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Towards a smart healthy city: A generalised flow-based 2SFCA method for incorporating actual mobility data in healthcare accessibility evaluation
... Urban accessibility is typically evaluated using spatial-and network-based methods (Chen et al., 2024) that provide actionable insights for planners. ...
This study investigates the accessibility of cultural and heritage sites in Seoul through the innovative lens of the 15-minute city framework, a model that prioritizes proximity to essential resources to foster equity, inclusion, and sustainability. Using GIS-based analysis, this study employed vital dimensions such as walkability, multimodal transit connectivity, land-use diversity, safety, equity, retail activity, and carbon emissions, to build a composite 15-minute accessibility index for cultural and heritage sites. The preliminary findings revealed pronounced spatial inequities, where the sites were predominantly clustered in Seoul’s urban core. Unexpectedly transit proximity and walkability present critical challenges in the central isochrone areas. For the sites in the peripheral areas, walkability and proximity to transit are better, but safety, equity, carbon emissions, and social dependency are clear challenges. These gaps restrict equitable, inclusive, and sustainable cultural accessibility. This study proposes a suite of tailored interventions, including decentralizing cultural infrastructure to underserved areas, expanding multimodal transit networks to enhance connectivity, improving walkability, fostering mixed-use neighbourhoods, and proposing participatory approach to integrate cultural accessibility as an essential element of the daily life for everyone. Aligning with Seoul’s Vision 2030 agenda, these strategies address local disparities and position cultural accessibility as a linchpin for sustainable urban development. This parallels other global metropolises facing similar challenges, showing that integrating cultural resources into urban planning can bolster inclusivity and resilience. This study provides actionable insights into global discourse on creating liveable, sustainable, and culturally vibrant urban environments.
... The city's six urban districts have undergone rapid urbanization and exhibit developed economic profiles, leading to a geographical clustering of hospitals. Consequently, when examining residents' medical-seeking behavior, it is imperative to consider the competitive dynamics among hospitals within the analysis framework [39,40]. To address this challenge, this paper uses the Huff extension of the 2SFCA method (Huff-2SFCA). ...
Reasonably allocating medical resources can effsectively optimize the utilization efficiency of such resources. This paper took Taiyuan City as an example and established a model to evaluate the rationality of medical resource spatial allocation, incorporating two key dimensions: the spatial layout and the supply and demand of medical resources. In terms of the spatial layout, three indexes were included: Firstly, the service coverage rates of different levels of medical institutions, based on residents’ medical orientations, were calculated using network analysis methods. Secondly, the Huff-2SFCA method was improved to calculate the accessibility of medical resources for four different modes of transportation. Then, the Health Resource Agglomeration Degree (HRAD) and Population Agglomeration Degree (PAD) were used to quantify the equity of medical resources. In terms of the supply and demand of medical resources, one index was included: the supply–demand ratio of medical resources during sudden public health events, which was calculated using the number of beds per thousand people as an indicator. These four indexes were weighted using the entropy weight method to obtain the rationality grade of medical resource spatial allocation in Taiyuan City. The study found that the rationality evaluation level of medical resource allocation in the central urban area of Taiyuan City followed a “concentrically decreasing” pattern. The rating ranged from “very reasonable” to “less reasonable”, with the area of each level expanding gradually. The areas rated within the top two categories only accounted for 19.92% of the study area, while the area rated as “less reasonable” occupied 38.73% of the total area. These results indicate that the model accounted for residents’ travel for various medical orientations and the availability of resources during public health emergencies. It considered both the spatial layout and supply and demand of medical resources, offering recommendations for the precise allocation of urban medical resources.
Equitable and high-quality medical services are more urgent in underdeveloped cities for the higher population ageing and demanding social justice. However, there is little attention paid to the multi-level medical services, particularly regarding the time indicators under the latest policies for underdeveloped cities. The improved efforts were hampered partly by single scenario of location optimization, ignoring the integrated optimization for both road infrastructure and institution location. Toward the healthy China 2030 and rural revitalization policy, this study systematically investigated medical services for underdeveloped cities by constructing a multi-level evaluation and multi-scenario optimization framework with Geographical Information System technology in a case study of Xuchang City in China. Following the time goals from the latest policies, the services of high-quality hospitals and primary health centers were multi-level evaluated by network analysis method and further optimized through multi-scenario involving different new multi-level medical facilities and roads. Driven by urban-rural inequalities, candidate facilities were first selected based on multi-source data and then determined by location‑allocation analysis method, while new roads were assumed by space syntax method. The improvement rose rapidly and finally slowly with the increasing number of candidates. Few new roads and facilities could be more suitable, and the priority was explored under the local economy and planning. The findings could provide valuable support for urban healthy development under the latest policies.
Achieving equal access to healthcare is an essential goal of the Sustainable Development Goals and a key criterion for building healthy communities. In this study, we examine the spatial and social heterogeneities of accessing hierarchical healthcare services through the lens of equity in the central urban area of Shanghai. The BFCA method is applied to analyze the accessibility to healthcare with various levels of services and via travel modes from communities and identify communities with a spatial mismatch. The relationship between factors, including socio-economic factors, health status, medical choice, and accessing healthcare services are examined using a multi-nominal logistic model. The results show that 1) Accessing healthcare performs a spatial mismatch and core-periphery disparity in the central urban area. 2) The lacking the accessibility to high-tier healthcare and a walkable environment are two main spatial equity issues, especially the latter one. 3) The inequities of access to healthcare facilities are systematic differences in factors including age, family income, family expenditure, medical choice, and health status. The results highlight the geographic and demographic disparities in healthcare services through the lens of equity and provide suggestions to improve the healthcare coverage and develop a sustainable and healthy-oriented city.
Background
At a time when life is starting to return to normal following the global pandemic, the medical service function as a key component of public infrastructure in livable communities still have an undeniable importance. In practice, however, due to a heterogeneity in the distribution of medical facilities, a significant spatial imbalance can exist in urban and country regions. By integrating the life circle theory and complex system theory, we try to propose a new framework to fill this gap and explain the formation mechanism of the medical service function equality. Furthermore, the feasibility of the framework was verified by evaluating the spatial equality of medical services of the primary, secondary, tertiary and total medical service function in Chengdu City, China.
Methods
Based on Z-score method, a quantitative method was constructed to quantitative detect the spatial pattern of Chengdu’s medical services. This method can help to accurately identify the spatial equality of the medical service function, thereby facilitating further refined policy formulation to improve these functions.
Results
The results for accessibility within the life circle indicate that 97.69% of the population and 63.76% of metropolitan Chengdu enjoy total access to medical services, but this desirable accessibility gradually decreases around the central line of Chengdu and the central areas of other districts and counties. The multi-center hierarchical structure of level II, level III and the total function reflects the fact that accessibility to medical facilities in the main urban areas is better than that in the surrounding counties, and in the central urban areas of these surrounding counties are better than that in their peripheral areas. the spatial equality for the total function, level III, and level II exhibits a clear hierarchical structure, namely core-edge pattern. Urban construction is gradually spread from the center to the outside, which fundamentally determines the skeleton of the spatial pattern of medical service facilities in Chengdu.
Conclusions
Findings of this research contribute new theoretical and methodological insights into addressing the spatial equality of public service functions in complex regional and urban system.
With the continuous aging of society, the demand among elderly citizens for care facilities is increasing. The accessibility of elderly care facilities is a significant indicator for evaluating whether the layout of urban elderly care facilities is reasonable, and research on the spatial accessibility of related facilities has become an important academic issue in recent years. In this paper, based on the lack of accurate measurement in calculating the spatial accessibility of existing elderly care facilities, we improve the mathematical model based on the two-step floating catchment area method (2SFCA) and introduce the probability function of the elderly population’s choice, taking into account the influence of institutional capacity and service quality. In terms of the catchment radius, the calculation accuracy is improved by using the shortest distance along the route combined with the real road network instead of choosing the Euclidean distance. In addition, specific travel thresholds are set for the travel characteristics of the elderly. An evaluation model of the accessibility of urban elderly care facilities is constructed with the help of ArcGIS software to evaluate and analyze the accessibility of the current layout of urban elderly care facilities in Xi’an, China. The results show that the improved 2SFCA model is more effective in evaluating the spatial accessibility of elderly care facilities and has higher accuracy than the previous calculation model, which provides a methodological basis and academic reference for the specific planning of urban elderly care facilities.
