Dynamic measurements of geographical accessibility considering traffic congestion using open data: a cross-sectional assessment for haemodialysis services in Cali, Colombia

Background

Many cities with traffic congestion lack accessibility assessments accounting for traffic congestion and equity considerations but have disaggregated georeferenced municipal-level open data on health services, populations, and travel times big data. We convened a multistakeholder intersectoral collaborative group that developed a digital, web-based platform integrating open and big data to derive dynamic spatial-temporal accessibility measurements (DSTAM) for haemodialysis services. We worked with stakeholders and data scientists and considered people's places of residence, service locations, and travel time to the service with the shortest travel time. Additionally, we predicted the impacts of strategically introducing haemodialysis services where they optimise accessibility.

Methods

Cross-sectional analyses of DSTAM, accounting for traffic congestion, were conducted using a web-based platform. This platform integrated traffic analysis zones, public census and health services datasets, and Google Distance Matrix API travel-time data. Predictive and prescriptive analytics identified optimal locations for new haemodialysis services and estimated improvements. Primary outcomes included the percentage of residents within a 20-min car drive of a haemodialysis service during peak and free-flow traffic congestion. Secondary outcomes focused on optimal locations to maximise accessibility with new services and potential improvements. Findings were disaggregated by sociodemographic characteristics, providing an equity perspective. The study in Cali, Colombia, used geographic and disaggregated sociodemographic data from the adjusted 2018 Colombian census. Predicted travel times were obtained for two weeks in 2020.

Findings

There were substantial traffic variations. Congestion reduced accessibility, especially among marginalised groups. For 6-12 July, free-flow and peak-traffic accessibility rates were 95.2% and 45.0%, respectively. For 23-29 November, free-flow and peak traffic accessibility rates were 89.1% and 69.7%. The locations where new services would optimise accessibility had slight variation and would notably enhance accessibility and health equity.

Interpretation

Establishing haemodialysis services in targeted areas has significant potential benefits. By increasing accessibility, it would enhance urban health and equity.

Funding

No external or institutional funding was received.

Patient Accessibility to Eye Care in the United States

PURPOSE

The United States (US) federal government uses health provider shortage areas (HPSAs) to define patient accessibility to primary care physicians. It is unclear whether HPSAs can be applied to eye care providers (ECPs). Our study determined the applicability of federal HPSA designations to ECP availability in the US.

DESIGN

Cross-sectional study.

PARTICIPANTS

US general population and ophthalmologists/optometrists in the Medicare database.

METHODS

The primary care HPSA score, visual impairment prevalence, and ECP location were determined for each census tract or county using data from the US Department of Health and Human Services, the Centers for Disease Control and Prevention, and Centers for Medicare and Medicaid Services.

MAIN OUTCOME MEASURES

Association of HPSA with vision loss and ECP density was examined. The 2-step floating catchment area approach was used to newly define eye care shortage areas (patient accessibility score [PAS], higher being worse accessibility) for every county in the US, by weighting the 2-step FCA scores by prevalence of vision loss and ECP density. Multivariable logistic regression was used to identify sociodemographic variables associated with areas of ECP shortage.

RESULTS

Among 72 735 census tracts included, statistically significant but weak correlations of HPSA score with visual impairment (VI) (r = 0.38; P < 0.0001) and ECP density per county population (r = -0.18; P < 0.0001) were found. Only 54.0% of census tracts with < 25th percentile ECP density per county were HPSAs (P < 0.0001). Of census tracts > than 75th percentile for VI only 58.0% were HPSAs (P < 0.0001). Multivariable regression found a higher odds of ECP PAS ≥ 75th percentile (worse accessibility) in rural counties (adjusted odds ratio [aOR], 2.47; 95% confidence interval [CI], 1.93-3.67; P < 0.001) and counties with a greater prevalence of residents with less than a high school education (aOR, 1.21; 95% CI, 1.19-1.25; P < 0.001), residents ≥ 65 years of age (aOR, 1.10; 95% CI, 1.07-1.13; P < 0.001), and uninsured residents (aOR, 1.04; 95% CI, 1.01-1.06; P < 0.001). Counties with a greater proportion of men (aOR, 0.93; 95% CI, 0.89-0.967; P < 0.001) or White residents (aOR, 0.99; 95% CI, 0.98-0.99) had a lower odds of ECP PAS ≥ 75th percentile.

