiency of the surviving hospitals while considering the effect of the 2011 hospital reform policies. To shed light on a potential time lag between hospital closure and changes in efficiency, we used various periods for comparison. Our results suggest that the efficiency of public hospitals in Turkey increased in hospitals that were located near hospitals that closed in Turkey from 2011. Hospital closure improves the efficiency of competitive hospitals under hospital market reforms. Future studies may wish to examine the efficiency effects of government and private sector collaboration on competition in the hospital market.

An integrated approach to analyze equitable access to food stores under disasters from human mobility patterns.

Limited access to food stores is often linked to higher health risks and lower community resilience. Socially vulnerable populations experience persistent disparities in equitable food store access. However, little research has been done to examine how people's access to food stores is affected by natural disasters. Previous studies mainly focus on examining potential access using the travel distance to the nearest food store, which often falls short of capturing the actual access of people. Therefore, to fill this gap, this paper incorporates human mobility patterns into the measure of actual access, leveraging large-scale mobile phone data. Specifically, we propose a novel enhanced two-step floating catchment area method with travel preferences (E2SFCA-TP) to measure accessibility, which extends the traditional E2SFCA model by integrating actual human mobility behaviors. We then analyze people's actual access to grocery and convenience stores across both space and time under the devastating winter storm Uri in Harris County, Texas. Our results highlight the value of using human mobility patterns to better reflect people's actual access behaviors. The proposed E2SFCA-TP measure is more capable of capturing mobility variations in people's access, compared with the traditional E2SFCA measure. This paper provides insights into food store access across space and time, which could aid decision making in resource allocation to enhance accessibility and mitigate the risk of food insecurity in underserved areas.

Comparative assessment of FSM and MPSIAC models in quantifying soil sedimentation rates in the semi-humid and alpine regions of northern Iran.

Soil erosion and sediment yield is a global problem that increasingly contributes to soil degradation. Although erosion analysis requires the availability of erosion and sedimentation data, the lack of sediment monitoring stations and the resulting limitations in collecting sediment measurements have necessitated the use of experimental models in many areas. The present study aimed to compare Factorial Scoring Model (FSM) and Modified Pacific South-West Inter-Agency Committee (MPSIAC) model for estimating erosion in the Mazdaran Basin (Firoozkuh, Iran). For this purpose, the required maps were prepared for both models, and the sediment rate was estimated using the two models to compare their efficiency using the corresponding maximum error (ME) and coefficient of determination (R2) values. The results showed that considering sediment based on the FSM model, the studied catchment consisted of regions with a high and very high sediment yield, while the MPSIAC model identified regions with low, medium, and high sediment yield. With an R2 value of 0.62 and an ME value of 2.24, the MPSIAC model provided more accurate estimates of the sediment yield in the studied area. Using the MPSIAC model, sediment yield was 6687.86 tons per year or the equivalent of 2.64 tons/ha per year.

A population-based survey of self-reported delays in breast, cervical, colorectal and lung cancer screening.

The early COVID-19 pandemic was associated with cessation of screening services, but the prevalence of ongoing delays in cancer screening into the third year of the pandemic are not well-characterized. In February/March 2022, a population-based survey assessed cancer needs in New Hampshire and Vermont. The associations between cancer screening delays (breast, cervical, colorectal or lung cancer) and social determinants of health, health care access, and cancer attitudes and beliefs were tested. Distributions and Rao-Scott chi-square tests were used for hypothesis testing and weighted to represent state populations. Of 1717 participants, 55% resided in rural areas, 96% identified as White race, 50% were women, 36% had high school or less education. Screening delays were reported for breast cancer (28%), cervical cancer (30%), colorectal cancer (24%), and lung cancer (30%). Delays were associated with having higher educational attainment (lung), urban living (colorectal), and having Medicaid insurance (breast, cervical). Low confidence in ability to obtain information about cancer was associated with screening delays across screening types. The most common reason for delay was the perception that the screening test was not urgent (31% breast, 30% cervical, 28% colorectal). Cost was the most common reason for delayed lung cancer screening (36%). COVID-19 was indicated as a delay reason in 15-29% of respondents; 12-20% reported health system capacity during the pandemic as a reason for delay, depending on screening type. Interventions that address sub-populations and reasons for screening delays are needed to mitigate the impact of the COVID-19 pandemic on cancer burden and mortality.