Improving the attractiveness of urban waterfronts has become an important objective to promote economic development and improve the environmental quality. However, few studies have focused on the inherent characteristics of urban waterfront attractiveness. In this study, mobile phone signaling data and the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) were used to construct the attractiveness evaluation system of the riverside in Wuhan. The OLS (ordinary least squares) regression model was used to analyze the relationship between the POI (point of interest) and the attractiveness of river waterfronts. Furthermore, the high-or-low-value aggregation classification of research units was performed according to attractiveness and the POI indicators to reveal the influencing factors of the attractiveness of the Wuhan urban riverside. Results showed the following. (1) The high-value distribution of attractiveness of the river waterfronts in Wuhan presented regional aggregation characteristics, and the attractiveness of economically developed areas was high. (2) Consumer POIs (CPOIs) and outdoor recreation POIs (RPOIs) had a positive effect on the attractiveness of the riverside in Wuhan, while housing POIs (HPOIs), public service POIs (OPOIs), and the high degree of POI mixing had a negative impact on the attractiveness of the urban riverside. (3) The high–high agglomeration spaces were mainly concentrated in the economically developed areas of the city center, which are mainly open spaces where urban cultural activities are held, while the low–low agglomeration spaces were mostly gathered in the suburban areas. The spatial distribution of the high–low agglomeration spaces, which are mainly green open spaces, was relatively fragmented, while the low–high agglomeration spaces, which are mainly freight terminals, linear walks, and residential areas, were near the city center.
Disaggregated population counts are needed to calculate health, economic, and development indicators in Low- and Middle-Income Countries (LMICs), especially in settings of rapid urbanisation. Censuses are often outdated and inaccurate in LMIC settings, and rarely disaggregated at fine geographic scale. Modelled gridded population datasets derived from census data have become widely used by development researchers and practitioners; however, accuracy in these datasets are evaluated at the spatial scale of model input data which is generally courser than the neighbourhood or cell-level scale of many applications. We simulate a realistic synthetic 2016 population in Khomas, Namibia, a majority urban region, and introduce several realistic levels of outdatedness (over 15 years) and inaccuracy in slum, non-slum, and rural areas. We aggregate the synthetic populations by census and administrative boundaries (to mimic census data), resulting in 32 gridded population datasets that are typical of LMIC settings using the WorldPop-Global-Unconstrained gridded population approach. We evaluate the cell-level accuracy of these gridded population datasets using the original synthetic population as a reference. In our simulation, we found large cell-level errors, particularly in slum cells. These were driven by the averaging of population densities in large areal units before model training. Age, accuracy, and aggregation of the input data also played a role in these errors. We suggest incorporating finer-scale training data into gridded population models generally, and WorldPop-Global-Unconstrained in particular (e.g., from routine household surveys or slum community population counts), and use of new building footprint datasets as a covariate to improve cell-level accuracy (as done in some new WorldPop-Global-Constrained datasets). It is important to measure accuracy of gridded population datasets at spatial scales more consistent with how the data are being applied, especially if they are to be used for monitoring key development indicators at neighbourhood scales within cities.
The coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges to worldwide health systems in quick response to epidemics. The assessment of personal exposure to COVID-19 in enclosed spaces is critical to identifying potential infectees and preventing outbreaks. However, traditional contact tracing methods rely heavily on a manual interview, which is costly and time consuming given the large population involved. With advanced indoor localisation techniques, it is possible to collect people's footprints accurately by locating their smartphones. This study presents a new framework for the assessment of personal exposure to COVID-19 carriers using their fine-grained trajectory data. An integral model was established to quantify the exposure risk, in which the spatial and temporal decay effects are simultaneously considered when modelling the airborne transmission of COVID-19. Regarding the obstacle effect of the indoor layout on airborne transmission, a weight graph based on the space syntax technique was further introduced to constrain the transmission strength between subspaces that are less inter-visible. The proposed framework was demonstrated by a simulation study, in which external comparison and internal analysis were conducted to justify its validity and robustness in different scenarios. Our method is expected to promote the efficient identification of potential infectees and provide an extensible spatial–temporal model to simulate different control measures and examine their effectiveness in a built environment.
The importance of understanding human mobility patterns has led many studies to examine their spatial-temporal scaling laws. These studies mainly reveal that human travel can be highly non-homogeneous, leaving gaps in investigating and quantifying the extent of variability in time and space when traveling the same air distance. Using taxi data from five large cities, we focus on several novel measures of distance and time to explore the spatio-temporal variations of taxi travel routes relative to their typical routes. To compare all trips using a single measure, we calculate the distributions of the ratios between actual distances and the average distance as well as between actual times and the average time for all origin destinations (ODs) during peak and nonpeak periods. In this way, we measure the scaling of the distribution of all single trip paths with respect to their mean trip path. Our results demonstrate very broad distributions for both the distance ratio and time ratio, characterized by long-tail power-law distributions. Moreover, all analyzed cities have larger exponents in peak hours than in nonpeak hours. We suggest that shorter trip lengths and times, characterized by larger exponents during rush hours, are due to the higher availability of travelers in rush hours compared to non-rush hours. We also find a high correlation between distances and times, and the correlation is lower during peak hours than during nonpeak hours. The reduced correlations may be due to the high availability of passengers in peak periods and more drivers choose long distances to save time compared to nonpeak periods. Furthermore, we employed an indeterminate traffic assignment model, which supports our finding of the power-law distribution of the distance ratio and time ratio for human mobility. Our results can help to assess traffic conditions within cities and provide guidance for urban traffic management.
Public medical facilities that are closely related to the health of residents have been recognised as one of the most crucial elements in sustainable urban planning. For the sake of social equality of medical services (especially for emergency medical conditions), the spatial distributions of medical resources need to be accurately measured and continuously optimized. This study presents an effective method to examine night emergency hospital visit and analyse its spatiotemporal characteristics using float car data (FCD). By extracting the hospital service areas, the two-step floating catchment area (2SFCA) methodology was improved to calculate hospital accessibility. Then, the balance between hospital accessibility and population density was analysed. In addition, we investigated the relationship between individual hospital choice preferences and hospital level and analysed several factors that affect individual choices. These results help us understand the special requirements and need of emergency hospital travel in cities and identify areas where medical resources are scarce. They can be used as guidance for urban hospital planning and construction. And the approach of hospital access behaviour investigation and the improved 2SFCA method can also provide insights for other activity-based travel behaviour research.
Background
Equity of healthcare spatial access is essential for the health outcomes of medical investments and the welfare of populations, and efficiency of medical resource allocation is important for obtaining a supply-demand equilibrium with lower cost and higher outputs with limited inputs. However, the literature that involves both equity and efficiency in its analysis of healthcare spatial allocation is rare, and the spatial accessibility of multilevel healthcare is difficult to measure by traditional methods in a large region with diversified population distribution.
Methods
To assist in solving these issues, this paper aims to build an equity and efficiency integrated analytical framework by proposing a new “GTL-2SFCA” approach to analyze the spatial accessibility of multilevel healthcare; maximum and minimum floating catchments of different levels of healthcare were assigned to ensure a combination of universal search coverage and efficient hospitalization behavior simulation.
Results
The analytical framework was applied and tested in Hubei, China. Almost half of the residents (47.95%) and townships (44.98%) have access to both public general hospitals (PGHs) and primary healthcare centers (PHCs) services, 36.89% of the residents enjoy only one sufficient service, either PGHs or PHCs, and the remaining residents (15.16%) are faced with the risk of lacking access to both services. The results reveal that there are core-periphery effects of multilevel healthcare throughout Hubei and isolate clusters that have adequate access in the western region. The polarization effect of higher-level healthcare and the polycentric pattern of lower-level healthcare coexist. The multilevel healthcare shortage was identified in some areas in boundary and peripheral regions.
Conclusions
This study integrates equity and efficiency into the GTL-2SFCA framework, enriches the FCA series methodologies and provides a more operational solution for evaluating the access of residents in more sophisticated spatial units to each level of healthcare. By more significantly differing and quantifying the catchment area and distance decay effect, this methodology avoids overestimating or underestimating accessibility and discovers some imperceptible spatial inequities. This study has application value for researchers and decision-makers in other scenarios and regions with significant heterogeneity in medical resources and where the population has greater mobility.