CONCLUSIONS

Current HPSAs only weakly correlate with ECP supply. We propose a new approach to identify counties with high need but limited access to eye care.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

Spatial accessibility modeling to healthcare facilities in the case of health shocks of Midnapore municipality, India

This research aims to identify the accessibility of the entire population, especially the slum population to existing healthcare facilities (HCF) as well as the slum neighborhoods having low geographic accessibility, and finally, to provide an analytical model for the people living in areas that are outside the coverage range of existing healthcare facilities (HCF) across the study area. Spatial data has been collected and used based on the road network, elevation, location of HCF, municipal boundary, slum point, and satellite images from various sources. Also, non-spatial data such as socioeconomic variables are collected from questionnaires survey within a particular period. The spatial analysis tool like as near, network analysis, and predictive analysis in the ArcGIS platform was used to examine geographic accessibility. The results of the spatial analysis show that the distribution of public healthcare facility centers in the study area has not been uniformly distributed. Across 84% of areas in the study area have sound spatial accessibility with traveling time coverage is about 12 min. However, 16% of areas have a traveling time of 12 to 30 min under low accessibility with existing slum neighborhoods. Therefore, the low spatial accessibility areas are demanding new healthcare facilities in the study area. The Analytical Hierarchy Process (AHP) is employed to find the most optimal and efficient locational suitability for building new healthcare facility centers. The finding of AHP analysis for site suitability of healthcare facilities revealed five major classes as most suitable (2%), suitable (5%), moderate (35%), poor (54%), and very poor (4%) in the study area. Moreover, the realistic framework of this study helps to measure geographic accessibility and suitability in any geographical area.

Geographic accessibility to cancer treatment in Brazil: A network analysis

Background

Geographic accessibility to healthcare services is a fundamental component in achieving universal health coverage, the central commitment of the Brazilian Unified Health System (SUS). For cancer patients, poor accessibility has been associated with inadequate treatment, worse prognosis, and poorer quality of life.

Methods

We explored nationwide healthcare data from the SUS health information systems, and mapped the geographic accessibility to cancer treatment in two time-frames: 2009-2010 and 2017-2018. We applied social network analysis (SNA) to estimate the commuting route, flow, and distances travelled by cancer patients to undergo surgical, radiotherapy, and chemotherapy treatment.

Findings

A total of 12,751,728 treatment procedures were analyzed. Overall, more than half of the patients (49·2 to 60·7%) needed to travel beyond their municipality of residence for treatment, a fact that did not change over time. Marked regional differences were observed, as patients living in the northern and midwestern regions of the country had to travel longer distances (weighted average of 296 to 870 km). Cancer care hubs and attraction poles were mostly identified in the southeast and northeast regions, with Barretos being the main hub for all types of treatment throughout time.

Interpretation

Important regional disparities in the accessibility to cancer treatment in Brazil were revealed, suggesting the need to review the distribution of specialized care in the country. The data presented here contribute to ongoing research on improving access to cancer care and can provide reference to other countries, offering relevant data for oncological and healthcare service evaluation, monitoring, and strategic planning.

Funding

This work was funded by the Oswaldo Cruz Foundation - Fiocruz (Inova - no. 8451635123 to BPF) and the National Council for Scientific and Technological Development - CNPq (no. 407060/2018-9 to BPF); Coordination for the Improvement of Higher Education Personnel - CAPES (scholarship to PCA, Finance Code 001); and Instituto Nacional de Ciência e Tecnologia de Inovação em Doenças de Populações Negligenciadas (INCT-IDPN).