Optimal allocation of physicians improves accessibility and workload disparities in stroke care.

BACKGROUND: Inequalities in access to stroke care and the workload of physicians have been a challenge in recent times. This may be resolved by allocating physicians suitable for the expected demand. Therefore, this study analyzes whether reallocation using an optimization model reduces disparities in spatial access to healthcare and excessive workload. METHODS: This study targeted neuroendovascular specialists and primary stroke centers in Japan and employed an optimization model for reallocating neuroendovascular specialists to reduce the disparity in spatial accessibility to stroke treatment and workload for neuroendovascular specialists in Japan. A two-step floating catchment area method and an inverted two-step floating catchment area method were used to estimate the spatial accessibility and workload of neuroendovascular specialists as a potential crowdedness index. Quadratic programming has been proposed for the reallocation of neuroendovascular specialists. RESULTS: The reallocation of neuroendovascular specialists reduced the disparity in spatial accessibility and the potential crowdedness index. The standard deviation (SD) of the demand-weighted spatial accessibility index improved from 125.625 to 97.625. Simultaneously, the weighted median spatial accessibility index increased from 2.811 to 3.929. Additionally, the SD of the potential crowdedness index for estimating workload disparity decreased from 10,040.36 to 5934.275 after optimization. The sensitivity analysis also showed a similar trend of reducing disparities. CONCLUSIONS: The reallocation of neuroendovascular specialists reduced regional disparities in spatial accessibility to healthcare, potential crowdedness index, and disparities between facilities. Our findings contribute to planning health policies to realize equity throughout the healthcare system.

BK-SWMM flood simulation framework is being proposed for urban storm flood modeling based on uncertainty parameter crowdsourcing data from a single functional region.

In recent years, urban flood disasters caused by sudden heavy rains have become increasingly severe, posing a serious threat to urban public infrastructure and the life and property safety of residents. Rapid simulation and prediction of urban rain-flood events can provide timely decision-making reference for urban flood control and disaster reduction. The complex and arduous calibration process of urban rain-flood models has been identified as a major obstacle affecting the efficiency and accuracy of simulation and prediction. This study proposes a multi-scale urban rain-flood model rapid construction method framework, BK-SWMM, focusing on urban rain-flood model parameters and based on the basic architecture of Storm Water Management Model (SWMM). The framework comprises two main components: 1) constructing a SWMM uncertainty parameter sample crowdsourcing dataset and coupling Bayesian Information Criterion (BIC) and K-means clustering machine learning algorithm to discover clustering patterns of SWMM model uncertainty parameters in urban functional areas; 2) coupling BIC and K-means with SWMM model to form BK-SWMM flood simulation framework. The applicability of the proposed framework is validated by modeling three different spatial scales in the study regions based on observed rainfall-runoff data. The research findings indicate that the distribution pattern of uncertainty parameters, such as depression storage, surface Manning coefficient, infiltration rate, and attenuation coefficient. The distribution patterns of these seven parameters in urban functional zones indicate that the values are highest in the Industrial and Commercial Areas (ICA), followed by Residential Areas (RA), and lowest in Public Areas (PA). All three spatial scales' REQ, NSEQ, and RD2 indices were superior to the SWMM and less than 10%, greater than 0.80, and greater than 0.85, respectively. However, when the study area's geographical scale expands, the simulation's accuracy will decline. Further research is required on the scale dependency of urban storm flood models.

Linking G2SFCA method and circuit theory to promote spatial equity and landscape connectivity in urban ecological infrastructure.

