Introduction
Emergency medical services (EMS) provide crucial, life-saving care to patients in a variety of settings. In particular, ambulance and air evacuation services are critical, as they can save a patient who cannot get to a hospital on their own. To provide effective care, it is essential for ambulances and air evacuation services to arrive and deliver patients to a care facility promptly. The present literature review will reflect the importance of studying the topic, the standards for an ambulance and air evacuation in different countries, and the use of geographic information systems (GIS) in emergency services.
The Importance of the Topic
EMS is an essential part of health care that helps to ensure adequate care delivery in urgent circumstances. EMS usually involve call centres, dispatchers, and ambulances staffed with qualified paramedics (Gholami-Zanjani, Pishvaee, & Ali Torabi, 2017). Due to the complex structure, operations in EMS include a set of procedures from receiving calls and dispatching ambulances or air evacuation to providing medical treatment on-site and delivering a patient to the nearest facility (Gholami-Zanjani et al., 2017). As the following sections will show, improving ambulance and air evacuation using research supports care provision, improves response time, and allows addressing healthcare disparities.
Care Provision
First of all, the research of ambulance and air evacuation helps to outline the population’s needs with regards to emergency medical care. For example, stroke is among the most critical acute illnesses, and it threatens the patient’s life if not addressed promptly. In Australia, approximately 56,000 cases of stroke are recorded each year (The Council of Ambulance Authorities [CAA], 2018). Fast response to stroke is crucial because, for every minute that passes without adequate treatment, the patient loses up to 2 million neurones, which contributes to brain damage (CAA, 2018).
An ambulance can provide urgent medical services and deliver the patient to the nearest medical institution, thus reducing brain damage and increasing their chances of survival. Research into ambulance services and stroke enabled to development of guidelines to determine if a patient has a stroke and requires to be taken to the hospital (CAA, 2018).
Moreover, research also showed that there are certain issues with delivering patients to a facility that meets the requirements to provide adequate stroke treatment. For instance, CAA (2018) reported that after ambulances usually transport stroke patients to the nearest facility, they often need to be transferred to a different institution for neurosurgical or endovascular care, which worsens patient outcome due to time delays. Further research into the subject would improve the capacity of Australian EMS to provide timely and efficient care to patients with stroke, thus enhancing survival and recovery rates.
Another example of using research to improve the work of ambulance and air evacuation is determining procedures and treatment that would be beneficial to emergency medical care. Naumann et al. (2018) studied the use of intravenous fluids during air ambulance treatment of patients in the United Kingdom. The research found that most patients received 0.9% saline for hypotensive trauma, and some also received Hartmannās solution (Naumann et al., 2018).
The authors also found that there was a gap in services provided by air ambulance due to the lack of prehospital blood products (PHBP). The research showed that providing PHBP would save approximately 800 patients annually by making care delivery more efficient (Naumann et al., 2018). This research can be used to improve the capacity of national EMS to respond to emergencies by proving the necessity of expanding the range of treatments offered by air ambulances.
Response Time
Response time is also a prevalent topic of research with regards to EMS. Insufficient response time affects patient outcomes by delaying the administration of treatment. In life-threatening circumstances, two or three minutes can be crucial, as seen in the example of stroke patients. Lower response time promotes the accessibility of services and vice versa (Gholami-Zanjani et al., 2017). However, there are multiple factors that affect response time, from internal operations to the patient’s distance from an EMS station. Research can assist in understanding these factors and ensuring adequate coverage of EMS services.
For example, a study by Lam et al. (2015) sought to determine the variables affecting ambulance response time. According to the researchers, weather, traffic, and patient location were the most critical factors influencing response time. Long average response time was almost 13 times more common under heavy traffic conditions than under light traffic conditions (Lam et al., 2015). In a similar manner, heavy rain doubled the possibility of long response time (Lam et al., 2015).
Although the distance to a patient was significant, the researchers found an interesting correlation between the type of buildings where patients were located and the response time. For homes and commercial destinations, the average response time of an ambulance was significantly higher than for road incidents (Lam et al., 2015). Studying the factors influencing response time can assist in reducing it through opening more EMS stations, developing new routes, and making changes to operations.
The location of EMS facilities is crucial to reducing the average response time of ambulance or air evacuation services. According to Gholami-Zanjani et al. (2017), the operations in most EMS systems choose a dispatch facility automatically, based on factors such as staff availability and time to destination. The systems used by EMS have three key goals: minimising the average response time, minimising the maximum response time, and maximising the geographical area that can be covered within a particular response time (Gholami-Zanjani et al., 2017).