Resumo

A acessibilidade geográfica aos serviços de saúde é um componente fundamental para o alcance da cobertura universal de saúde, compromisso central do Sistema Único de Saúde (SUS). Para pacientes com câncer, a baixa acessibilidade aos serviços especializados tem sido associada ao tratamento inadequado, piora no prognóstico e na qualidade de vida.Neste estudo, dados de saúde dos sistemas de informação em saúde do SUS foram utilizados para mapear a acessibilidade geográfica ao tratamento do câncer em dois períodos: 2009-2010 e 2017-2018. Aplicamos a análise de redes sociais (ARS) para estimar os fluxos de deslocamento e as distâncias percorridas por pacientes com câncer para receberem tratamento cirúrgico, radioterápico e quimioterápico.Um total de 12.751.728 procedimentos de tratamento foram analisados. Em geral, mais da metade dos pacientes (49,2 a 60,7%) precisaram se deslocar de seus municípios de residência para receber tratamento, fato que não mudou comparando os dois períodos de tempo analisados. Foram observadas importantes diferenças regionais no acesso. Pacientes residentes das regiões norte e centro-oeste do país tiveram que percorrer maiores distâncias para alcançar os serviços (média ponderada = 296 a 870 km). A maioria dos hubs e polos de atração para atendimento oncológico foram identificados nas regiões Sudeste e Nordeste, sendo o município de Barretos o principal hub para todos os tipos de tratamento ao longo do tempo.As disparidades de acessibilidade para o tratamento de câncer, alertam para a necessidade de revisar a distribuição dos serviços de atenção especializada no país. A metodologia e os resultados apresentados neste estudo contribuem para as pesquisas sobre a melhoria do acesso ao tratamento do câncer e podem servir como referência para outros países, oferecendo dados relevantes para avaliação, monitoramento e planejamento estratégico de serviços oncológicos e de saúde em geral.

Travel Time to Title X Facilities and Teenage Birth Rates in North Carolina

OBJECTIVES

In the United States, Title X facilities are understood to be an effective starting point for improving teenagers' reproductive health outcomes, including unintended pregnancy. We investigate geographic accessibility of Title X facilities and the relationship between geographic accessibility of Title X facilities and teenage birth rates in the state of North Carolina (NC).

METHODS

Vehicular travel time from each ZCTA to its nearest Title X facility was calculated using a geographic information system and summarized as the indicator of geographic accessibility. We used bivariate and multiple spatial lag regressions to evaluate the relationship between ZCTA-level teenage birth rates (n = 754) in 2016 and geographic accessibility to a Title X facility, as well as socioeconomic and demographic factors.

RESULTS

Nearly 60% of teenage women lived 30 min or less from a Title X funded facility, while approximately 12% of women lived 60 min or more from the nearest facility. In the regression models, percent non-Hispanic White, percent Hispanic, percent in Poverty, percent not enrolled in school, and population density were associated with teenage birth rates; however, geographic accessibility was only associated in the bivariate model.

CONCLUSIONS

Our findings show that geographic accessibility of Title X facilities is lower in NC than in other states. However, our results suggest that geographic accessibility is not related to teenage birth rates. Overall, these findings may indicate that publicly funded family planning facilities are underutilized by proximal populations or factors other than proximity act as a barrier to utilization.

Geographic Access Disparities to Clinical Trials in Diabetic Eye Disease in the United States

PURPOSE

To identify geographic and socioeconomic variables predictive of residential proximity to diabetic eye disease clinical trial locations.

DESIGN

Cross-sectional, retrospective study.

PARTICIPANTS

De-identified census tract-level data from public datasets and trial-level data from ClinicalTrials.gov.

METHODS

Using public data from ClinicalTrials.gov, we identified all active interventional clinical trials in diabetic eye disease since 2017. After geolocating every trial site, we used an origin-destination cost-matrix to calculate the driving distance and travel time from the population-weighted United States census tract centroid to the nearest site. We then used public databases to identify census tract-level socioeconomic factors predictive of driving distance and time.

MAIN OUTCOME MEASURES

Driving distance > 60 miles and time traveled > 60 minutes to the nearest clinical trial site.