Protecting and constructing urban ecological infrastructure (UEI) is an important spatial means of improving the quality of life of urban residents, enhancing the benefits of the urban environment, and improving urban habitats. Landscape connectivity is the basis for UEI to play an ecological role. Spatial equity is an important goal for UEI to enhance urban resident happiness and sense of access and achieve environmental justice. Taking Yantai city as an example, this study analyzed the UEI morphological spatial pattern based on morphological spatial pattern analysis and calculated the spatial accessibility of UEI based on the gravity -based two-step-floating catchment area (G2SFCA) method. In addition, the study proposed the concept of accessible UEI and reflected the spatial differences in the equity of accessible UEI in urban residential areas through equity modeling that was oriented to connectivity enhancement and equity improvement. Moreover, the study integrated the location-allocation model and circuit theory to optimize the spatial layout of the existing UEI and construct an urban ecological corridor that considered landscape connectivity and leisure and recreational convenience. The results of this study showed that the proportion of bridge and island areas with connecting functions in the existing UEI in Yantai was only 10%, and they had not yet formed a complete network structure; hence, connectivity improvements were needed. In addition, the equity of accessible UEI in the residential areas of Yantai was generally good, and more than two-thirds of residents had sufficient access to UEI. However, approximately 32.7% of the residents in the four old city areas lacked a UEI distribution within their effective commuting time. Moreover, UEI layout optimization could improve the equity of accessible UEI in residential areas; however, the method of adding a new UEI was not applicable to areas with high concentrations of urban populations and stable urban spatial layouts. Furthermore, urban ecological corridors could effectively improve the connectivity and equity of UEI; however, 70% relied on existing road systems and needed to enhance their ecological attributes. The UEI equity of residential areas was highly correlated with house prices, indicating an obvious spatial injustice in the UEI layout in Yantai. Planners and governments should promote urban environmental justice through effective conservation and construction measures by incorporating established ecological and artificial infrastructures into UEI planning to achieve equitable access to UEI services for urban residents. This study provides a spatial reference and methodological support to enhance the equity and connectivity of UEI.

Refining 2SVCA Method for Measuring Telehealth Accessibility of Primary Care Physicians in Baton Rouge, Louisiana.

Equity in health care delivery is a longstanding concern of public health policy. Telehealth is considered an important way to level the playing field by broadening health services access and improving quality of care and health outcomes. This study refines the recently developed "2-Step Virtual Catchment Area (2SVCA) method" to assess the telehealth accessibility of primary care in the Baton Rouge Metropolitan Statistical Area, Louisiana. The result is compared to that of spatial accessibility via physical visits to care providers based on the popular 2-Step Floating Catchment Area (2SFCA) method. The study shows that both spatial and telehealth accessibilities decline from urban to low-density and then rural areas. Moreover, disproportionally higher percentages of African Americans are in areas with higher spatial accessibility scores; but such an advantage is not realized in telehealth accessibility. In the study area, absence of broadband availability is mainly a rural problem and leads to a lower average telehealth accessibility than physical accessibility in rural areas. On the other side, lack of broadband affordability is a challenge across the rural-urban continuum and is disproportionally associated with high concentrations of disadvantaged population groups such as households under the poverty level and Blacks.

Improving allocative efficiency from network consolidation: a solution for the health workforce shortage.

