1. Introduction
Geographical Information Systems (GIS) play a major role in health care, surveillance of infectious diseases, and mapping and monitoring of the spatial and temporal distributions of vectors of infection, hence allowing researchers to study the relationships between spatial and temporal trends and risks, and between environmental factors and health, at all scales [
1]. Using GIS for the spatial representation of health issues helps professionals arrive at conclusions faster and reach better decisions related to deferent public health planning issues [
2]. The medical research applications of GIS are numerous and include finding disease clusters and their possible causes, improving deployment for emergency services, and determining if an area is being served adequately by health services. The benefit of using GIS in the health care industry is just now beginning to be realized. Public and private sectors are reaching better decisions based on spatial data integration and GIS. Public health departments and public health policy and research organizations, hospitals, medical centers, and health insurance organizations are all examples of health sectors that benefit from applying GIS in their spatial decision-making process. For instance, public health uses GIS for tracking child immunizations, conducting health policy research, and establishing service areas and districts.
Access to health care can be measured using the straight line or road distance for evaluating existing and future optimal service location. In addition, health care accessibility studies are focused in identifying health catchments, and in examining social groups in relation to health accessibility [
3]. Nichols et al., 2014, [
4] have presented another recent GIS application for evaluation accessibility to mammography resources in Mississippi, USA, showing the location of the geocoded facilities, along with the counties and major transportation networks in Mississippi, and defining areas within and outside the drive-time distance with respect to all mammography facilities based on an optimum driving route. Bagheri et al., 2005 [
5] discussed a GIS application for measuring spatial accessibility to primary health care services in New Zealand and applied drive-time analysis for estimating the shortest time through road networks between any pair of population and health center locations.
The advantages of using GIS in health care studies lies in its power to analyze, store, and display very large amounts of geo-referenced spatial data. Geographic information systems (GIS) can be defined as computer-based systems for integrating and analyzing geographical data. Fletcher-Lartey and Caprarelli (2016) [
1] reviewed applications of the GIS technology in public health and identified its successes and challenges. They summarized the common uses of GIS technology in the public health sector, emphasizing applications related to mapping and the understanding of parasitic diseases. They confirmed that geographical analysis has allowed researchers to interlink health, population, and environmental data, thus enabling them to evaluate and quantify relationships between health-related variables and environmental risk factors at different geographical scales. Mushonga, Banda, and Mulolwa (2017) [
6] added that GIS can be successfully used for defining access and utilization of health care services.
Geographic data are known as spatial data which result from the observation and measurement of Earth phenomena referenced to their locations on the Earth’s surface. Public health professionals or epidemiologists work with geographical data, such as disease registries with address information, locations of toxic waste disposal sites, or water quality reports from monitoring stations. These spatial data are considered as fundamental components of any GIS application. The success of GIS applications in health care studies depend critically on having access to accurate, timely, and compatible spatial data. For sectors working with GIS applications, spatial data can be viewed as both a cost and a resource. Creating geo-spatial datasets is very costly; it is estimated that well over half the cost of GIS projects are spent on creating and updating the geo-database. The created geo-spatial datasets are often useful for addressing a wide range of policy and planning issues. Their value extends well beyond the scope of the original projects for which they were created, and it increases as the datasets are used. GIS software systems enable public health analysts and planners to do more than simply visualizing map data. GIS supports a range of spatial analysis functions. Spatial analysis refers to “a general ability to manipulate spatial data into different forms and extract additional meaning as a result”. Spatial analysis covers the techniques that use both the locations and the attributes of features. Spatial analysis covers a broad range of methods. For example, public health could identify the area within a specified distance of a public drinking water well or surface source, and overlay the footprint of a building to determine whether or not that building would be located far from the source to meet legal requirements. GIS network analysis is another branch of spatial analysis that investigates flows through a network. The network is modeled as a set of nodes and the links that connect the nodes. Network analysis functions are also used to model service areas of facilities and to locate facilities. Geographical analysis helps researchers to overlay health, population, and environmental data, thus enabling them to evaluate and quantify relationships between health-related variables and environmental risk factors at different geographical scales. Today, GIS plays a major role in health care studies, including surveillance of infectious diseases, mapping and monitoring of the spatial and temporal distributions of vectors of infection, studying the relationships between spatial and temporal trends, and risk between environmental factors and health.
In summary, GIS can be used to define access to health services using the straight line distance, network distance, and the road-based travel time [
7]. For Jeddah City healthcare centers, only the GIS based straight line service area was applied by Murad, 2008 [
8]. However, based on the previous research no study so far has yet covered the GIS based drive time service area for health centers in Jeddah. Therefore, this paper presents a new GIS application created for determining geographical access to health centers at Jeddah City based on a GIS drive time analysis approach.
4. Discussion
Health care accessibility is defined in many studies. For example, Penchansky and Thomas [
12], mentioned that “access is most frequently viewed as a concept that somehow relates to consumers ability or willingness to enter into the health care system” and define access as “a concept representing the degree of ‘fit’ between the clients and the system”. Accessibility can be classified based on several issues, including availability, accessibility, accommodation, affordability, and acceptability. Aday and Andersen [
13] also consider wider definitions of accessibility that go beyond geographical or spatial accessibility to consider, for example, financial, informational, and behavioral influences. Gulliford et al. [
14] indicated that there is a difference between “having access” to health care and “gaining access” to health care. The former is related to the availability of health services. Meanwhile, the latter refers to whether health demand has the ability to overcome financial, organizational, and socio-cultural barriers and utilize health services. Accessibility studies should cover issues including ‘affordability’, ‘physical accessibility’, and ‘acceptability’. In addition, the availability of services, and barriers to access, have also to be considered in the context of the differing perspectives, health needs and socio-economic groups in the society. Based on accessibility studies there are three major factors that need to be covered in accessibility research, which are: (a) the spatial distribution and characteristics of the health services; (b) the transportation system in connecting individuals to health services; and (c) the socio-economic characteristics of individuals utilizing health services [
15].
Optimization in the geographical space is tantamount to solving a mathematical problem which eventually leads to finding a minimal length algorithm. In the case of route finding, this algorithm also reflects the minimal distance traveled. This is an interesting theoretical problem which refers to the “traveling salesman” problem (that has been proven to be very hard to solve), and to newer approaches dealing with complexity in geographical studies [
16,
17].
Health inequalities come from several factors that include the organization and management of space, which could differ between socio-economic groups. For instance, the under-resourcing of health care facilities, fragmentation of care across providers, and the lack of continuity of care can be barriers, which lead to increased health inequalities. Access to health care is one potential driver of health inequalities and is internationally recognized as the primary goal of meeting the essential health needs of individuals. Nevertheless, equitable access has proved difficult to achieve. This paper has used the travel-time approach to calculate accessibility to health centers in Jeddah City. After collecting the required data related to health center locations and road network travel times, ArcGIS software was used to determine how far or how close these centers are from residential districts in Jeddah City. As shown in
Figure 3, there are quite large parts of Jeddah City that have low health center accessibility, mainly located in the north city districts. After defining accessibility to health centers, the presented study has overlaid population data over the resulting health accessibility zones to define the amount of people that are falling within the poorly-accessible location in Jeddah City.
Figure 5 indicates that there are large population districts that are considered as un-served populations because they fall outside the 30-min travel time accessibility zones. These parts should be given priority for future health center expansion plans made by local health planners in Jeddah City.