Research on system configurations and supporting tools, such as geographic information systems (GIS), is essential to achieving these goals and increasing the responsiveness of EMS. For instance, GIS can contribute to decision support systems that choose options for reducing response time (Gholami-Zanjani et al., 2017). Overall, considering the response time of EMS from the perspective of the ambulance and air evacuation services provides insight into problems and helps to generate solutions.
Addressing Healthcare Disparities
Disparities in access to care and patient outcomes exist in most countries. Reducing these disparities has a positive effect on population health. EMS services, in particular, are concerned with improving access to care regardless of patients’ background and their location. Geographical justice is a critical concept in EMS as it considers location-based healthcare disparities (Rosenberg, 2013). Research on the use of EMS services, including ambulance and air evacuation, can help to underline and address existing disparities, thus contributing to population health outcomes.
Firstly, improving the efficiency of the ambulance and air evacuation can lead to a significant reduction in location-based disparities. Research showed that the use of ambulance services decreases in less developed areas (Liu et al., 2015). Neighbourhood characteristics, such as health infrastructure and demographic make-up, can also create geographical health disparities (Rosenberg, 2013). Improving the coverage of EMS could contribute to the development of health infrastructure in remote areas, thus addressing location-based disparities.
Research on the ambulance and air evacuation services can also generate ideas for policy changes needed to reduce healthcare disparities. According to multiple studies, socioeconomic factors play an essential role in determining patients’ utilisation of emergency services. One of the most crucial variables was insurance status. According to a study by Seo, Begley, Langabeer, and DelliFraine (2014), over 85% of those willing to use emergency services were insured.
In countries where there is no universal healthcare, such as the United States, the correlation of insurance coverage and EMS use can have a critical influence on population health. Income was also a significant predictor of EMS use due to the burden of medical costs (Seo et al., 2014). This information can assist governments in reducing health disparities and increasing access to care through policy changes.
Lastly, racial and ethnic disparities can also be addressed in research studies and programs. As noted by Mochari-Greenberger et al. (2015), racial and ethnic minorities are less likely to use EMS than white people, which contribute to health disparities experienced by these populations. Determining reasons for racial and ethnic differences in an ambulance or air evacuation use can provide insight and help generate viable, long-term solutions.
For instance, Phung et al. (2015) studied inequality in ambulance care received by people of colour. According to researchers, “Inequalities in prehospital care for ethnic minority groups are underpinned by problems of cultural awareness in professionals; language and communication difficulties; and a limited understanding of how the healthcare system operates for some minority groups” (p. 37). Improving EMS delivery to and use by ethnic minorities would thus require policy and organisational changes addressing these issues. Providing paramedics with training on culturally sensitive care or creating linguistically diverse emergency response teams could be among the useful strategies.
National Standards in Emergency Services
There are numerous variables that affect how national standards in emergency services are set and updated. For example, the duties of EMS service providers might differ from one country to another. In most countries, EMS providers are responsible for receiving and processing emergency calls and arranging patient transportation (Reuter-Oppermann, van den Berg, & Vile, 2017). However, different types of ambulances can also perform various functions, such as life support (Reuter-Oppermann et al., 2017). The standard service time for different types of calls will vary depending on the availability and workload of various ambulances.
An excellent example of differences in standards is the differentiation between patient transports and emergency calls. Emergency calls are made in life-threatening events, whereas patient transport calls are made for patients who require assistance with transportation to a hospital due to injury or illness (Reuter-Oppermann et al., 2017). In the Netherlands, the standard response time is 30 minutes for patient transports and 15 minutes for emergency calls, whereas, in the UK, the standards are 8 minutes for emergencies (Care Quality Commission, 2014; Reuter-Oppermann et al., 2017).
The set standards are influenced by the capacity of the national EMS system, as well as the demand for services. The UK has a robust EMS system with a large number of ambulances on call at all times, thus allowing for a reduced response time.
The present section will seek to compare EMS standards used in the USA, Germany, Saudi Arabia, and Australia. In particular, response time and classification of calls will be taken into account to allow for comparing EMS functions in these countries. The section will also attempt to provide a rationale for setting a particular standard for response time based on previous research and geospatial analysis.
