Close-Up on Ambulance Service Estimation in Indonesia: Monte Carlo Simulation Study

Autor: Syaribah N Brice, Justin J Boutilier, Geraint Palmer, Paul R Harper, Vincent Knight, Mark Tuson, Daniel Gartner
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Interactive Journal of Medical Research, Vol 13, p e54240 (2024)
Druh dokumentu: article
ISSN: 1929-073X
DOI: 10.2196/54240
Popis: BackgroundEmergency medical services have a pivotal role in giving timely and appropriate responses to emergency events caused by medical, natural, or human-caused disasters. To provide adequate resources for the emergency services, such as ambulances, it is necessary to understand the demand for such services. In Indonesia, estimates of demand for emergency services cannot be obtained easily due to a lack of published literature or official reports concerning the matter. ObjectiveThis study aimed to ascertain an estimate of the annual volume of hospital emergency visits and the corresponding demand for ambulance services in the city of Jakarta. MethodsIn this study, we addressed the problem of emergency services demand estimation when aggregated detailed data are not available or are not part of the routine data collection. We used survey data together with the local Office of National Statistics reports and sample data from hospital emergency departments to establish parameter estimation. This involved estimating 4 parameters: the population of each area per period (day and night), the annual per capita hospital emergency visits, the probability of an emergency taking place in each period, and the rate of ambulance need per area. Monte Carlo simulation and naïve methods were used to generate an estimation for the mean ambulance needs per area in Jakarta. ResultsThe results estimated that the total annual ambulance need in Jakarta is between 83,000 and 241,000. Assuming the rate of ambulance usage in Jakarta at 9.3%, we estimated the total annual hospital emergency visits in Jakarta at around 0.9-2.6 million. The study also found that the estimation from using the simulation method was smaller than the average (naïve) methods (P
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