Public transit is indispensable for car-free households to access healthcare. Meanwhile, different households have unequal transit-based healthcare accessibility due to different socio-economic factors such as race/ethnicity and car ownership. Few studies have comprehensively explored the inequality in transit-based healthcare accessibility by integrating both racial/ethnic inequity and car ownership. This study fills the gap with an up-to-date analysis of transit-based healthcare accessibility in the Chicago Metropolitan Area at the census tract level. The results show that the percentage of car-free households is positively related to transit-based healthcare accessibility; while a higher percentage of minorities (i.e., Black/Hispanic) is negatively related to transit-based healthcare accessibility. Among all neighbourhoods with higher percentages of higher-than-average car-free households, Hispanic-majority neighbourhoods fare the worst; while White-majority neighbourhoods have much better healthcare accessibility than both Black-majority and Hispanic-majority neighbourhoods. © 2021 The Authors. The Canadian Geographer / Le Géographe canadien published by Wiley Periodicals LLC on behalf of Canadian Association of Geographers / l'Association canadienne des géographes
Aviation is responsible for at least 3.5% of global warming, and demand is predicted to rise rapidly over the next few decades. To reverse this trend, air travel demand will need to be managed. An important question is: ‘who would be affected by air travel demand reduction policies’? The answer to that question largely depends on who is participating in air travel, and how unequally it is distributed. Existing analysis suggests that participation in air travel in the UK is highly unequal and driven by richer, highly educated and urban households. However, so far little is known about how these patterns of inequality have changed over time – has air travel participation increased among low income households, e.g. due to the rise of low-cost carriers and ‘normalisation’ of air travel as a social practice? Would these groups therefore now be more affected by flight taxes or frequent flyer levies? To address these questions, this paper examines trends in air travel inequality between 2001 and 2018 in the UK based on two representative surveys, providing the first micro-level analysis of air travel inequality over time for this country. We find that while disadvantaged groups have contributed to the expansion of air travel over the past two decades, they remain far less likely to be affected by air travel demand management policies because air travel inequality is still at a very high level. These findings challenge common discourses that present air travel as a widespread norm, and demand management policies as socially unfair.
Human mobility impacts many aspects of a city, from its spatial structure1,2,3 to its response to an epidemic4,5,6,7. It is also ultimately key to social interactions⁸, innovation9,10 and productivity¹¹. However, our quantitative understanding of the aggregate movements of individuals remains incomplete. Existing models—such as the gravity law12,13 or the radiation model¹⁴—concentrate on the purely spatial dependence of mobility flows and do not capture the varying frequencies of recurrent visits to the same locations. Here we reveal a simple and robust scaling law that captures the temporal and spatial spectrum of population movement on the basis of large-scale mobility data from diverse cities around the globe. According to this law, the number of visitors to any location decreases as the inverse square of the product of their visiting frequency and travel distance. We further show that the spatio-temporal flows to different locations give rise to prominent spatial clusters with an area distribution that follows Zipf’s law¹⁵. Finally, we build an individual mobility model based on exploration and preferential return to provide a mechanistic explanation for the discovered scaling law and the emerging spatial structure. Our findings corroborate long-standing conjectures in human geography (such as central place theory¹⁶ and Weber’s theory of emergent optimality¹⁰) and allow for predictions of recurrent flows, providing a basis for applications in urban planning, traffic engineering and the mitigation of epidemic diseases.
Accessibility is increasingly recognised as a key purpose of transport policies. Most of the common practices found both in academic studies and policy planning draw on relatively simple accessibility measures taken as ‘objective’ indicators that only focus on the interaction between land use and transport. Relatively little attention has been paid to heterogeneity in individual characteristics and in self-reported perceptions of accessibility (‘subjective’ indicators), and the corresponding differences with respect to available modal options. This study includes a comparison of (1) ‘objective’ indicators of accessibility to key activities by various modes of transport; and (2) individuals' own perceptions of their capability to access valuable out-of-home activities and the modal options available to them. This study examines the key differences between the two representations of accessibility. The calculated measure was developed using door-to-door travel times to supermarkets and healthcare centres using OpenTripPlanner. The self-reported measure was based on a dedicated capability-oriented travel survey of people aged 65–79 in Sweden's large metropolitan regions: Stockholm, Gothenburg and Malmö. The data were analysed using descriptive statistics and binary and multinomial logistic regressions. The results of this study allow us to gain a greater insight into the ways in which the two accounts differ and can complement one another. We find that conventional methods, by overlooking the heterogeneity in people's perceptions of their accessibility, tend to overestimate accessibility levels and underestimate accessibility inequalities. This study shows how perceived accounts of accessibility can be incorporated into conventional accessibility models and improve accessibility analyses.
The measurement of medical service accessibility is typically based on driving or Euclidean distance. However, in most non-emergency cases, public transport is the travel mode used by the public to access medical services. Yet there has been little evaluation of the public transport system-based inequality of medical service accessibility. This work uses massive real smart card data (SCD) and an improved potential model to estimate the public transport-based medical service accessibility in Beijing, China. These real SCD data are used to calculate travel costs in terms of time and distance, and medical service accessibility is estimated using an improved potential model. The spatiotemporal variations and patterns of medical service accessibility are explored, and the results show that it is unevenly spatiotemporally distributed across the study area. For example, medical service accessibility in urban areas is higher than that in suburban areas, accessibility during peak periods is higher than that during off-peak periods, and accessibility in weekends is generally higher than that on weekdays. To explore the association of medical service accessibility with socio-economic factors, the relationship between accessibility and house price is investigated via a spatial econometric analysis. The results show that at a global level, house price is positively correlated with medical service accessibility. In particular, the medical service accessibility of a higher-priced spatial housing unit is lower than that of its neighboring spatial units, due to the positive spatial spillover effect of house price. This work sheds new light on the inequality of medical service accessibility from the perspective of public transport, which may benefit urban policymakers and
Background
It is necessary to ensure sufficient healthcare. The use of current, precise and realistic methods to model spatial accessibility to healthcare and thus improved decision-making is helping this process. Generally, these methods—which include the family of floating catchment area (FCA) methods—incorporate a number of criteria that address topics like access, efficiency, budget, equity and the overall system utilization. How can we measure spatial accessibility? This paper investigates a sophisticated approach for quantifying the spatial accessibility of general practitioners. (GPs). Our objective is the investigation and application of a spatial accessibility index by an improved Huff three-step floating catchment area (MH3SFCA) method.
Methods
We modify and implement the huff model three-step floating catchment area (MH3SFCA) method and exemplary calculation of the spatial accessibility indices for the test study area. The method is extended to incorporate a more realistic way to model the distance decay effect. To that end, instead of a binary approach, a continuous approach is employed. Therefore, each distance between a healthcare site and the population is incorporated individually. The study area includes Swabia and the city of Augsburg, Germany. The data for analysis is obtained from following data sources: (1) Acxiom Deutschland GmbH (2020) provided a test dataset for the locations of general practitioners (GPs); (2) OpenStreetMap (OSM) data is utilized for road networks; and (3) the Statistische Ämter des Bundes und der Länder (German official census 2011) provided a population distribution dataset stemming from the 2011 Census.
Results
The spatial accessibility indices are distributed in an inhomogeneous as well as polycentric pattern for the general practitioners (GPs). Differences in spatial accessibility are found mainly between urban and rural areas. The transitions from lower to higher values of accessibility or vice versa in general are smooth rather than abrupt. The results indicate that the MH3SFCA method is suited for comparing the spatial accessibility of GPs in different regions. The results of the MH3SFCA method can be used to indicate over- and undersupplied areas. However, the absolute values of the indices do not inherently define accessibility to be too low or too high. Instead, the indices compare the spatial relationships between each supply and demand location. As a result, the higher the value of the accessibility indices, the higher the opportunities for the respective population locations. The result for the study area are exemplary as the test input data has a high uncertainty. Depending on the objective, it might be necessary to further analyze the results of the method.
Conclusions
The application of the MH3SFCA method on small-scale data can provide an overview of accessibility for the whole study area. As many factors have to be taken into account, the outcomes are too complex for a direct and clear interpretation of why indices are low or high. The MH3SFCA method can be used to detect differences in accessibility on a small scale. In order to effectively detect over- or undersupply, further analysis must be conducted and/or different (legal) constraints must be applied. The methodology requires input data of high quality.
Background
Access as a primary indicator of Emergency Medical Service (EMS) efficiency has been widely studied over the last few decades. Most previous studies considered one-way trips, either getting ambulances to patients or transporting patients to hospitals. This research assesses spatiotemporal access to EMS at the shequ (the smallest administrative unit) level in Wuhan, China, attempting to fill a gap in literature by considering and comparing both trips in the evaluation of EMS access.
Methods
Two spatiotemporal access measures are adopted here: the proximity-based travel time obtained from online map services and the enhanced two-step floating catchment area (E-2SFCA) which is a gravity-based model. First, the travel time is calculated for the two trips involved in one EMS journey: one is from the nearest EMS station to the scene (i.e. scene time interval (STI)) and the other is from the scene to the nearest hospital (i.e. transport time interval (TTI)). Then, the predicted travel time is incorporated into the E-2SFCA model to calculate the access measure considering the availability of the service provider as well as the population in need. For both access measures, the calculation is implemented for peak hours and off-peak hours.