USA
In the United States, EMS services are guided by the NFPA 1710 standard, which is regularly updated to ensure coherence. NFPA 1710 provides guidelines and standards for fire departments, EMS, and special operations (NFPA, 2016). There are three different levels of EMS treatments set out by the standards: First Responder, Basic Life Support (BLS), and Advanced Life Support (ALS). According to the International Association of Fire Fighters (IAFF, 2017), personnel deployed to ALS emergency responses shall include, at a minimum, two paramedics and two BLS members.
There are no standard response times set on the federal level, which allows states, districts, and counties to regulate response times based on needs and available resources. However, as reported by Racht and Turpen (2013), in 90% of communities, First Responders had a standard response time of 4 minutes, and ALS ambulances had a standard of 8 minutes. Although there are various factors impacting the response time of a particular ambulance, a short standard response time reflects the overall capacity of EMS services in America.
Germany
In Germany, EMS operations are somewhat similar in terms of geospatial distribution. There are 16 critical areas in the country, each having a separate EMS system (Malteser, 2018). There are three types of EMS available to the public in case of a medical emergency: road ambulances, air rescue, and emergency doctor service (Malteser, 2018). There are no specific guidelines for EMS operations on the national level, although some standards are developed locally (Malteser, 2018).
However, the local EMS systems are structured in a way that allows for a fast response to any location. Malteser (2018) reports that there are at least 88 helicopters utilised by the country’s EMS, which means that in any place, an EMS helicopter is available within a 50-kilometre radius. As a result, the maximum response time of EMS services in Germany is 15 minutes (Malteser, 2018). The effectiveness of Germany’s EMS functions is also evident from research. For example, a study by BĆ¼rger et al. (2018) found that the response time of German EMS services was always between 1 and 10 minutes. The results show that despite the lack of national EMS standards, local EMS systems in Germany are efficient in providing medical care to patients.
Saudi Arabia
In Saudi Arabia, EMS is provided by the Saudi Red Crescent Authority (SRCA), which is a national healthcare agency. There are two levels of the national EMS system in Saudi Arabia, including a network of public health centres and specialised hospitals in large cities (Al Mutairi et al., 2018). SRCA acts as an assistance agency to other medical facilities in the kingdom, which allows it to ensure the presence of staffed ambulances on call at all times (Al Mutairi et al., 2018).
There are two types of ambulance services based on patients’ needs: ALS and BLS. ALS is staffed with paramedics who are qualified to perform invasive procedures in the ambulance to preserve a patient’s life until arrival at the nearest facility Al Mutari et al., 2018). There are no national standards of EMS operations in Saudi Arabia and no guidelines for implementing such standards locally. The international standard of 8 minutes is usually applied in research. Nevertheless, the average response time of ambulances in Saudi Arabia was found to be 13 minutes in its capital city, Riyadh (Alnemer et al., 2016). This allows suggesting that response time in remote areas may be higher due to the lower availability of ambulances and fewer hospitals.
Australia
EMS in Australia are regulated by state governments, and thus there are no formal national standards with regards to EMS procedures. Incidents are classified based on the level of urgency, and ambulances respond to an emergency (code 1), urgent (code 2), and non-emergency (codes 3, 4) calls (Productivity Commission, 2018). There are no national standards for ambulance response times in Australia. According to the Productivity Commission (2018), 90% of state-wide ambulances reach patients in 14.3 to 31.4 minutes, depending on the incident. For instance, in New South Wales, the median response time for emergency cases was 7.47 minutes in 2016-2017 (NSW Government, 2018). However, as only 50% of ambulances arrived within this time, it can be assumed that in many cases, the response time for emergency or urgent calls can be much higher.
Comparison
Out of the four countries, formal standards for response times and EMS operations were only adopted in the United States and Germany. These countries also had lower response times of ambulances in comparison to Saudi Arabia and Australia. This finding suggests a correlation between formal standards and EMS systems performance. However, it could also mean that countries that perform well on EMS services have a greater overall capacity of their EMS systems. Research on average response times in Saudi Arabia and Australia shows that, in both cases, there is room for significant improvement (Alnemer et al., 2016; NSW Government, 2018).
Lowering the average response time on a national level would benefit patients by promoting their health outcomes and reducing geographical healthcare disparities. In order to achieve this goal, it is critical to adopt formal standards of EMS operations and response time, as well as ensure that there is a robust network of ambulances in all parts of the country.
