Does health service funding go where the need is? A prototype spatial access analysis for new urban contracts data

Background Much of spatial access research measures the proximity to health service locations. We advance this research by focusing on whether health service funding is within walkable reach of neighborhoods with high hardship. This is made possible by a new administrative data source: financial contracts data for those human services that are delivered by nonprofits under contract with the government. Methods In a prototypical spatial access study we apply a classic 2-step floating area catchment model for walkable network access to analyze 2018 data about contracted nonprofit health services funded by the Chicago Department of Public Health (CDPH). CDPH collected the data for the purpose of this study. Results We find that the common container approach of aggregating contract amounts by provider headquarter locations in a given area (ignoring satellite service sites) underestimates the share of funding that goes to Chicago neighborhoods with higher hardship. Once service sites and spatial access are taken into account, a larger share of CDPH funds was found to be within walkable reach of Chicago’s high hardship areas. This was followed by low hardship areas (which could be driven by more headquarter locations there that do serve areas throughout the city). Medium hardship areas trail both, perhaps warranting closer attention. We explore these results by program type and neighborhood with a spatial decision support system developed for the health department. Conclusions The typical approach for analyzing human service contracts based on headquarters is misleading -- in fact, we find that results are reversed when service sites and walkable access are taken into account. This prototype provides an alternative framework for avoiding these misleading results.

Geographical Access to Child and Family Healthcare Services and Hospitals for Africa-Born Migrants and Refugees in NSW, Australia; A Spatial Study

Background: African-born migrants and refugees arriving from fragile states and countries with political and economic challenges have unique health needs requiring tailored healthcare services and support. However, there is little investigation into the distribution of this population and their spatial access to healthcare in Australia. This paper reports on research that aimed to map the spatial distribution of Africa-born migrants from low and lower-middle-income countries (LLMICs) and refugees in New South Wales (NSW) and access to universal child and family health (CFH) services and hospitals. Methods: We analysed the Australian Bureau of Statistics 2016 Census data and Department of Social Services 2018 Settlement data. Using a Geographic Information System mapping software (Caliper Corporation. Newton, MA, USA), we applied data visualisation techniques to map the distribution of Africa-born migrants and refugees relative to CFH services and their travel distance to the nearest service. Results: Results indicate a spatial distribution of 51,709 migrants from LLMICs in Africa and 13,661 refugees from Africa live in NSW, with more than 70% of the total population residing in Sydney. The Africa-born migrant and refugee population in Sydney appear to be well served by CFH services and hospitals. However, there is a marked disparity between local government areas. For example, the local government areas of Blacktown and Canterbury-Bankstown, where the largest number of Africa-born migrants and refugees reside, have more uneven and widely dispersed services than those in Sydney’s inner suburbs. Conclusion: The place of residence and travel distance to services may present barriers to access to essential CFH services and hospitals for Africa-born refugees and migrants. Future analysis into spatial-access disadvantages is needed to identify how access to health services can be improved for refugees and migrants.

Planning for the future: Addressing the spatial accessibility of aged residential care facilities in New Zealand

<p>Evidence in New Zealand suggests that spatial access to aged residential care facilities (ARCFs) has been declining. Poor spatial access to facilities has been shown internationally to lead to reduced frequency of visitation by family and friends, and in turn poorer mental health and wellbeing of people in care. However, the New Zealand population is ageing and older people are increasing as a proportion of the total population. Subsequently, total demand for ARCFs is set to increase dramatically and a substantial number of facilities will likely need to be built by 2026. The intent of this thesis is to explore how geographic information science (GIS) methods can be used to identify potential locations for these ARCFs in New Zealand so that travel time for friends and family is minimised. Providers were surveyed on the relative importance of a series of spatial attributes when deciding where to place new facilities. Maps for each spatial attribute were generated from their preferences and overlaid using weighted linear combination and areas exceeding a suitability threshold were identified as potential locations. To choose optimal locations, maximal covering location-allocation models were used based on projected populations and demand for 2026. The spatial accessibility of these locations was then compared to the spatial accessibility of facilities in 2011. The results suggest that GIS methods have the potential to improve the spatial access to ARCFs to friends and family of people in care.</p>

Planning for the future: Addressing the spatial accessibility of aged residential care facilities in New Zealand

<p>Evidence in New Zealand suggests that spatial access to aged residential care facilities (ARCFs) has been declining. Poor spatial access to facilities has been shown internationally to lead to reduced frequency of visitation by family and friends, and in turn poorer mental health and wellbeing of people in care. However, the New Zealand population is ageing and older people are increasing as a proportion of the total population. Subsequently, total demand for ARCFs is set to increase dramatically and a substantial number of facilities will likely need to be built by 2026. The intent of this thesis is to explore how geographic information science (GIS) methods can be used to identify potential locations for these ARCFs in New Zealand so that travel time for friends and family is minimised. Providers were surveyed on the relative importance of a series of spatial attributes when deciding where to place new facilities. Maps for each spatial attribute were generated from their preferences and overlaid using weighted linear combination and areas exceeding a suitability threshold were identified as potential locations. To choose optimal locations, maximal covering location-allocation models were used based on projected populations and demand for 2026. The spatial accessibility of these locations was then compared to the spatial accessibility of facilities in 2011. The results suggest that GIS methods have the potential to improve the spatial access to ARCFs to friends and family of people in care.</p>