Results
Both methods showed a marked decrease in EMS access during peak traffic hours, and differences in spatial patterns of ambulance and hospital access. About 73.9% of shequs can receive an ambulance or get to the nearest hospital within 10 min during off-peak periods, and this proportion decreases to about 45.5% for peak periods. Most shequs with good ambulance access but poor hospital access are in the south of the study area. In general, the central areas have better ambulance, hospital and overall access than peripheral areas, particularly during off-peak periods.
Conclusions
In addition to the impact of peak traffic periods on EMS access, we found that good ambulance access does not necessarily guarantee good hospital access nor the overall access, and vice versa.
Background: Spatial accessibility to healthcare facilities has drawn much attention in health geography. In China, central and local governments have aimed to develop a well-organized hierarchical system of healthcare facilities in recent years. However, few studies have focused on the measurement of healthcare accessibility in a hierarchical service delivery system, which is crucial for the assessment and implementation of such strategies.
Methods: Based on recent improvements in 2SFCA (two-step floating catchment area) method, this study aims to propose a Hierarchical 2SFCA (H2SFCA) method for measuring spatial accessibility to hierarchical facilities. The method considers the varied catchment area sizes, distance decay effects, and transport modes for facilities at various levels. Moreover, both the relative and absolute distance effects are incorporated into the accessibility measurement.
Results: The method is applied and tested in a case study of hierarchical healthcare facilities in Shenzhen, China. The results reveal that the general spatial accessibility to hierarchical healthcare facilities in Shenzhen is unevenly distributed and concentrated. The disparity of general accessibility is largely caused by the concentrated distribution of tertiary hospitals. For facilities at higher levels, average accessibility of demanders is higher, but there are also larger disparities in spatial accessibility. The comparison between H2SFCA and traditional methods reveals that traditional methods underestimate the spatial disparity of accessibility, which may lead to biased suggestions for policy making.
Conclusions: The results suggest that the supply of healthcare resources at primary facilities is far from sufficient. To improve the spatial equity in spatial accessibility to hierarchical healthcare facilities, various actions are needed at different levels. The proposed H2SFCA method contributes to the modelling of spatial accessibility to hierarchical healthcare facilities in China and similar environments where the referral system has not been well designed. It can also act as the foundation for developing more comprehensive measures in future studies.
Background:
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing the coronavirus disease 2019 (COVID-19) pandemic, has infected millions of people and caused hundreds of thousands of deaths. While COVID-19 has overwhelmed healthcare resources (e.g., healthcare personnel, testing resources, hospital beds, and ventilators) in a number of countries, limited research has been conducted to understand spatial accessibility of such resources. This study fills this gap by rapidly measuring the spatial accessibility of COVID-19 healthcare resources with a particular focus on Illinois, USA.
Method:
The rapid measurement is achieved by resolving computational intensity of an enhanced two-step floating catchment area (E2SFCA) method through a parallel computing strategy based on cyberGIS (cyber geographic information science and systems). The E2SFCA has two major steps. First, it calculates a bed-to-population ratio for each hospital location. Second, it sums these ratios for residential locations where hospital locations overlap.
Results:
The comparison of the spatial accessibility measures for COVID-19 patients to those of population at risk identifies which geographic areas need additional healthcare resources to improve access. The results also help delineate the areas that may face a COVID-19-induced shortage of healthcare resources. The Chicagoland, particularly the southern Chicago, shows an additional need for resources. This study also identified vulnerable population residing in the areas with low spatial accessibility in Chicago.
Conclusion:
Rapidly measuring spatial accessibility of healthcare resources provides an improved understanding of how well the healthcare infrastructure is equipped to save people's lives during the COVID-19 pandemic. The findings are relevant for policymakers and public health practitioners to allocate existing healthcare resources or distribute new resources for maximum access to health services.
Background
With universal health coverage a key component of the 2030 Sustainable Development Goals, targeted monitoring is crucial for reducing inequalities in the provision of services. However, monitoring largely occurs at the national level, masking sub-national variation. Here, we estimate indicators for measuring the availability and geographical accessibility of services, at national and sub-national levels across sub-Saharan Africa, to show how data at varying spatial scales and input data can considerably impact monitoring outcomes.
Methods
Availability was estimated using the World Health Organization guidelines for monitoring emergency obstetric care, defined as the number of hospitals per 500,000 population. Geographical accessibility was estimated using the Lancet Commission on Global Surgery, defined as the proportion of pregnancies within 2 h of the nearest hospital. These were calculated using geo-located hospital data for sub-Saharan Africa, with their associated travel times, along with small area estimates of population and pregnancies. The results of the availability analysis were then compared to the results of the accessibility analysis, to highlight differences between the availability and geographical accessibility of services.
Results
Despite most countries meeting the targets at the national level, we identified substantial sub-national variation, with 58% of the countries having at least one administrative unit not meeting the availability target at province level and 95% at district level. Similarly, 56% of the countries were found to have at least one province not meeting the accessibility target, increasing to 74% at the district level. When comparing both availability and accessibility within countries, most countries were found to meet both targets; however sub-nationally, many countries fail to meet one or the other.
Conclusion
While many of the countries met the targets at the national level, we found large within-country variation. Monitoring under the current guidelines, using national averages, can mask these areas of need, with potential consequences for vulnerable women and children. It is imperative therefore that indicators for monitoring the availability and geographical accessibility of health care reflect this need, if targets for universal health coverage are to be met by 2030.
Most existing healthcare accessibility studies ignore the travel time uncertainty that are commonly encountered in road networks. This study aims to examine the impacts of travel time uncertainty on healthcare accessibility. A reliability-based two-step floating catchment area (2SFCA) method is proposed to evaluate healthcare accessibility under travel time uncertainty. The proposed measure generalizes the conventional 2SFCA measure by explicitly considering individuals’ reliability constraints when scheduling visits to healthcare facilities in the face of travel time uncertainty. The proposed measure is further used to investigate travel time uncertainty impacts in a comprehensive case study. A big dataset of taxi trajectories is collected in the case study to extract dynamic information on travel time distributions. The results of the case study highlight the significant but heterogeneous impacts of travel time uncertainty on healthcare accessibility for various parts of the city at different times of the day. They also have several methodological implications for the evaluation of healthcare accessibility under travel time uncertainty.
Background:
To tackle the issue with the low usage of primary healthcare service in China, it is essential to align resource distribution with the preferences of the community residents. There are few academic researches for describing residents' perceived characteristics of healthcare services in China. This study aims to investigate the preferences of healthcare services utilization in community residents and explore the heterogeneity. The findings will be useful for the policy makers to take targeted measures to tailor the provision of healthcare services.
Methods:
The face-to-face interviews and surveys were conducted to elicit four key attributes (care provider; mode of services; cost; travel time) of the preference from community residents for healthcare utilization. A rational test was presented first to confirm the consistency, and then 16 pairs of choice tasks with 12 sociodemographic items were given to the respondents. Two hypothetical options for each set, without an opt-out option, were presented in each choice task. The latent class analysis (LCA) was used to analyse the data.
Results:
Two thousand one hundred sixty respondents from 36 communities in 6 cities were recruited for our study. 2019 (93.47%) respondents completed valid discrete choice experiment (DCE) questionnaires. The LCA results suggested that four groups of similar preferences were identified. The first group (27.29%) labelled as "Comprehensive consideration" had an even preference of all four attributes. The second group (37.79%) labelled as "Price-driven" preferred low-price healthcare services. The third group labelled as "Near distance" showed a clear preference for seeking healthcare services nearby. The fourth group (34.18%) labelled as "Quality seeker" preferred the healthcare service provided by experts. Willingness to pay (WTP) results showed that people were willing to accept CNY202.12(87.81) for the service provided by experts.
Conclusions:
Our study qualitatively measures the distinct preferences for healthcare utilization in community residents in China. The results suggest that the care provider, mode of services, travel time and cost should be considered in priority setting decisions. The study, however, reveals substantial disagreement in opinion of TCM between different population subgroups.
Objective
For a long time in China, public hospitals have been the most prominent provider of healthcare. However, recent policy reforms mean the private sector is experiencing rapid development. Thus, the purpose of this study is to detect whether the policies published by the government aimed to improve the quality of healthcare services were catering to patient’s preferences.
Participants and methods
Our work uses dental care as an example of services provided in outpatient setting and takes advantage of a labelled discrete choice experiment with a random sample of respondents from Beijing. Participants were asked to make a choice between four healthcare providers with different attributes. Mixed logit and latent class models were used for the analysis.
Result
Care provided by high-level private hospitals and community hospitals were valued RMB154 and 216 less, respectively, than care provided by class A tertiary hospitals, while the most disliked provider was private clinics. This was the most valued attribute of dental care. Respondents also value: lower waiting times, the option to choose their doctor, lower treatment costs, shorter travel times and a clean waiting room. However, when the level of provider was analysed, the prevailing notion that patients in China were always likely to choose public services than private services no longer holds. Four classes of patients with distinct preferences for dental care provider choice were identified, which can partly be explained by age, income, experience and Hukou status—a household registration permit.