Rationale
Standards for ambulance response times are mostly based on previous research and the capacity of EMS systems. For example, a study by BĆ¼rger et al. (2018) showed that, in life-threatening circumstances, increases in mean response time reduce discharge rates. The researchers note that “among patients who did not receive bystander resuscitation, the discharge rate declined from 12.9% at a mean response time of 1 minute and 10 seconds to 6.4% at a mean response time of 9 minutes and 47 seconds” (BĆ¼rger et al., 2018, p. 541).
Another study by Goto, Funada, and Goto (2018) highlighted that, with every minute of response time, the patient’s odds of neurologically intact survival at one month after cardiac arrest decreased. The authors concluded that response times of 11-13 minutes would only result in neurologically intact survival if patients receive defibrillation or cardiopulmonary resuscitation by bystanders (Goto et al., 2018). Assuming that there is no bystander intervention, setting a standard response time under 10 minutes is justified.
Another reason for lower standard response time in certain countries is the use of geospatial analysis, as it helps to expand the capacity of EMS systems. Firstly, geospatial analysis allows estimating the average response time for EMS systems operating in a specific area. Thus, if a state or county government seeks to set a new standard response time, it can use data from medical research and geospatial analysis to determine a time that is beneficial for patients and operationally feasible. Secondly, the use of geospatial analysis for ambulance deployment also results in decreased arrival times, both for road ambulances and air ambulances (Alharbi, 2015; Ong et al., 2010; Swalehe & Atkas, 2016). Therefore, EMS systems that utilise geospatial analysis as part of their operations can set a lower standard response time.
Recent Research on GIS
Recent research on the use of GIS in EMS operations focuses primarily on utilising the system for improving service delivery and optimising operations. For example, a study by Baloyi, Mokgalaka, Green, and Mans (2017) considered his use of a GIS-based accessibility analysis to evaluate service levels of public ambulances. In particular, the study aimed to determine if the distribution of EMS stations in a specific area was sufficient and adequate to ensure arrival within the standard time frame. The research showed that GIS could be used to evaluate the capacity of local EMS systems and outline gaps in their operations (Baloy et al., 2017).
In the given case, the area showed satisfactory results in EMS distribution, but the allocation of vehicles was uneven (Baloy et al., 2017). A GIS-based framework was used to predict system performance under different scenarios, which shows its value for improving EMS delivery and operations.
Another recent study of GIS considered its use for optimising regional health emergency services in Morocco. Khalfaoui and Hammouche (2018) used GIS mapping to achieve several important goals. First of all, GIS helped to evaluate the overall capacity of the regional network and its current effectiveness. Secondly, the researchers tested the performance of regional health emergency network under different scenarios, such as a traffic incident requiring fast EMS response and a high number of EMS urgent calls for individual patients.
Finally, based on the results of the analysis, the authors suggested a decision-support model based on GIS that would help to improve the performance of regional EMS networks (Khalfaoui & Hammouche, 2018). The study is valuable to the topic, as it portrays several possible applications of GIS for improving EMS delivery to the public. Modelling EMS activity in different scenarios is particularly beneficial because it allows testing the current system for emergency preparedness instead of evaluating it under regular circumstances.
The possible influence of GIS on evacuation planning is also a popular topic in recent research. Mohamed, Kosba, Mahar, and Mesbah (2017) used a combination of GIS and decision-support systems to devise local emergency preparedness and response plans. The application of GIS, in this case, enabled the assessment of different route options and planned for optimal response to various emergency scenarios.
For example, the authors applied GIS to modelling different evacuation routes and established the best alternative (Mohamed et al., 2017). GIS also allowed determining the nearest safe destinations that could be used for evacuation purposes in a variety of emergencies. Based on this study, the application of GIS in evacuation planning can be beneficial because it improves EMS system capacity indirectly by optimising its operations in different scenarios.
A different study by Alharbi (2015) considered the potential use of GIS to reduce the response time of air ambulance services. The author used GIS to develop an extensive decision-support system that could optimise air ambulance performance through improving allocation, direction, and distance analysis (Alharbi, 2015). This is one of a few studies that assessed the application of GIS to air ambulance services, and thus it contributes to the growing body of knowledge regarding the importance of GIS. Aminzadeh, Rabiee, Rezaei, and Bahmanabadi (2017) also evaluated the usefulness of GIS to EMS systems by applying it to decision-making processes in hospitals and ambulance centres.
The study showed that GIS has numerous applications in the field of EMS. The authors found that it helps to reduce ambulance response time by routing, assists in emergency operations planning, and ensures optimal allocation of ambulance patients to hospitals based on distance, availability, and disease prevalence (Aminzadeh et al., 2017). This is a useful study that reviews general applications of GIS in EMS operations, thus highlighting the importance of the system.