BACKGROUND: Public hospitals are facing a critical shortage of health workers. The area-based network consolidations could be the solution to increase the system capacity for human resources by improving local allocative efficiency. METHODS: This study develops counterfactual simulations for area-based network allocations for the health workforce in 10500 public hospitals in Thailand and examines improvements in allocative efficiency from the health workforce redistribution at different administrative levels such as sub-districts, districts, provinces, and health service areas. The workload per worker is calculated from the output measured by numbers of outpatient and inpatient cases and the input measured by numbers of health workers. Both output and input are weighted with their economic values and controlled for heterogeneity through regression analysis. Finally, this study compares the workload per worker and economic valuation of the area-based networks or ex-ante scenarios with the hospital-level or status quo scenario. RESULTS: Network consolidations of the sub-district primary-level hospitals within the same district could reduce workload per worker by seven percentage points. Another practical policy option is to consolidate similar hospital levels such as primary, first-level secondary, and mid-level secondary hospitals altogether within the same province which could result in the reduction of the workload per worker by 6-7 percentage points. The total economic value gained from consolidating similar hospital levels within the same province is about 15-18 percentage points of total labor cost in the primary hospitals. CONCLUSION: This study illustrates the improvement in allocative efficiency of the health workforce in public hospitals from the area-based network consolidations. The results provide an insightful example of economic gains from efficiently reallocating the medical workforce within the same local areas. Major reforms are required such that the health care delivery units can automate their resources in corresponding to the population's health needs through a strengthening gatekeeping system.

Algorithmic hospital catchment area estimation using label propagation.

BACKGROUND: Hospital catchment areas define the primary population of a hospital and are central to assessing the potential demand on that hospital, for example, due to infectious disease outbreaks. METHODS: We present a novel algorithm, based on label propagation, for estimating hospital catchment areas, from the capacity of the hospital and demographics of the nearby population, and without requiring any data on hospital activity. RESULTS: The algorithm is demonstrated to produce a mapping from fine grained geographic regions to larger scale catchment areas, providing contiguous and realistic subdivisions of geographies relating to a single hospital or to a group of hospitals. In validation against an alternative approach predicated on activity data gathered during the COVID-19 outbreak in the UK, the label propagation algorithm is found to have a high level of agreement and perform at a similar level of accuracy. RESULTS: The algorithm can be used to make estimates of hospital catchment areas in new situations where activity data is not yet available, such as in the early stages of a infections disease outbreak.

Supply-demand matching of medical services at a city level under the background of hierarchical diagnosis and treatment - based on Didi Chuxing Data in Haikou, China.

BACKGROUND: Implementation of the Healthy China Strategy and the hierarchical diagnosis and treatment system has injected new vitality into medical services. Given the insufficient supply of medical services and increasing demand for medical treatment, exploring the supply-demand pattern of medical services has become an urgent theoretical and practical problem to be solved. The equity of healthcare facilities has received widespread attention, but due to limited data, there is little research on the supply-demand pattern of medical services. This study focuses on evaluating the supply-demand matching pattern of medical services at different levels in Haikou City with big geographic data and promoting the realization of a balance between medical supply and demand. METHODS: This study utilizes spatial data of medical institutions, Didi Chuxing Data, and population density data. Firstly, use the two-step floating catchment area method and GIS spatial analysis to explore characteristics of the supply-demand patterns of medical services at different levels in Haikou. Secondly, we mine residents' demand for medical treatment based on Didi Chuxing Data. Then combined with population density data, divide supply-demand matching of medical institutions into four types. Finally, propose optimization strategies for the problems. RESULTS: The accessibility pattern of high-level medical institutions in Haikou presents high in the north and low in the south. The accessibility pattern of low-level medical institutions is the opposite. High-level medical institutions have a strong demand for medical treatment, which is less hampered by distance. The healthcare demand of low-level medical institutions is small, and they mainly are medium- and short-distance medical travel. The types of medical services at different levels are mainly "low supply - low demand" and "high supply - low demand" types. CONCLUSIONS: Medical services at different levels in Haikou are mainly in supply-demand imbalance. Therefore, we put forward optimization strategies to promote the equity of primary medical services, such as propelling the establishment and improvement of the hierarchical diagnosis and treatment system, building a new model of medical and health service supply, and strengthening balanced coverage of primary medical institutions. The mining of big geographic data is beneficial to alleviate the mismatch between medical supply and demand, although the data and methods need to be improved.

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.

Spatial and Nonspatial Factors Associated with Access to Medication for Opioid Use Disorder among Pregnant Women in Massachusetts.

