Introduction
Accessibility shows how easily individuals can get to the necessary services (Luo, 2004). Place and remoteness comprise spatial parameters of accessibility, while demographic factors and socioeconomic status are its non-spatial characteristics (Joseph and Phillips, 1984). The combination of these factors defines the overall accessibility of public facilities. In this paper, the use of spatial accessibility in emergency care will be reviewed. Medical specialists should be able to reach patients quickly; therefore, it is necessary to determine the accessibility associated with changes in demand while deciding on the location of emergency services. There are two components of spatial accessibility: proximity and availability (Khan, 1992; Joseph and Phillips, 1984; Luo and Wang, 2003; McGrail and Humphreys, 2009). According to McGrail and Humphreys (2009), one should take both of them into account to determine spatial accessibility. This suggestion applies to emergency care where proximity and availability play a major role in assessing accessibility. Further, four approaches will be discussed, which are used for measuring spatial accessibility and can be of use while choosing the place for emergency facilities.
Proximity
There are four ways of measuring spatial accessibility of ambulance services. They are proximity, regional availability, the gravity model and the floating catchment area (Guagliardo, 2004; Bagheri, Benwell and Holt, 2006; Langford and Higgs, 2006; McGrail and Humphreys, 2009). The first approach to be discussed is the proximity to the nearest station. It is the most commonly used measure, perhaps, because of its simplicity. Proximity evaluates the remoteness of or travel time to the closest supplier of medical services (Luo, 2004; Langford, Fry and Higgs, 2012). As it was mentioned above, proximity is not the only constituent of spatial accessibility; thus, this measure does not take into account the availability of medical facilities. It fails to assess the ambulance station capacity and the magnitude of the demand. Hence, measuring time or distance to the closest emergency stations is an inadequate way of estimating spatial accessibility.
Regional Availability
The second method of assessing spatial accessibility is regional availability. It measures the allocation of the service site capacity among the population within a particular area; in other words, it is the ratio of supply and demand within specific administrative boundaries (Luo, 2004). This approach is easy to apply because it is usually not difficult to obtain the data of emergency medical services and the population within administrative boundaries. Because of its simplicity, the method is commonly used in public health services. However, the effective use of this approach is hindered because the demand and supply of different regions tend to overlap (Luo, 2004). Therefore, the assumption that people stay within their administrative boundaries and do not turn for medical help in other regions is wrong, which is why this method has undergone criticism.
Gravity Model
The third approach to measuring spatial accessibility is the gravity model. Being initially developed by Hansen in 1959, it resolves the problems related to the traditional access-based method by combining the availability and proximity of facilities (Weibull, 1976; Joseph and Phillips, 1984). The gravity model addresses the relation between supply and demand within different areas by means of a distance-decay function that shows how the accessibility changes with the increase in distance (Weibull, 1976; Joseph and Phillips, 1984; Guagliardo, 2004; Yang, Goerge and Mullner, 2006). Despite the seeming soundness of the gravity model, it has its drawbacks. Its implementation requires many computations, information and skills in programming, and the results are difficult to interpret without specific knowledge (Luo and Qi, 2009). Furthermore, the gravity model assesses the supply but pays no attention to the demand.
Another problem that hinders the implementation of this approach for determining the location of emergency medical services on a broad scale is the need for defining the distance-decay function. Research has shown that the distance-decay function is very complicated to determine (Joseph and Phillips, 1984; Guagliardo, 2004). Moreover, Luo and Wang (2003) found out that the use of this function gives implausible results by showing high accessibility in areas with poor access. However, the main problem with this method is that it assumes that the quantity of available services compensates for the travel time (Luo and Wang, 2003). Luo and Wang (2003) applied this approach to assess spatial accessibility of medical services in Chicago, U.S. They discovered that the accessibility of an individual to two healthcare professionals 20 minutes away was the same as that to one medical specialist 10 minutes away (Luo and Wang, 2003). In the gravity model, accessibility is a continuous variable, but when it is applied to medical facilities, it should be treated as a dichotomous variable (Luo and Qi, 2009). Therefore, this approach is hardly appropriate for assessing spatial accessibility in this field.
Floating Catchment Area
The fourth method to be reviewed is the floating catchment area (FCA). It was designed to address the drawbacks of the methods mentioned above. The main distinction of the FCA is that it uses floating areas rather than set boundaries (McGrail and Humphreys, 2009). Since there was a need to consider both supply and demand in catchment areas, the 2SFCA model was developed (McGrail and Humphreys, 2009). This method is more efficient in determining spatial accessibility for emergency services, and it is still being improved.
Conclusion
To sum up, there are four major methods of measuring spatial accessibility in the emergency care. Proximity is the easiest approach, but it has the lowest efficiency. Regional availability may be used for public services, but it utilizes a faulty assumption that people always stay within their administrative boundaries. The gravity model analyses the supply-and-demand ratio, but it provides inaccurate results and is difficult to implement. The FCA addresses the disadvantages of the previous methods and serves as a base for further improvements.
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