Discussion
The study to some extent challenged the overwhelming predominance of public healthcare providers in China. The preference heterogeneity we found was relatively large. Our findings are significant for providers in developing more specific services for patients and for policymakers in weighing the pros and cons of future initiatives in medical reform.
Background:
Equal access to healthcare facilities, patient's satisfaction, and respect for the desire of the patient were recognized as the basic principles of each of the health care system. Each person must be given the opportunity to access health services in accordance with the requirements of their health. We aimed to prove the existence of disparities hospital utilization based on the category of urban-rural areas.
Methods:
The research used the 2013 Indonesian Basic Health Survey (RKD) as analysis material, that was designed a cross-sectional survey. With the multi-stage cluster random sampling method, 722,329 respondents were obtained. Data were analyzed using Multinomial Logistic Regression tests.
Results:
The results showed adults living in urban were likely to use hospital outpatient facilities 1.246 times higher than adults living in rural areas (OR 1.246; 95% CI 1.026 - 1.030). The likelihood of utilizing at the same time outpatient and inpatient facilities at 1.134 times higher in adults living in urban than those in rural areas (OR 1.134; 95% CI 1.025 - 1.255). While for the category of hospital inpatient utilization, there was no significant difference.
Conclusion:
There was a disparity in hospital utilization between urban-rural areas. Urban show better utilization than rural areas in outpatient and at the same time the use of inpatient care.
The spatial accessibility to urban health services is a key issue for urban environment and public health studies especially among developing countries with explosive population growth and limited urban land space. Chinese cities have experienced rapid growth and obtained remarkable economic achievements in the last three decades, while this also brings out numerous urban planning problems, e.g., spatial access disparities to urban services. For this the Chinese government worked out a new policy, community opening policy, for the improvement of urban accessibility through opening the private intra-community streets and increasing the spatial density of public street network. Although this policy has not been implemented yet, this paper aims at predicting the extent to which the community opening policy increases the spatial accessibility to health services at different places. Our work simulates the new system of street network and compares results of the spatial accessibility of health services within the current and potential (planned) network systems. More specifically, Delaunay triangulation skeleton model is constructed from GIS building footprints data for generating intra-community street segments; then, with adding these private streets to the existing inter-community street network, the two-step floating catchment area (2SFCA) method based on network path distance is employed to assess spatial accessibility to health services under both the current and potential urban contexts of Shenzhen, China. The results show that the impacts of the community opening policy on spatial accessibility of health services have spatial variations, and the most positively and negatively affected places are gathered together in the center area of the city.
Introduction
Despite policy measure to strengthen and promote primary care, Chinese patients increasingly choose to access higher level hospitals. The resulting overcrowding at higher level hospitals and underutilisation of primary care are viewed to diminish the effects of the continuing health system investments on population health. We explore the factors that influence the choice of healthcare facility level in rural and urban China and aim to reveal the underlying choice processes.
Methods
We conducted eight semistructured focus group discussions among the general population and the chronically ill in a rural area in Chongqing and an urban area in Shanghai. Respondents’ discussions of (evidence-based) factors and how they influenced their facility choices were analysed using qualitative analysis techniques, from which we elicited choice process maps to capture the partial order in which the factors were considered in the choice process.
Results
The factors considered, after initial illness perception, varied over four stages of health service utilisation: initial visit, diagnosis, treatment and treatment continuation. The factors considered per stage differed considerably between the rural and urban respondents, but less so between the general population and the chronically ill. Moreover, the rural respondents considered the township health centres as default and prefer to continue in primary care, yet access higher levels when necessary. Urban respondents chose higher levels by default and seldom moved down to primary care.
Conclusions
Disease severity, medical staff, transportation convenience, equipment and drug availability played important roles when choosing healthcare facilities in China. Strengthening primary care correspondingly may well be effective to increase primary care utilisation by the rural population but insufficient for the urban population. The developed four-stage process maps are general enough to serve as the basis for (partially) ordering factors influencing facility level choices in other contexts.
In the context of rapid population aging, Beijing is facing great challenges in providing healthcare services for the elderly. The objective of this study is to measure the spatial accessibility of the elderly to healthcare services in Beijing. A major challenge is that healthcare services are not exclusive for the elderly, so the elderly must compete with the non-elderly for access to healthcare services. In this study, we have developed a multi-mode and variable-demand two-step floating catchment area model for measuring spatial accessibility of the elderly to healthcare services, taking into account the competition between the elderly and non-elderly. This is modeled by differences in demand intensity and mobility. The elderly have a higher demand intensity and are disadvantaged in mobility due to their higher dependence on public transportation than the non-elderly. To improve the elderly’s healthcare accessibility, more healthcare resources should be allocated and the public transportation to hospitals should be improved, especially in peripheral areas. The proposed model can also be applied in other scenarios considering multiple population groups with different demand intensity for public services and mobility.
Accessibility to healthcare services strongly correlates with residents' health. As one of the objectives of sustainable cities, the social equality of access to healthcare plays a vital role in the rational allocation of healthcare facilities. However, limited attention has been paid to how the varying traffic conditions impact the equality of access to public service among places or demographic groups. Taking Wuhan, China, as the study area, this paper measured the hourly accessibility to healthcare by using two methods: Gaussian Two-Step Floating Catchment Area and Weighted Average Travel Time. Then, it investigated how traffic conditions affected the equality of healthcare services among places or demographic groups at different times. We found that traffic conditions change the accessibility by extending travel time and reducing the likelihood of obtaining healthcare services during peak hours, especially for suburban residents. Regarding equality evaluation, the impact of traffic variability on equality across places is much more significant than that on equality across demographic groups. The results highlight the effects of transport on the equal accessibility of healthcare and provide suggestions to minimise spatial and demographic disparities in healthcare services, meet the need of Sustainable Development Goals, and develop a more sustainable and inclusive society.
With the ongoing spread of COVID-19, vaccination stands as an effective measure to control and mitigate the impact of the disease. However, due to the unequal distribution of COVID-19 vaccination sites, people can have different levels of spatial accessibility to COVID-19 vaccination. This study adopts an improved gravity-based model to measure the racial/ethnic inequity in transit-based spatial accessibility to COVID-19 vaccination sites in the Chicago Metropolitan Area. The results show that Black-majority and Hispanic-majority neighborhoods have significantly lower transit-based spatial accessibility to COVID-19 vaccination sites compared to White-majority neighborhoods. This research concludes that minority-dominated inner-city neighborhoods, despite better public transit coverage, are still disadvantaged in terms of transit-based spatial accessibility to COVID-19 vaccination sites. This is probably due to their higher population densities, which increase the competition for the limited supply of COVID-19 vaccination sites within each catchment area.
Urban green space (UGS) is an important component of urban resources which contributes to human physical and mental health. Studies on the accessibility of UGS under the two-step floating catchment (2SFCA) framework have recently received much attention. However, the effects of people’s actual mobility patterns have not been fully considered in current studies. Proposed in this study is an improved accessibility model called AM-Ga2SFCA, which refines the traditional Gaussian 2SFCA method with the actual mobility information extracted from mobile phone big data and online map. A new attractiveness index of UGS is implemented by combining the popularity evaluated by the PageRank algorithm and the actual utilisation based on buffer analysis. In addition, realistic travel time between each demand point and UGS is retrieved from the online map, which is further introduced into AM-Ga2SFCA as the travel cost. A case study is conducted in Shenzhen, China to validate the proposed model. Results show that the accessibility of UGS is strongly correlated with regional urbanization level, for example, higher accessibility generally occurred in the region with developed transportation and rich green resources. From the perspective of age groups and travel modes, we found that the environmental justice issue had already occurred in Shenzhen especially for the non-elderly: under the walk mode, nearly 80% of the non-elderly only shared 20% of UGS whilst approximately 80% of the elderly shared 30% of UGS. However, taxi or private vehicles can effectively alleviate the aforementioned phenomenon by reducing the Gini index to less than 0.5. The proposed model is expected to advance the understanding of UGS accessibility and facilitate effective planning to reduce environmental justice.