INTRODUCTION: In Massachusetts, one-third of pregnant women with opioid use disorder (OUD) do not receive medications for OUD (MOUD), such as buprenorphine and methadone. Research has demonstrated that broadly, access to medications differs by location and by socioeconomic and geographic characteristics of communities, but a comprehensive understanding at the micro-level is lacking. This study aims to identify and characterize access to MOUD treatment among pregnant women in Massachusetts. METHODS: We used enhanced two-step floating catchment area analyses, which incorporated supply and demand measures, as well as local drive-time, to determine spatial accessibility to MOUD. We used four publicly available data sources to calculate geographic accessibility to MOUD. We then merged the resulting accessibility indices with data from the American Community Survey to statistically analyze ZIP Code Tabulation Area (ZCTA) characteristics that were associated with geographic accessibility to MOUD among the study population. RESULTS: We calculated access to 258 opioid (methadone and/or buprenorphine) treatment programs and 2,585 buprenorphine-waivered prescribers among 74,969 pregnant women during the period 2016-2020 in 448 ZCTAs (N = 537 ZCTAs). ZCTAs with lower accessibility to both types of MOUD were concentrated in Western Massachusetts. Central Massachusetts had poor accessibility to buprenorphine providers. Accessibility was greater in ZCTAs that were nonmetropolitan, that had higher minority status and langauge vulnerability, and that had less extreme concentration of privilege. CONCLUSIONS: There is a need to improve MOUD access overall, and to enhance access to both types of medications, so pregnant women can choose the one that works best for them.

Potential crowdedness of mechanical thrombectomy and cerebral infarction mortality in Japan: Application of inverted two-step floating catchment area method.

OBJECTIVES: This study aimed to evaluate a stroke medical delivery system based on population coverage and the potential crowdedness index (PCI) of mechanical thrombectomy and investigate the relationship between PCI and cerebral infarction mortality in Japan. MATERIALS AND METHODS: This cross-sectional study defined 662 facilities and 1605 neurointerventionalists as supply, population aged 55 years or older as demand, and set the reachable area for demand as 120 min in driving time. Multiple regression analysis adjusted for spatial autocorrelation was used to examine the relationship between PCI and cerebral infarction mortality. RESULTS: In the 2020 data, 99% of the population aged 55 years or older had access to mechanical thrombectomy (≤120 min), and the PCI ranged from 5876 to 129838, with a median of 30426. From 2020 to 2035, the PCI is estimated to increase (30426 to 32510), decreasing after 2035 (32510 to 29469). The PCI distribution exhibited geographical heterogeneity. High PCI values emerged in eastern Japan. According to regression analysis, the increase in PCI by 1% led to an increase of 0.13% in standardized mortality ratio of cerebral infarction in men. However, PCI did not significantly correlate with cerebral infarction mortality in women. CONCLUSIONS: PCI for hospitals based on supply and demand was geographically heterogeneous in Japan. Optimization of PCI contributes equalization of mechanical thrombectomy provision system and may improve cerebral infarction mortality.

Using the health belief model to assess racial/ethnic disparities in cancer-related behaviors in an NCI-designated comprehensive cancer center catchment area.

BACKGROUND: Racial and ethnic minorities experience well-documented disparities across the cancer trajectory. However, factors underlying these disparities may vary regionally. The Health Belief Model (HBM) was developed to explain and predict health-related prevention and early detection behaviors, particularly uptake of health services. Our goal was to use the HBM to guide an exploration of factors that contribute to racial/ethnic health disparities in the catchment area of a large National Cancer Institute-designated Comprehensive Cancer Center in the Southeastern United States. METHODS: We conducted a secondary analysis of data collected by the cancer center for its triennial Community Health Needs Assessment, which sampled adults from the center's 15-county catchment area. White non-Hispanics (WNHs; n = 887), Black non-Hispanics (BNHs; n = 78), Hispanics/Latinxs (H/Ls; n = 185), and those identifying as another race/ethnicity ("Others"; n = 39) were compared across key HBM variables, including demographic/psychosocial information, perceived benefits and barriers to preventive health behaviors, risk perception, and health behavior outcomes. RESULTS: Controlling for annual household income, relationship status, and age (for certain screening behaviors), significant differences were seen in information-seeking behaviors, risk perception, community attributes, discrimination, and distress. Non-WNH groups reported worse community attributes, higher everyday discrimination, lower health literacy, less confidence in their ability to get health information, and lower perceived risk of cancer. CONCLUSION: This analysis presents a better understanding of how HBM factors may influence health disparities in the cancer center's catchment area. Results describe the needs of community members from racial and ethnic minority groups, which will inform future research, education, outreach, and service activities.