GIS Application Issues
Despite the potential benefits of GIS that are well-described in various research studies, the application of GIS for location and relocation of health services poses some problems. First of all, as described by Fletcher-Lartey and Caprarelli (2016), geographical information systems use highly complex data that cannot be applied to all areas and settings evenly. For example, GIS can conflict with traditional applications used for location and relocation of health services, thus producing contradicting analysis results. The possibility to use GIS for simulation is also limited due to the need for specialised analysis of information obtained from it (āLimitations and challenges of GIS,ā 2018). Therefore, when planning location or relocation using GIS, facilities and service providers might experience issues that require utilising additional applications.
The second issue that comes with the use of GIS for location and relocation is the lack of necessary GIS infrastructure (Fletcher-Lartey & Caprarelli, 2016). GIS software and tools required for analysing GIS data are usually very expensive, which creates problems for applying GIS in resource-limited settings (Fletcher-Lartey & Caprarelli, 2016). As the healthcare budget in most countries is limited, this can prove to be a crucial problem impeding GIS application. Additionally, due to the complexity of the system, it is not possible to use a single GIS function to solve a specific problem (e.g., reducing ambulance response time). The use of GIS for any purpose requires a complex operational infrastructure, which limits the scope of its application in practice.
Thirdly, limited access to high-quality spatial data in GIS is also an important issue. Fletcher-Lartey and Caprarelli (2016) state that the availability of high-quality spatial and healthcare data in GIS is limited. Finally, there is a shortage of staff that is qualified in using GIS and has prior experience with the system (Fletcher-Lartey & Caprarelli, 2016). As location and relocation of health services are usually performed within a tight timeframe, poor access to qualified personnel makes GIS application in these settings problematic. Nevertheless, as GIS becomes more popular all over the globe, these two issues might resolve.
Conclusion
Overall, effective EMS operations are critical to preserving a patient’s life and reducing the possibility of long-term consequences. The analysis of EMS systems in the United States, Germany, Saudi Arabia, and Australia showed that the application of EMS standards is uneven, leading to higher ambulance response time in certain countries. Geospatial analysis and GIS could be used to address common issues in EMS, including ambulance response time. Nevertheless, the lack of GIS infrastructure, the complexity of the system, and the limited availability of resources create issues for GIS implementation. Future development of GIS technology could enhance its applicability; in the current circumstances, using GIS for location and relocation creates more problems than opportunities.
References
Alharbi, R. (2015). A GIS-Based decision support system for reducing air ambulance response times: A case study on public schools in Jeddah City. Journal of Geographic Information System, 7(4), 384-390.
Al Mutairi, M., Jawadi, A., Al Harthy, N., Al Enezi, F., Al, N., Jerian, A. A. Q.,… Al Anazi, A. (2016). Emergency medical service system in the Kingdom of Saudi Arabia. Emergency, 4(10), 13084-13092.
Alnemer, K., Al-Qumaizi, K. I., Alnemer, A., Alsayegh, A., Alqahtani, A., Alrefaie, Y.,… Alhariri, A. (2016). Ambulance response time to cardiac emergencies in Riyadh. Imam Journal of Applied Sciences, 1(1), 33-38.
Aminzadeh, S., Rabiee, M., Rezaei, Y., & Bahmanabadi, M. (2017). The role of GIS in information system, management and decision making in hospitals and ambulance centers. International Journal of Body, Mind and Culture, 4(1), 18-23.
Baloyi, E., Mokgalaka, H., Green, C., & Mans, G. (2017). Evaluating public ambulance service levels by applying a GIS based accessibility analysis approach. South African Journal of Geomatics, 6(2), 172-183.
BĆ¼rger, A., Wnent, J., Bohn, A., Jantzen, T., Brenner, S., Lefering, R.,… Fischer, M. (2018). The effect of ambulance response time on survival following out-of-hospital cardiac arrest. Deutsches Ćrzteblatt International, 115(33-34), 541-555.
Care Quality Commission. (2014). A fresh start for the regulation of ambulance services. Web.
The Council of Ambulance Authorities (CAA). (2018). The patient: At the centre of everything we do. Web.
Fletcher-Lartey, S. M., & Caprarelli, G. (2016). Application of GIS technology in public health: Successes and challenges. Parasitology, 143(4), 401-415.