RESULTS

In a multivariate model, driving distance of more than 60 miles had a significant association with rural versus urban location (adjusted odds ratio, 5.22; 95% confidence interval [CI], 3.75-7.26; P < 0.001), percentage of population at less than 200% of federal poverty level compared with the fourth quartile (first quartile: adjusted odds ratio, 0.40 [95% CI, 0.29-0.55]; second quartile: adjusted odds ratio, 0.60 [95% CI, 0.47-0.77]; third quartile: adjusted odds ratio, 0.76 [95% CI, 0.63-0.91]; P < 0.001) and the Midwest (adjusted odds ratio, 2.15; 95% CI, 1.13-4.07; P = 0.02), South (adjusted odds ratio, 2.71; 95% CI, 1.23-5.99; P = 0.01), and West (adjusted odds ratio, 3.01; 95% CI, 1.21-7.54; P = 0.02) regions as compared with the Northeast. Driving distance was associated with county-level prevalence of diabetes in the univariate model (odds ratio, 1.12; 95% CI, 1.06-1.19; P < 0.001), although it was nonsignificant in the multivariate model. Similar predictors were found for time traveled in minutes.

CONCLUSIONS

Geographic maldistributions of clinical trial sites exist for diabetic eye disease in the United States. Those with higher travel burden are more likely to reside in a census tract that is rural, low income, and from areas outside the Northeast.

Urban and rural differences in geographical accessibility to inpatient palliative and end-of-life (PEoLC) facilities and place of death: a national population-based study in England, UK

BACKGROUND

Little is known about the role of geographic access to inpatient palliative and end of life care (PEoLC) facilities in place of death and how geographic access varies by settlement (urban and rural). This study aims to fill this evidence gap.

METHODS

Individual-level death data in 2014 (N = 430,467, aged 25 +) were extracted from the Office for National Statistics (ONS) death registry and linked to the ONS postcode directory file to derive settlement of the deceased. Drive times from patients' place of residence to nearest inpatient PEoLC facilities were used as a proxy estimate of geographic access. A modified Poisson regression was used to examine the association between geographic access to PEoLC facilities and place of death, adjusting for patients' socio-demographic and clinical characteristics. Two models were developed to evaluate the association between geographic access to inpatient PEoLC facilities and place of death. Model 1 compared access to hospice, for hospice deaths versus home deaths, and Model 2 compared access to hospitals, for hospital deaths versus home deaths. The magnitude of association was measured using adjusted prevalence ratios (APRs).

RESULTS

We found an inverse association between drive time to hospice and hospice deaths (Model 1), with a dose-response relationship. Patients who lived more than 10 min away from inpatient PEoLC facilities in rural areas (Model 1: APR range 0.49-0.80; Model 2: APR range 0.79-0.98) and urban areas (Model 1: APR range 0.50-0.83; Model 2: APR range 0.98-0.99) were less likely to die there, compared to those who lived closer (i.e. ≤ 10 min drive time). The effects were larger in rural areas compared to urban areas.

CONCLUSION

Geographic access to inpatient PEoLC facilities is associated with where people die, with a stronger association seen for patients who lived in rural areas. The findings highlight the need for the formulation of end of life care policies/strategies that consider differences in settlements types. Findings should feed into local end of life policies and strategies of both developed and developing countries to improve equity in health care delivery for those approaching the end of life.

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.

Measurement of the potential geographic accessibility from call to definitive care for patient with acute stroke

BACKGROUND

The World Health Organization refers to stroke, the second most frequent cause of death in the world, in terms of pandemic. Present treatments are only effective within precise time windows. Only 10% of thrombolysis patients are eligible. Late assessment of the patient resulting from admission and lack of knowledge of the symptoms is the main explanation of lack of eligibility.

METHODS

The aim is the measurement of the time of access to treatment facilities for stroke victims, using ambulances (firemen ambulances or EMS ambulances) and private car. The method proposed analyses the potential geographic accessibility of stroke care infrastructure in different scenarios. The study allows better considering of the issues inherent to an area: difficult weather conditions, traffic congestion and failure to respect the distance limits of emergency transport.