Disparities in Access to Opioid Treatment Programs and Office-Based Buprenorphine Treatment Across the Rural-Urban and Area Deprivation Continua: A US Nationwide Small Area Analysis.

OBJECTIVES: To measure access to opioid treatment programs (OTPs) and office-based buprenorphine treatment (OBBTs) at the smallest geographic unit for which the Census Bureau publishes demographic and socioeconomic data (ie, block group) and to explore disparities in access to treatment across the rural-urban and area deprivation continua across the United States. METHODS: Access to OTPs and OBBTs at the block group in 2019 was quantified using an innovative 2-step floating catchment area technique that accounts for the supply of treatment facilities relative to the population size, proximity of facilities relative to the location of population in block groups, and time as a barrier within catchments. Block groups were stratified into tertiles based on the rural-urban continuum codes (metropolitan, micropolitan, small town, or rural) and area deprivation index (least-deprived, middle-deprived, most-deprived). The Integrated Nested Laplace Approximation approach was used for statistical analysis. RESULTS: Across the United States, 3329 block groups corresponding to 2 915 949 adults lacked access to OTPs within a 2-hour drive of their community and 130 block groups corresponding to 86 605 adults did not have access to OBBTs. Disparities in access to treatment were observed across the urban-rural and area deprivation continua including (1) lowest mean access score to OBBTs were found among most-deprived small towns, and (2) lower mean access score to OTPs were found among micropolitan and small towns. CONCLUSIONS: The results of this study revealed disparities in access to medication-assisted treatment. The findings call for creative initiatives and local and regional policies to develop to mitigate access problems.

An integrated analysis of spatial access to the three-tier healthcare delivery system in China: a case study of Hainan Island.

BACKGROUND: Access to healthcare is critical for the implementation of Universal Health Coverage. With the development of healthcare insurance systems around the world, spatial impedance to healthcare institutions has attracted increasing attention. However, most spatial access methodologies have been developed in Western countries, whose healthcare systems are different from those in Low- and Middle-Income Countries (LMICs). METHODS: Hainan Island was taken as an example to explore the utilization of modern spatial access techniques under China's specialized Three-Tier Health Care Delivery System. Healthcare institutions were first classified according to the three tiers. Then shortest travel time was calculated for each institution's tier, overlapped to identify eight types of multilevel healthcare access zones. Spatial access to doctors based on the Enhanced Two-Step Floating Catchment Area Method was also calculated. RESULTS: On Hainan Island, about 90% of the population lived within a 60-min service range for Tier 3 (hospital) healthcare institutions, 80% lived within 30 min of Tier 2 (health centers), and 75% lived within 15 min of Tier 1 (clinics). Based on local policy, 76.36% of the population living in 48.52% of the area were able to receive timely services at all tiers of healthcare institutions. The weighted average access to doctors was 2.31 per thousand residents, but the regional disparity was large, with 64.66% being contributed by Tier 3 healthcare institutions. CONCLUSION: Spatial access to healthcare institutions on Hainan Island was generally good according to travel time and general abundance of doctors, but inequity between regions and imbalance between different healthcare institution tiers exist. Primary healthcare institutions, especially in Tier 2, should be strengthened.