Introduction to the Issue
The continued increasing urban population raises concerns regarding municipal public administrators and their ability to effectively provide emergency healthcare services. It is essential for every local community, whether urban or rural, to be able to provide emergency healthcare that is aligned with the needs of pre-hospital care demanded by the population. As population increases in metropolitan cities, it is deductible that there is an increase in the number of traffic accidents, heart attacks, and other medical emergencies that warrant emergency medical services (Beninde, Veith, & Hochkirch, 2015). The increase in the number of inhabitants in the city continues to strain the resources in place as such necessitating an investigation in the delivery of emergency health care services.
The World Health Organization currently recognizes the provision of essential life support to all risk situations involving both individuals and goods as the primary objective of emergency medical services. In this particular context, EMS encompasses the provision of acute pre-hospital care for patients with illnesses or injuries to reduce the degree of lesions or, in some cases, the number of deaths (Pell, Sirel, Marsden, & Ford, 2001). The quality of EMS lies with the response time, which must be controlled to improve the chances of survival in emergencies.
The lack of quality emergency medical care due to long response time has continuously placed the lives of people in the community at stake, especially in the events of accidents such as car accidents. The community continues to face tragic losses with devastating consequences, primarily due to ineffective planning and structuring in EMS. The response time is described as the time between notification and the arrival of the ambulance at the scene. WHO recommends the ideal response time at eight minutes. The current response time is above the recommended eight minutes. Therefore, there is a need for research to determine why there is longer response time and how this response time can be reduced to even an average of five minutes.
How can Research Help
The status of the community healthcare system must be surveyed to ensure that the existing resources are in a position to effectively handle all emergencies in the city within the shortest time possible. Therefore, the research encompasses experimenting, whether qualitatively or quantitatively, to determine why the EMS response time is relatively long and proceed to recommend strategies that might work to reduce the current response time. The research will pinpoint the locations of different emergence departments across the city, nature of the operations, and how these departments coordinate to ensure effective delivery of emergency healthcare in a particular jurisdiction (McDonald, 2015).
The research will showcase the current contribution of the resources in place, including an analysis of their present shortcomings. Indeed, the longer response time might be due to limited resources, or it might be related to disorganization and lack of sufficient coordination in the departments associated with providing EMS. After identifying the specific reasons for the relatively long response time, the research analyzes how to improve the response time. The improvement of response time involves a lot of aspects from better coordination to conducting statistical analysis to determine the best streets to be used. Specifically, the research can help by applying techniques that are capable of quantifying the response time of emergency medical services.
Overview of Scientific Method
The inquiry will be grounded on statistical methods and operational research. The application of analytical techniques will ensure the process is as efficient as possible. Statistics are particularly useful in addressing issues of variability. In variability, it is implied and understood that successive observations of a particular phenomenon do not necessarily produce the same result when in operation (Takeda, Widmer, & Morabito, 2007). Therefore, the application of statistical tools such as descriptive statistics, statistical inference, regression, correlation, and multivariate analysis of data is necessary for quantifying the response time of EMS.
Initially, there is a necessity of trend analysis to establish the response time in past cases, the reason for the delay, and the exact response time that was necessary to avoid devastating consequences to the individual and the community in general. The past data is particularly important in informing future decisions on the best cause of action to achieve and beat the WHO recommended response time (Blanchard, Hagel, Doig, & Anton, 2012). Since the local organizations in charge of emergency medical services readily provide the information necessary to conduct a research to determine the best technique to improve the response time, it will be relatively easy to make the basic statistical descriptions based on the data provided. The research will make use of simulations, algorithms, and data analysis through descriptive statistics to decrease response time, coverage, and routes (Takeda, Widmer, & Morabito, 2007).
Concerns and Recommendation
If the current delivery of emergency care is to be relied on, the community may continue to lose life in addition to causing permanent damage because of the delayed response of mere minutes or seconds. Therefore, the local government must invest in research on the most appropriate course of action to improve on the current response time (Von Vopelius-Feldt, Coulter, & Benger, 2015). Undeniably, the research will provide specific recommendations that will ensure the improvement of response time, which not only saves lives but also work to increase the quality of healthcare.
Beninde, J., Veith, M., & Hochkirch, A. (2015). Biodiversity in cities needs space: a meta-analysis of factors determining intra-urban biodiversity variation. Ecology letter, 581-592.
Blanchard, I. E., Hagel, B., Doig, C., & Anton, A. (2012). Emergency medical services, response time and mortality in an urban setting. Prehospital Emergency Care, 16(1), 142-151.
McDonald, R. I. (2015). The effectiveness of conversation interventions to overcome urban-environment paradox. Annual Academic Science, 1-14.
Pell, J., Sirel, J. M., Marsden, A., & Ford, I. (2001). effect of reducing ambulance response times on deaths from out of hospital cardiac arrest: Cohort study. BMJ Clinical Research, 1385-1388.
Takeda, R. A., Widmer, J. A., & Morabito, R. (2007). Analysis of ambulance decentralization in an urban emergency medical service using the hypercube queueing model. Computer Operations Research, 34(3), 727-741.
Von Vopelius-Feldt, J., Coulter, A., & Benger, J. (2015). The impact of a pre-hospital critical care team on survival from out-of-hospital cardiac arrest. Resuscitation, 290-295.