Spatial accessibility to health care plays a vital role in the evaluation of medical resource equality. A widely used method of spatial accessibility is the Two-Step Floating Catchment Area (2SFCA) method. However, the 2SFCA model (and its later variants) implicitly assumes that each doctor has the same attraction (unlimited resources) to care seekers and each care seeker's need is the same; it does not consider insurance that doctors accept or patients' different needs by age and gender. In fact, patients usually choose doctors within their insurance network and seniors and females usually have higher health care needs/demands than others. Here we present an improvement to the 2SFCA method to address these shortcomings. On the supply side, we allocate each doctor's resource equally to the insurance plans that he/she accepts. On the demand side, we adjusted the population based on their health care needs by age and gender and estimated the population holding each insurance based on the insurance's market share (assuming each insurance's market share is a reasonable representation of the population using that insurance). Next we calculate the accessibility score of each insurance plan following the 2SFCA approach and sum them at each population location as the accessibility at that location. We call the new improved approach Supply-Demand Adjusted 2SFCA. The results indicate that the SDA-2SFCA model could better reflect the actual supply and demand situation of health care and thus provide a better measure of spatial accessibility to health care. The SDA-2SFCA model can help researchers and government agencies better allocate limited resources to the neediest areas.
Accessibility is an essential indicator for measuring the effectiveness and equity of transport and public health services. However, previous studies neglect the effects of monetary costs for evaluating access to healthcare services. Therefore, this paper attempts to analyze the spatial accessibility patterns to healthcare services by integrating the total travel costs into an improved enhanced three-step floating catchment area (E3SFCA) method. Firstly, we adopt the explanatory factor analysis to compute the attractiveness coefficient by considering healthcare service capacities and qualities. The total travel cost under the private car and public transport modes are then determined by the integration of both real-time travel times and monetary costs during the journey, expressed in time. Notably, the real-time travel times under two travel modes are collected from the open-source route planning application program interface. Following that, the healthcare service catchment area thresholds are determined based on the results of frequency distribution of travel time under each travel mode, and the corresponding Gaussian impedance functions are produced. Based on the improved enhanced three-step floating catchment area (E3SFCA) method, Changsha, China's empirical case study is conducted to verify and investigate the accessibility between 189 subdistricts and 25 tertiary hospital locations at six different time periods in a working day under both the private car and public transport modes. The results suggest that the accessibility distribution shape reflects a circular diffusion centered on the central urban areas. The accessibility to tertiary hospitals is inadequate and regionally unbalanced in Changsha with respect to population allocations, especially during peak hours. Moreover, the private car mode is superior to public transport in most areas of the city. These findings may provide new insights for city planners and policymakers in terms of equity evaluations of medical resource accessibility and site allocations.
Public open space (POS) is often regarded as a necessity that is meant to be enjoyed by everyone, especially as we move toward a post-pandemic society. It is considered one of the most crucial public health assets that contribute tremendously to people’s physical, social, and psychological wellbeing. While obliging private development projects to provide POS has become a common policy for optimizing land use, some critiques regard Public Open Space in Private Developments (POSPD) as over-controlled and exclusive spaces, which raise justice concerns about people’s equal rights towards POS as health resources. However, little is known about the degree to which spatial justice can be created in POSPD. With the urban population becoming more diverse, investigating POSPD’s actual spatial justice situation under a robust framework to ensure access for all is timely and vital. Through the lens of spatial justice, we first examined the current dominant critiques of POSPD based on a comprehensive literature review. Using Hong Kong as a case study, we then conducted a questionnaire survey on the spatial justice performance of three representative POSPD sites and also introduced Bayesian Network as a graphical probabilistic model to illustrate the mutual relationships among key variables. The results have identified the most sensitive issues (e.g., safety, affordability and diversity), contributing to spatial justice per- formance and indicated that inclusive POS requires a secure, affordable environment that supports diverse ac- tivity for everyone. The findings will guide decision-makers to put the appropriate emphasis on creating and protecting inclusive POSPD in the wake of the pandemic.
A location's irreplaceability refers to the degree of difficulty with which it can be replaced by other locations. For example, the irreplaceability of airports, hospitals, and ATMs varies, and that between hospitals is also different. They differ in both the number of users and the extent of service area. Quantifying the location's irreplaceability provides guidance for urban planning, such as siting of public resources. Existing methods for quantifying an urban location's irreplaceability do not consider human activity at the location, therefore the revealed irreplaceability may deviate from the resident's perceptions. To address this issue, we use origin-destination flows to reflect human activity. We propose a flow-based locational measure, I-index, to quantify the location's irreplaceability. It can be viewed as ‘H-index of flow’ where we regard locations as scientists, flows as papers. I-index of a location is the maximum value of i such that at least i flows with a length of at least α ∗ i meters have reached this location, where α is the conversion factor that can be determined adaptively from the flow dataset. I-index elegantly combines the flow volume and length into a single value. The effectiveness of the I-index is validated by simulation experiments. Two case studies show that the hospital's irreplaceability strongly correlates with the hospital bypass behavior and locations with strongly mixed urban functions are more irreplaceable. The implications for urban planning are further discussed.
Spatial equity of parks is a major concern in environmental justice studies. While many measurements have been used to evaluate access to parks, few studies have considered the impact of travel behavior on park accessibility. This study aims to establish a travel behavior-based Gaussian two-step floating catchment area (TB-G2SFCA) method to assess spatial equity of parks in the Nanjing region, and Local Moran's I index is applied to identify spatial agglomeration patterns in assessing equity. The results demonstrate that (1) the traditional single-mode model maybe cannot provide accurate approach to evaluating park accessibility while the TB-G2SFCA method can provide a more realistic park accessibility evaluation; (2) the inhabitants of most communities distributed south of the Yangtze River can obtain better park services than the northern areas; (3) the spatial disparities of equity in park accessibility are severe in three suburban districts, relatively minor in four central districts, and insignificant in two central districts. These findings may assist urban planners and policy makers to frame more reasonable policy and planning to improve spatial equity to parks in urban areas.
Introduction
There is an absence of literature describing Medicare utilization by physiatrists, despite their key role in treating Medicare enrollees with qualifying disabilities and common neuromusculoskeletal conditions.
Objective
Analyze Medicare data regarding physiatrists and their beneficiaries, services, and reimbursement, as well as trends in utilization and geographic distribution.
Design and Setting
Retrospective analysis of publicly available Center for Medicare & Medicaid Services data for Medicare beneficiaries receiving physiatric services from 2012-2017.
Main Outcome Measures
After adjustment for inflation, variables assessed for changes over time included provider and beneficiary demographics, total Medicare reimbursement, and number of services provided, subsequently separated by drug and medical service metrics. Lorenz curves and Gini coefficients were computed to study reimbursement inequality. Choropleth maps were generated to assess geographic differences in physician density and reimbursement, both by state and ZIP code.
Results
The number of physiatrists utilizing Medicare increased from 7230 to 7895 from 2012-2017, while the average number of unique beneficiaries per clinician remained constant (307 vs 310; P = 0.51). Beneficiaries' mean hierarchical conditions category (HCC) health risk score, normalized to 1.0 for the average beneficiary, increased significantly from 2012-2017 (1.72 vs 1.80; P < 0.01). Mean Medicare reimbursement per physiatrist decreased significantly from 2012-2017 (117 623; P < 0.001), while mean number of services remained constant (3243 vs 3077; P = 0.132). Botulinum toxin and baclofen injections were the two most reimbursed drug-related services. Gini coefficients ranged from 0.52-0.53 for 2012-2017, suggesting moderate reimbursement inequality, with the 75th percentile receiving on average 2 times the median. Both physician density and top earners were concentrated in urban and metropolitan areas.
Conclusions
Despite rising healthcare costs and increasing medical complexity of physiatrists' beneficiaries, Medicare payments have decreased over time. These trends are relevant to both providers and policy makers, particularly in light of unequal geographic distribution of physiatrists across the country.
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Urban public health is one of the most critical yet neglected aspects of urban planning in developing countries such as India. Inequity in access to government healthcare facilities affects the overall urban population and can substantially negatively impact the vulnerable population, who mostly rely on government healthcare services. In this paper, the accessibility measure for healthcare services by public transport is developed using travel time and the number of transit stops (accounting for transit connectivity) for Greater Mumbai. We also identified socially vulnerable wards (administrative units) using a Social Vulnerability Index (SVI), developed based on 16 indicators using Principal Component Analysis (PCA). Developed regression models showed that the proposed accessibility measure explains the coverage and usage of healthcare services better than the traditional accessibility measure, which is based on only aggregate level travel time impedances. South Mumbai has relatively better accessibility for public hospitals and dispensaries, whereas, lower level of accessibility is observed in the eastern part for public healthcare services. Assessment for the spatial inequity based on the Gini index, bivariate Moran's I, and mean access value reveals a higher degree of spatial inequity for accessing government hospitals for the slum population. The study developed a decision framework to suggest effective policy measures, which can be prioritised based on SVI to reduce the disparity in the spatial distribution of accessibility to government healthcare systems for vulnerable groups. Our findings can aid transportation and urban planners, health researchers, and policymakers to improve accessibility in under-served areas and give special attention to the needs of the vulnerable population.