Gholami-Zanjani, S. M., Pishvaee, M. S., & Torabi, S. A. (2018). OR models for emergency medical service (EMS) management. In C. Kahraman & Y. I. Topcu (Eds.), Operations Research Applications in Health Care Management (pp. 395-421). Cham, Switzerland: Springer.
Goto, Y., Funada, A., & Goto, Y. (2018). Relationship between emergency medical services response time and bystander intervention in patients with outāofāhospital cardiac arrest. Journal of the American Heart Association, 7(9), e007568.
International Association of Fire Fighters (IAFF). (2017). NFPA Standard 1710. Web.
Khalfaoui, I., & Hammouche, A. (2018). GIS platform for the optimized management of the health emergency services regional network (HES-RN) in Morocco. In Proceedings of the International Conference on Geoinformatics and Data Analysis (pp. 117-121). New York, NY: ACM.
Lam, S. S. W., Nguyen, F. N. H. L., Ng, Y. Y., Lee, V. P. X., Wong, T. H., Fook-Chong, S. M. C., Ong, M. E. H. (2015). Factors affecting the ambulance response times of trauma incidents in Singapore. Accident Analysis & Prevention, 82(1), 27-35.
Limitations and challenges of GIS. (2010). Web.
Liu, Y., Jiang, Y., Tang, S., Qiu, J., Zhong, X., & Wang, Y. (2015). Analysis of the equity of emergency medical services: A cross-sectional survey in Chongqing city. International Journal for Equity in Health, 14(1), 150-157.
Malteser. (2018). Medical rescue services in Germany. Web.
MochariāGreenberger, H., Xian, Y., Hellkamp, A. S., Schulte, P. J., Bhatt, D. L., Fonarow, G. C.,… Smith, E. E. (2015). Racial/ethnic and sex differences in emergency medical services transport among hospitalized US stroke patients: analysis of the National Get With The GuidelinesāStroke Registry. Journal of the American Heart Association, 4(8), 1-10.
Mohamed R. E., Kosba E., Mahar K., Mesbah S. (2018). A framework for emergency-evacuation planning using GIS and DSS. In V. Popovich, M. Schrenk, J. C. Thill, C. Claramunt, & T. Wang (Eds.), Information Fusion and Intelligent Geographic Information Systems (pp. 213-226). Cham, Switzerland: Springer.
National Fire Protection Association (NFPA). (2016). NFPA 1710: Standard for the organization and deployment of fire suppression operations, emergency medical operations, and special operations to the public by career fire departments. Web.
Naumann, D. N., Hancox, J. M., Raitt, J., Smith, I. M., Crombie, N., Doughty, H.,… Midwinter, M. J. (2018). What fluids are given during air ambulance treatment of patients with trauma in the UK, and what might this mean for the future? Results from the RESCUER observational cohort study. BMJ Open, 8(1), e019627.
NSW Government. (2018). Response times. Web.
Ong, M. E. H., Chiam, T. F., Ng, F. S. P., Sultana, P., Lim, S. H., Leong, B. S. H.,… Anantharaman, V. (2010). Reducing ambulance response times using geospatialātime analysis of ambulance deployment. Academic Emergency Medicine, 17(9), 951-957.
Phung, V. H., Siriwardena, N., Windle, K., Asghar, Z., Barot, M., Kai, J., & Johnson, M. (2015). Ethnicity and prehospital emergency care provided by ambulance services. Web.
Productivity Commission. (2018). Chapter 11: Ambulance services. Web.
Racht, E., & Turpen, L. (2013). EMS response time standards: Time to move? Web.
Reuter-Oppermann, M., van den Berg, P. L., & Vile, J. L. (2017). Logistics for emergency medical service systems. Health Systems, 6(3), 187-208.
Rosenberg, M. (2014). Health geography I: Social justice, idealist theory, health and health care. Progress in Human Geography, 38(3), 466-475.
Seo, M., Begley, C., Langabeer, J. R., & DelliFraine, J. L. (2014). Barriers and disparities in emergency medical services 911 calls for stroke symptoms in the United States adult population: 2009 BRFSS Survey. Western Journal of Emergency Medicine, 15(2), 251-259.
Swalehe, M., & Aktas, S. G. (2016). Dynamic ambulance deployment to reduce ambulance response times using geographic information systems: A case study of Odunpazari District of Eskisehir Province, Turkey. Procedia Environmental Sciences, 36, 199-206.