RESULTS

Depending on the scenario, access times vary considerably within the same commune. For example, between the first and the second scenario for cities in the north of Rhône county, there is a 10 min difference to the nearest Primary Stroke Center (PSC). For the first scenario, 90% of the population is 20 min away of the PSC and 96% for the second scenario. Likewise, depending on the modal vector (fire brigade or emergency medical service), overall accessibility from the emergency call to admission to a Comprehensive Stroke Center (CSC) can vary by as much as 15 min.

CONCLUSIONS

The setting up of the various scenarios and modal comparison based on the calculation of overall accessibility makes this a new method for calculating potential access to care facilities. It is important to take into account the specific pathological features and the availability of care facilities for modelling. This method is innovative and recommendable for measuring accessibility in the field of health care. This study makes possible to highlight the patients' extension of care delays. Thus, this can impact the improvement of patient care and rethink the healthcare organization. Stroke is addressed here but it is applicable to other pathologies.

Measurement of the potential geographic accessibility from call to definitive care for patient with acute stroke

BACKGROUND

The World Health Organization refers to stroke, the second most frequent cause of death in the world, in terms of pandemic. Present treatments are only effective within precise time windows. Only 10% of thrombolysis patients are eligible. Late assessment of the patient resulting from admission and lack of knowledge of the symptoms is the main explanation of lack of eligibility.

METHODS

The aim is the measurement of the time of access to treatment facilities for stroke victims, using ambulances (firemen ambulances or EMS ambulances) and private car. The method proposed analyses the potential geographic accessibility of stroke care infrastructure in different scenarios. The study allows better considering of the issues inherent to an area: difficult weather conditions, traffic congestion and failure to respect the distance limits of emergency transport.

RESULTS

Depending on the scenario, access times vary considerably within the same commune. For example, between the first and the second scenario for cities in the north of Rhône county, there is a 10 min difference to the nearest Primary Stroke Center (PSC). For the first scenario, 90% of the population is 20 min away of the PSC and 96% for the second scenario. Likewise, depending on the modal vector (fire brigade or emergency medical service), overall accessibility from the emergency call to admission to a Comprehensive Stroke Center (CSC) can vary by as much as 15 min.

CONCLUSIONS

The setting up of the various scenarios and modal comparison based on the calculation of overall accessibility makes this a new method for calculating potential access to care facilities. It is important to take into account the specific pathological features and the availability of care facilities for modelling. This method is innovative and recommendable for measuring accessibility in the field of health care. This study makes possible to highlight the patients' extension of care delays. Thus, this can impact the improvement of patient care and rethink the healthcare organization. Stroke is addressed here but it is applicable to other pathologies.

Do Avoidable Hospitalization Rates among Older Adults Differ by Geographic Access to Primary Care Physicians?

OBJECTIVE

To investigate the association between older adults' potentially avoidable hospitalization rates and both a geographic measure of primary care physician (PCP) access and a standard bounded-area measure of PCP access.

DATA SOURCES

State physician licensure data from the Virginia Board of Medicine. Patient-level hospital discharge data from Virginia Health Information. Area-level data from the American Community Survey and the Area Health Resources Files. Virginia Information Technologies Agency road network data. US Census Bureau TIGER/Line boundary files.

STUDY DESIGN

We use enhanced two-step floating catchment area methods to calculate geographic PCP accessibility for each ZIP Code Tabulation Area in Virginia. We use spatial regression techniques to model potentially avoidable hospitalization rates.

DATA COLLECTION/EXTRACTION

Geographic accessibility was calculated using ArcGIS. Physician locations were geocoded using TAMU GeoServices and ArcGIS.

PRINCIPAL FINDINGS

Increased geographic access to PCPs is associated with lower rates of potentially avoidable hospitalization among older adults. This association is robust, allowing for spatial spillovers in spatial lag models.

CONCLUSIONS

Compared to bounded-area density measures, unbounded geographic accessibility measures provide more robust evidence that avoidable hospitalization rates are lower in areas with more PCPs per person. Results from our spatial lag models reveal the presence of positive spatial spillovers.