Background
During the COVID-19 pandemic, many urban residents stopped riding public transit despite their reliance on it to reach essential services like healthcare. Few studies have examined the implications of public transit reliance on riders’ ability to reach healthcare when transit is disrupted. To understand how shocks to transportation systems impact healthcare access, this study measures the impact of avoiding public transit on the ability of riders to access healthcare and pharmacy services during lockdowns.
Methods
We deployed a cross-sectional survey of residents of Toronto and Vancouver in May 2020 through Facebook advertisements and community list-serves. Eligibility criteria included riding transit at least weekly prior to the pandemic and subsequent cessation of transit use during the pandemic. We applied multivariable modified Poisson models to identify socio-demographic, transportation, health-related, and neighborhood predictors of experiencing increased difficulty accessing healthcare and getting prescriptions while avoiding public transit. We also predicted which respondents reported deferring medical care until they felt comfortable riding transit again.
Results
A total of 4367 former transit riders were included (64.2% female, 56.1% Toronto residents). Several factors were associated with deferring medical care including: being non-White (Toronto, APR, 1.14; 95% CI, 1.00-1.29; Vancouver, APR, 1.52; 95% CI, 1.26-1.84), having a physical disability (Toronto, APR, 1.20; 95% CI, 1.00-1.45; Vancouver, APR, 1.42; 95% CI, 1.08-1.87), having no vehicle access (Toronto, APR, 1.74; 95% CI, 1.51-2.00; Vancouver, APR, 2.74; 95% CI, 2.20-3.42), and having low income (Toronto, APR, 1.77; 95% CI, 1.44-2.17; Vancouver, APR, 1.51; 95% CI, 1.06-2.14).
Discussion
During COVID-19 in two major Canadian cities, former transit riders from marginalized groups were more likely to defer medical care than other former riders. COVID-19 related transit disruptions may have imposed a disproportionate burden on the health access of marginalized individuals. Policymakers should consider prioritizing healthcare access for vulnerable residents during crises.
Current quantitative measures of job accessibility rarely consider the interaction between job opportunities and labor force, and the effects of dynamic travel mode choice. Drawing upon multiple open-source datasets, we develop a job accessibility index by extending the two-step floating catchment area method (2SFCA). The job accessibility indices are calculated for different commuting scenarios concerning distance, time, and travel modes. The results suggest that job accessibility is very sensitive to travel modes, and using a single travel mode would contribute to a biased job accessibility index. The job accessibility indices with combined travel modes are more geographically balanced than using a single travel mode. Furthermore, the new index is employed to examine the spatial pattern of job accessibility and explore the relationship between job accessibility, housing, and population in the Pudong district, Shanghai. The new job accessibility indices manifest the impacts of ring roads on the spatial distribution of job accessibility. A comparative analysis shows that the floating population has poor driving-based job accessibility but can access job opportunities using public transit. Also, poor job accessibility leads to low rent prices but has little impact on medium-high rent. Both transit-based and drive-based job accessibility indices are positively related to housing prices. Our study highlights the importance of considering dynamic travel mode choice in job accessibility research. The research outcomes also contribute to the literature on spatial mismatch by revealing the unique relationship between job accessibility, housing, and population in urban China.
Disaggregated population counts are needed to calculate health, economic, and development indicators in Low- and Middle-Income Countries (LMICs), especially in settings of rapid urbanisation. Censuses are often outdated and inaccurate in LMIC settings, and rarely disaggregated at fine geographic scale. Modelled gridded population datasets derived from census data have become widely used by development researchers and practitioners. These datasets are evaluated for accuracy at the spatial scale of the input data which is often much courser (e.g. administrative units) than the neighbourhood or cell-level scale of many applications. We simulate a realistic "true" 2016 population in Khomas, Namibia, a majority urban region, and introduce realistic levels of outdatedness (over 15 years) and inaccuracy in slum, non-slum, and rural areas. We aggregate these simulated realistic populations by census and administrative boundaries (to mimic census data), and generate 32 gridded population datasets that are typical of a LMIC setting using WorldPop-Global-Unconstrained gridded population approach. We evaluate the cell-level accuracy of these simulated datasets using the original "true" population as a reference. In our simulation, we found large cell-level errors, particularly in slum cells, driven by the use of average population densities in large areal units to determine cell-level population densities. Age, accuracy, and aggregation of the input data also played a role in these errors. We suggest incorporating finer-scale training data into gridded population models generally, and WorldPop-Global-Unconstrained in particular (e.g., from routine household surveys or slum community population counts), and use of new building footprint datasets as a covariate to improve cell-level accuracy. It is important to measure accuracy of gridded population datasets at spatial scales more consistent with how the data are being applied, especially if they are to be used for monitoring key development indicators at neighbourhood scales with relevance to small dense deprived areas within larger administrative units.
Purpose
Spatial behavior of patients in utilizing health care reflects their travel burden or mobility, accessibility for medical service, and subsequently outcomes from treatment. This paper derives the best-fitting distance decay function to capture the spatial behaviors of cancer patients in the Northeast region of the U.S., and examines and explains the spatial variability of such behaviors across sub-regions.
Principal results
(1) 46.8%, 85.5%, and 99.6% of cancer care received was within a driving time of 30, 60, and 180 min, respectively. (2) The exponential distance decay function is the best in capturing the travel behavior of cancer patients in the region and across most sub-regions. (3) The friction coefficient in the distance decay function is negatively correlated with the mean travel time. (4) The best-fitting function forms are associated with network structures. (5) The variation of the friction coefficient across sub-regions is related to factors such as urbanicity, economic development level, and market competition intensity.
Major conclusions
The distance decay function offers an analytic metric to capture a full spectrum of travel behavior, and thus a more comprehensive measure than average travel time. Examining the geographic variation of travel behavior needs a reliable analysis unit such as organically defined “cancer service areas,” which capture relevant health care market structure and thus are more meaningful than commonly-used geopolitical or census area units.
Health care accessibility is a vital indicator for evaluating areas where there are medical shortages. However, due to the lack of population data with a satisfactory spatial resolution, efforts to accurately measure health care accessibility among older individuals have been hampered to some extent. To address this issue, we attempt to measure accessibility to health care services for older bus passengers in Nanjing, China, using a finer spatial resolution. More specifically, based on one month's worth of bus smart card data, a framework for identifying the home stations (i.e., a passenger's preferred station near their residence) of older passengers is developed to measure the aggregate demand at the bus stop scale. On this basis, a measurement that integrates the Gaussian two-step floating catchment area (2SFCA) and the adjusted 2SFCA methods (referred to as the adjusted Gaussian 2SFCA method) is proposed to measure accessibility to health care services for older people. The results show that: (1) almost all home stations experience inflated demand, especially those located in the suburbs; (2) despite abundant health care resources, home stations in urban districts are rarely identified as high accessibility stations , due to high demand densities among the older population; and (3) more attention should be paid to two types of home stations-those with a medical institution and those with bed shortages, respectively. The first type is predominantly distributed in the periphery of the city, in the suburbs where the travel time required to access the nearest health care service by bus is longer. The second type is mostly located in the outskirts of urban districts and in the central area of one suburb. These findings could help policy makers to implement more appropriate measures to design and reallocate health care resources.
Urban green space (UGS) has positive impacts on people’s physical and mental health. Equal access to UGS for all people, regardless of their individual characteristics, is key to the achievement of better public health outcomes. Existing studies have focused largely on inequity in spatial UGS accessibility distribution but failed to uncover the disparities of UGS accessibility among different racial/ethnic and income groups as well as inequity in income-based UGS accessibility distribution within the same racial/ethnic groups. By using the city of Chicago as the study area, we adopt the two-step floating catchment area (2SFCA) method to measure census tract-level UGS accessibility and compare distribution disparities among white-majority, black-majority and Hispanic-majority census tracts as well as low-income and non-low-income census tracts. In addition, we employ the Palma ratio to measure the income-based UGS accessibility distribution inequity within respective racial/ethnic groups. The results show that white-majority census tracts generally enjoy significantly better UGS accessibility than minority-dominated census tracts, while black-majority census tracts have higher UGS accessibility than Hispanic-majority census tracts. In terms of the intra-racial/ethnic income-based UGS accessibility inequity between the richest and the poorest, inequity is the lowest among white-majority census tracts and the highest among black-majority census tracts, with inequity in Hispanic-majority census tracts in the intermediate range.
