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Response time is the amount of time required to provide medical care from the moment of receiving a call up to the scene (Khorasani-Zavareh et al. 2018). Moreover, the emergency medical response system is a complicated network. It consists of several elements, and each has unique structures that can be investigated, analysed, and improved in the case of detecting deficiencies (Vasilyeva et al., 2018). It is considered to be a critical factor in defining the victim’s survival and recovery (El Sayed et al., 2017).
Numerous studies conclude that there is a correlation between survival and response time, especially with evident ailments (Burger et al., 2018; Cho, You & Yoon 2017; Ong et al. 2010). For instance, early treatment has a significant impact on outcomes and survival. Both are clarified by the notion of a “survival chain.” This conceptual idea implies that early detection of all four “links” in the survival chain will improve the statistics in cardiac arrest outside the hospital.
The links are claimed to be early access to medical care: the activation of the emergency medical care system (EMS) by calling the medical control room, initial cardiopulmonary resuscitation (CPR), defibrillation, and early treatment, such as airway management, are ways to influence the survival data. Researchers note that chances of survival are reduced by 10% per minute if OHCA is left unattended. The convincing evidence precisely indicates the significance of conducting an early (in <4 minutes) defibrillation (Association 2015).
It is possible to note that in the case of basic and advanced life support after 4 and 8 minutes, respectively, survival would be significantly reduced (Doumouras et al. 2012; Jánošíková et al. 2019). Therefore, they propose the emergency response of basic and advanced life support providers as recommended guidelines. Though the study reported solely on the results of cardiac arrest, recommendations for response times to all reactions that occurred and to any disease or injury were subsequently summarised (Doumouras et al. 2012؛ Pons et al. 2005).
On the other hand, spatial factors included responding time (Earnest et al. 2012; Jezek et al. 2011), transportation distance (Cho, J, You, M & Yoon, YJPo 2017), residential density (Uber et al. 2017) and rural-urban diversity (Alanazy et al. 2019). The first two agents from the call to hospitalisation were precisely related to the EMS time interval. It has been reported that a response time increased survival with the activation of a small emergency medical care system (Earnest et al., 2012).
It was believed that the last two factors represent spatial heterogeneity in each region. Moreover, the extensional allocation of ambulance hospitals and the density of emergency medical care system coverage were influenced by the fundamental socio-economic situation.
Several studies that take into consideration the influence of traffic conditions when analysing response times depending on vehicle speed have been conducted. Peleg and Pliskin calculated the ambulance speeds for five daily shifts on weekdays, using the actual driving time taken from the logbook and the distance determined by GIS. Based on speed information, they worked out GIS-derived polygons to introduce geographic areas with a maximum response time of 8 minutes.
The researchers made a conclusion that 94% of actual cases corresponded to the 8-minute standard if ambulances were located within the polygon (Peleg & Pliskin 2004). Schmid and Doerner solved the problem of ambulance location and transfer up to 10% by virtue of speed changes of the ambulance during the day (Schmid, V & Doerner 2010). Generally, two studies demonstrate substantial differences in speed depending on time and region.
The changes prove that speed and resulting travel times during peak hours can significantly vary during the day in areas with high traffic. However, other studies do not adequately consider changes in speed due to conditions common to the traffic system, such as a traffic jam. It is possible to note that the travel speed is generally permanent. For instance, speed limits on roads (Patel et al. 2012), hypothetical values based on types of ways and pavements are constant (Jezek et al. 2011). The general agreement in these studies is that it is necessary to realise the calculation of travel time, which may reflect functional movement conditions.
However, with sufficient resources and a good road condition, the response time with respect to EMS may not work efficiently if demographic and socio-economic characteristics are not taken into account. For example, an emergency station in an area with a large number of elderly residents may receive more calls at any time. The location of emergency services, considering the total population, can make these emergency services maladaptive to respond quickly to a request.
Researchers note that the construction of new ambulances is one of the first public investments (Basar et al., 2012). Wrong decisions about the location of medical institutions have a significant impact on healthcare and society, in addition to simple indicators of cost and service. For example, inaccessible medical facilities may be associated with an increased sickness rate and mortality (Ahmadi-javid, Seyedi and Syam, 2017).
Thus, it is crucial not only to find emergency stations for a reliable and effective system of emergency response. It is possible to note that strategic planning is critical, considering all aspects, in determining the location of a potential future emergency medical care system to respond to urgent calls and save lives (Murray, Tong and Grubesic, 2012). The location choice of new primary medical care facilities is a multilayered process, which consists of objective and subjective reasons (Dudko et al., 2018).
An example of an objective cause can be demographic data of the population and any other statistics related to the target population (Dudko et al., 2018). Subjective reasons include public opinion, which can be assessed by consulting with the concerned communities. According to the researchers, variables such as perceived demand, ecological factors, transport and cityscape, as well as some others, may be taken into consideration (Dudko et al., 2018).
In conclusion, both objective and subjective factors are thought to be essential causes in facilitating the process of making decisions. It should be borne in mind that in some cases, a compromise may be required to coordinate one or another (Vickery 2011). In addition, based on the review of literature, as shown in the table, no studies have been carried out to conjoin these considerations. Both spatial and non-spatial factors to improve response times in emergency medical services in this area have not been included yet. Thus, taking into account the above facts from various studies, the conclusion is that improving response time contributes to an increase in patient survival.
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