Spatial Accessibility Assessment of Prehospital EMS with a Focus on the Elderly Population: A Case Study in Ningbo, China

The spatial accessibility of prehospital EMS is particularly important for the elderly population’s physiological functions. Due to the recent expansion of aging populations all over the globe, elderly people’s spatial accessibility to prehospital EMS presents a serious challenge. An efficient strategy to address this issue involves using geographic information systems (GIS)-based tools to evaluate the spatial accessibility in conjunction with the spatial distribution of aging people, available road networks, and prehospital EMS facilities. This study employed gravity model and empirical Bayesian Kriging (EBK) interpolation analysis to evaluate the elderly’s spatial access to prehospital EMS in Ningbo, China. In our study, we aimed to solve the following specific research questions: In the study area, “what are the characteristics of the prehospital EMS demand of the elderly?” “Do the elderly have equal and convenient spatial access to prehospital EMS?” and “How can we satisfy the prehospital EMS demand of an aging population, improve their spatial access to prehospital EMS, and then ensure their quality of life?” The results showed that 37.44% of patients admitted to prehospital EMS in 2020 were 65 years and older. The rate of utilization of ambulance services by the elderly was 27.39 per 1000 elderly residents. Ambulance use by the elderly was the highest in the winter months and the lowest in the spring months (25.90% vs. 22.38%). As for the disease spectrum, the main disease was found to be trauma and intoxication (23.70%). The mean accessibility score was only 1.43 and nearly 70% of demand points had scored lower than 1. The elderly’s spatial accessibility to prehospital EMS had a central-outward gradient decreasing trend from the central region to the southeast and southwest of the study area. Our proposed methodology and its spatial equilibrium results could be taken as a benchmark of prehospital care capacity and help inform authorities’ efforts to develop efficient, aging-focused spatial accessibility plans.

Measuring COVID-19 vaccination coverage: an enhanced age-adjusted two-step floating catchment area model

Background There are only limited studies on access to COVID-19 vaccines and identifying the most appropriate health centres for performing vaccination in metropolitan areas. This study aimed to measure potential spatial access to COVID-19 vaccination centres in Mashhad, the second-most populous city in Iran. Methods The 2021 age structure of the urban census tracts was integrated into the enhanced two-step floating catchment area model to improve accuracy. The model was developed based on three different access scenarios: only public hospitals, only public healthcare centres and both (either hospitals or healthcare centres) as potential vaccination facilities. The weighted decision-matrix and analytic hierarchy process, based on four criteria (i.e. service area, accessibility index, capacity of vaccination centres and distance to main roads), were used to choose potential vaccination centres looking for the highest suitability for residents. Global Moran’s index (GMI) was used to measure the spatial autocorrelation of the accessibility index in different scenarios and the proposed model. Results There were 26 public hospitals and 271 public healthcare centres in the study area. Although the exclusive use of public healthcare centres for vaccination can provide the highest accessibility in the eastern and north-eastern parts of the study area, our findings indicate that including both public hospitals and public healthcare centres provide high accessibility to vaccination in central urban part. Therefore, a combination of public hospitals and public healthcare centres is recommended for efficient vaccination coverage. The value of GMI for the proposed model (accessibility to selected vaccination centres) was calculated as 0.53 (Z = 162.42, P < 0.01). Both GMI and Z-score values decreased in the proposed model, suggesting an enhancement in accessibility to COVID-19 vaccination services. Conclusions The periphery and poor areas of the city had the least access to COVID-19 vaccination centres. Measuring spatial access to COVID-19 vaccination centres can provide valuable insights for urban public health decision-makers. Our model, coupled with geographical information systems, provides more efficient vaccination coverage by identifying the most suitable healthcare centres, which is of special importance when only few centres are available. Graphic abstract

Does Health Service Funding Go Where the Need Is? A Prototype Spatial Access Analysis for New Urban Contracts Data

Background | Much of spatial access research measures the proximity to health service locations. We advance this research by focusing on whether health service funding is within walkable reach of neighborhoods with high hardship. This is made possible by a new administrative data source: financial contracts data for those human services that are delivered by nonprofits under contract with the government.Methods | In a prototypical spatial access study we apply a classic 2-step floating area catchment model for walkable network access to analyze 2018 data about contracted nonprofit health services funded by the Chicago Department of Public Health (CDPH). CDPH collected the data for the purpose of this study.Results | We find that the common container approach of aggregating contract amounts by provider headquarter locations in a given area (ignoring satellite service sites) underestimates the share of funding that goes to Chicago neighborhoods with higher hardship. Once service sites and spatial access are taken into account, a larger share of CDPH funds was found to be within walkable reach of Chicago’s high hardship areas. This was followed by low hardship areas (which could be driven by more headquarter locations there that do serve areas throughout thecity). Medium hardship areas trail both, perhaps warranting closer attention. We explore these results by program type and neighborhood with a spatial decision support system developed for the health department.Conclusions | The typical approach for analyzing human service contracts based on headquarters is misleading -- in fact, we find that results are reversed when service sites and walkable access are taken into account. This prototype provides an alternative framework for avoiding these misleading results.