The recent decade has witnessed a new wave of development in the place-based accessibility theory, revolving around the two-step floating catchment area (2SFCA) method. The 2SFCA method, initially serving to evaluate the spatial inequity of health care services, has been further applied to other urban planning and facility access issues. Among these applications, different distance decay functions have been incorporated in the thread of model development, but their applicability and limitations have not been thoroughly examined. To this end, the paper has employed a place-based accessibility framework to compare the performance of twenty-four 2SFCA models in a comprehensive manner. Two important conclusions are drawn from this analysis: on a small analysis scale (e.g., community level), the catchment size is the most critical model component; on a large analysis scale (e.g., statewide), the distance decay function is of elevated importance. In sum, this comparative analysis provides the theoretical support necessary to the choice of the catchment size and the distance decay function in the 2SFCA method. Justification of model parameters through empirical evidence (e.g., field surveys about local travel activities) and model validation through sensitivity analysis are needed in future 2SFCA applications for various urban planning, service delivery, and spatial equity scenarios.
Objective
With the continuing rise in the global incidence of diabetes, the prevention of diabetes and control of associated medical expenses has become a public health issue worldwide. This study aims to identify the medical expenses of patients with diabetes in different regions of China and examine the differences in inpatient medical expenses and the impacts of them on these patients.
Study design
This study is a longitudinal analysis of medical expenses for inpatients with diabetes for different years; horizontal analysis of medical expenses among different regions; and literature review.
Methods
Data were derived from China's Medical Insurance Department database. We selected inpatients with diabetes in the eastern, central, and western regions of China for the period 2013–2015 and randomly selected data through systematic sampling.
Results
Among the 4150 patients with diabetes considered in this study, the patients' medical expenses were found to differ significantly across regions, years, ages, medical insurance types, medical institution levels, total medical expenses, medical insurance fund payments, and out-of-pocket (OOP) expenses. In addition, there were significant differences in total medical expenses for male and female patients. Furthermore, medical insurance type, patients' age, medical institution level, and year significantly influenced total medical expenses.
Conclusions
Inpatients with diabetes in different regions exhibited significant differences in total medical expenses, medical insurance fund payments, and OOP expenses. China should invest more in chronic disease treatment in its central and western regions, narrow the regional differences in medical expenses, and endeavor to ensure equity in the availability and cost of medical services. Moreover, patients with diabetes must be encouraged to access primary care to reduce their medical expenses.
This research attempts to build a unified framework for distinguishing the spatiotemporal visit patterns of urban places by different social groups using mobile phone data in Harbin, China. Social groups are detected by their social ties in the ego‐to‐ego mobile phone call network and are embedded in physical space according to their home locations. Popular urban places are detected from user‐generated content as the basic spatial analysis unit. Coupling subscribers’ footprints and urban places in physical space, the spatiotemporal visit patterns of urban places by distinct social groups are uncovered and interpreted by non‐negative matrix factorization. The proposed framework enables us to answer several critical questions from three perspectives: (1) How to model popular urban places in terms of vague boundary, land use, and semantic features based on crowdsourcing data?; (2) How to evaluate interaction between individuals for inspecting the relationship between spatial proximity and social ties based on spatiotemporal co‐occurrence?; and (3) How to distinguish urban place visit preferences for social groups associated with different socio‐demographic characteristics? Our research could assist urban planners and municipal managers to identify critical urban places frequented by different population groups according to their roles and social/cultural characteristics for improvement of urban facility allocation.
As accessibility becomes an increasingly relevant concept in the analysis of sustainable transport and urban development, the accuracy of accessibility measures becomes increasingly vital. While more complex measures are gradually gaining popularity with increasing data and computational resources, policy makers and planners are still prone to opt for less complex methods that are easy to use and interpret. The cumulative opportunities measure is the most widely applied accessibility measure in planning practice, but it is also among the least accurate due to its lack of consideration of the impact of competition for those opportunities. This study seeks to highlight the impact of addressing competition for different urban services in the cumulative opportunities measure. A competition component is added to the measure, which is applied to a case study of three types of urban services in the Perth metropolitan area; jobs, primary/secondary education and shopping. The results show that considering competition changes the spatial patterns of accessibility and its equity. Since this approach reveals demand-supply imbalances, it can more accurately determine spatial inequalities in accessibility, and hence increases the utility of the cumulative opportunities measure. We also find that the three services had varying levels and spatial patterns of accessibility and spatial equity, thus relying on any single one of them for assessing spatial structural performance can be misleading.
Introduction: The existing healthcare-services-related literature tends to examine accessibility under a single travel mode, and measurement approaches are remaining limited for several inherent deficiency. This paper proposed a methodological enhancement of the three-step floating catchment area approach. Methods: First, we incorporates real-time travel time and trip distance of private car and public transport obtained from open-source route planning API into model, which aims to differentiate the impact of multiple travel costs on spatial accessibility outcomes; next, an arithmetic mean-based Gaussian weight algorithm was introduced for achieve stable accessibility index; then, exploratory factor analysis was further employed to evaluate healthcare capacity, with the total score as the healthcare supply indicator to calculate the provider-to-population ratios; finally, an empirical study was conducted to verify the model's advantages. We investigate accessibility to three tiers of healthcare facilities (including 22 tertiary hospitals, 88 secondary hospitals, and 55 community healthcare centres), and reveal disparities between supply and demand, via conjoint analysis of the accessibility of facilities and the population density under four associate patterns in the district of Wuhan at community scale (total 830 communities). Results: The results suggest that in terms of travel modes, the travel time and trip distance under the private car mode are shorter than these calculated under the public transport mode. Highly accessible communities are more concentrated in the central urban areas and distributed near a healthcare service centre, and community healthcare center have the greatest accessibility among the three tiers of healthcare. Moreover, statistical analysis highlights that distinct polarized differentiation appears in the number of communities with low and high accessibility, and more than half of the communities have accessibility levels that are inappropriate for their population size. Conclusions: These findings may have important policy implications for health planners and decision makers who must reasonably allocate public health resources.
The rapid development in telecommunication networks is producing a huge amount of information regarding how people (with their mobile devices) move and behave over space and time. While GPS data, typically collected by smartphone apps, are restricted to rather small samples of the population, mobile phone network data, routinely collected by mobile network operators, potentially allow to analyze travel behaviors and social interaction of the whole population, with full temporal (e.g., longitudinal) coverage at a comparatively low cost. Therefore, recent years have seen an increasing interest in using such data for human mobility studies. However, due to their noisy and temporally infrequent/irregular nature, extracting mobility information such as transport modes from these data is particularly challenging. This paper provides an in-depth, systematic review of transport mode detection based on mobile phone network data. The results of the review show that existing studies tend to identify easy-to-detect modes (e.g., train or metro), or aggregate fine-grained modes into more general groups (e.g., public versus private transport). Rule-based methods making use of geographic data were often developed. More importantly, due to the lack of ground truth data, evaluation of the proposed methods was seldom done and reported. Finally, we identify a list of research gaps currently being faced in this field, particularly regarding robust and real-time data cleaning and mode detection methods, “benchmark” datasets and metrics allowing the comparison of different mode detection methods, as well as privacy and bias issues.
Healthcare access and utilization remain key challenges in the Global South. South Africa represents this given that more than twenty years after the advent of democratic elections, the national government continues to confront historical systems of spatial manipulation that generated inequities in healthcare access. While the country has made significant advancements, governmental agencies have mirrored international strategies of healthcare decentralization and focused on local provision of primary care to increase healthcare access. In this paper, we show the significance of place in shaping access and health experiences for rural populations. Using data from a structured household survey, focus group discussions, qualitative interviews, and clinic data conducted in northeast South Africa from 2013 to 2016, we argue that decentralization fails to resolve the uneven landscapes of healthcare in the contemporary period. This is evidenced by the continued variability across the study area in terms of government-sponsored healthcare, and constraints in the clinics in terms of staffing, privacy, and patient loads, all of which challenge the access-related assumptions of healthcare decentralization.
Big Data sources offer new possibilities for urban mobility and accessibility studies. As people carry out their activities in a city, they leave behind a digital fingerprint that can be used to analyze the population's daily mobility patterns and determine the exact times of travel between points of origin and destination at different times of the day. These data present high spatial and temporal resolution, and enable accurate and dynamic analysis of accessibility. The objective of this study was to conduct a dynamic analysis of urban accessibility considering its two main components: travel times and the attractiveness of destinations. To this end, we calculated travel times between transport zones using the Google Maps API and constructed origin and destination (OD) travel matrices from mobile phone records. Several scenarios were generated to analyze dynamic accessibility and the separate influence of its two components. We also conducted a cluster analysis to characterize transport zones according to their accessibility in each of the scenarios and times of day considered. Our results indicate that these new sources of geolocated data show considerable potential for use in time-sensitive accessibility studies, since they yield more accurate and realistic information than static or partially dynamic analyses. Such information could help politicians take better decisions concerning transport and land use.