Modelling Emergency Medical Services in Indonesia

印度尼西亚紧急医疗服务建模

• 批准号: EP/T003197/1
• 负责人: Paul Harper
• 金额: $ 58.71万
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FT003197%2F1
• 关键词: Modelling; Emergency; Medical; Services; Indonesia

Recent events such as the Anak Krakatau eruption and tsunami, and the Lombok and Palu earthquakes and tsunami have once again brought the attention of the world on Indonesia. In 2018 alone, it is estimated that natural disasters claimed the lives of more than 4,000 people and displaced around 3 million people across the country. Natural disasters, manmade conflicts and violence are commonly experienced across the country, alongside a rising demand for emergency services. The lack of emergency medical transportation across Indonesia is a main barrier to the access and availability of medical care for the 264 million population. Until recently, Indonesia had no public ambulance service but is now moving towards an integrated national emergency response system. There are however many challenges faced including vast geographical areas, severe traffic congestion, and inadequate numbers of ambulances. Making efficient and effective use of such valuable resources is therefore critical and will be the focus of our research, as is helping to empower local services and provide for the poorest in society who cannot afford to take privately run ambulances. The National 118 Emergency Ambulance Service was established in 2005 by the Indonesian Surgeons' Association, and is the only public ambulance service in the country, operating currently in five cities: Jakarta, Palembang, Yogyakarta, Surabaya and Makasser. Whilst some private ambulance providers are available, these are hugely expensive and thus out of reach of the majority of the Indonesian population who consequently suffer from a lack of timely access to medical care and are at high risk of morbidity and mortality. Traffic accidents account for 70% of the country's trauma deaths, and nearly 1 in 3 of all deaths are caused by strokes and ischemic heart disease/heart attacks, where rapid access to appropriate treatment is absolutely vital. In Jakarta alone, 118 serves a potential population of 11 million people (the 15th most populous city in the World and the largest in Southeast Asia), covering an area of 661 square km, but remarkably with only 15 ambulances currently available based at 5 locations across the city. Not surprisingly response times and outcomes are very poor, because of the lack of vehicles, the sheer volume of traffic on the roads (Jakarta is reported to have the worst traffic jams of any major Asian city), and the large area to cover. Our research programme will use Operational Research (OR) methods for mathematical modelling of emergency medical services (EMS). We will work directly with the Founder and Director of the Indonesian National 118 Ambulance Service, Professor Aryono Pusponegoro MD, PhD, and his EMS team to help forecast emergency demand and make critical decisions on the optimal types, capacities and geographical locations of vehicles for a sustainable emergency service. Such factors directly impact on the probability of patient survival, ability to respond to major disasters, and the overall quality of care provided. Our ambitious, adventurous and transformative research programme is underpinned by novel scientific methods that will: (i) develop a methodology to forecast spatiotemporal demand without historical call data using census and survey data within a machine-learning framework, and (ii) develop a novel approach to consider EMS capacities and allocations for maximising survival within a heterogeneous population (multiple medical needs) using a heterogeneous fleet with consideration of multiple vehicle types each with differing travel times/speeds. This will be achieved via the creation of an optimisation and simulation decision-support framework that will be deployed by the national 118 emergency ambulance service.

最近发生的诸如Anak Krakatau火山爆发和海啸以及龙目岛和帕卢地震和海啸等事件再次引起了世界对印度尼西亚的关注。据估计，仅在2018年，自然灾害就夺去了4,000多人的生命，并使全国约300万人流离失所。自然灾害、人为冲突和暴力在全国各地普遍存在，同时对紧急服务的需求不断增加。印度尼西亚全国缺乏紧急医疗运输是2.64亿人口获得医疗服务的主要障碍。直到最近，印度尼西亚还没有公共救护车服务，但现在正在向综合国家应急系统迈进。然而，面临着许多挑战，包括广阔的地理区域，严重的交通拥堵和救护车数量不足。因此，高效和有效地利用这些宝贵的资源至关重要，也将是我们研究的重点，因为这有助于增强当地服务的能力，并为那些负担不起私人救护车的社会最贫困者提供服务。国家118紧急救护车服务由印度尼西亚外科医生协会于2005年建立，是该国唯一的公共救护车服务，目前在五个城市运营：雅加达，帕伦邦，日惹，泗水和Makasser。虽然有一些私人救护车提供者，但这些救护车价格昂贵，因此大多数印度尼西亚人无法获得医疗服务，因此无法及时获得医疗服务，发病率和死亡率很高。交通事故占该国创伤死亡人数的70%，近三分之一的死亡是由中风和缺血性心脏病/心脏病发作引起的，迅速获得适当的治疗是绝对重要的。仅在雅加达，118就为1100万潜在人口提供服务（世界第15大人口城市，东南亚最大的城市），占地面积661平方公里，但值得注意的是，目前只有15辆救护车分布在全市的5个地点。毫不奇怪，由于缺乏车辆，道路上的交通量（据报道，雅加达是亚洲任何主要城市中交通堵塞最严重的城市）以及需要覆盖的大面积，响应时间和结果非常差。我们的研究计划将使用运筹学（OR）方法对紧急医疗服务（EMS）进行数学建模。我们将直接与印度尼西亚国家118救护车服务的创始人兼主任Aryono Pusponegoro博士及其EMS团队合作，帮助预测紧急需求，并就可持续紧急服务的车辆的最佳类型，容量和地理位置做出关键决策。这些因素直接影响到患者的生存概率、应对重大灾难的能力以及所提供护理的整体质量。我们雄心勃勃，冒险和变革性的研究计划以新颖的科学方法为基础，这些方法将：（i）在机器学习框架内，利用普查和调查数据，在没有历史呼叫数据的情况下，制定一种预测时空需求的方法，和（ii）开发一种新的方法来考虑EMS容量和分配，以最大限度地提高异质人群中的生存率（多种医疗需求）使用异构车队，考虑到多种车辆类型，每种车辆类型具有不同的行驶时间/速度。这将通过创建一个优化和模拟决策支持框架来实现，该框架将由国家118急救车服务部署。

项目成果

A game theoretic model of the behavioural gaming that takes place at the EMS - ED interface

• DOI: 10.1016/j.ejor.2022.07.001
• 发表时间: 2022-07
• 期刊: Eur. J. Oper. Res.
• 作者: M. Panayides;Vince Knight;Paul Harper

Still looking in the wrong place: Literature-based evidence of why patients really attend an emergency department

• DOI: 10.1016/j.seps.2023.101707
• 发表时间: 2023-10-09
• 期刊: SOCIO-ECONOMIC PLANNING SCIENCES
• 影响因子: 6.1
• 作者: Behrens，Doris A.;Morgan，Jennifer S.;Gartner，Daniel
• 通讯作者: Gartner，Daniel

Emergency services utilization in Jakarta (Indonesia): a cross-sectional study of patients attending hospital emergency departments.

• DOI: 10.1186/s12913-022-08061-8
• 发表时间: 2022-05-13
• 期刊: BMC HEALTH SERVICES RESEARCH
• 影响因子: 2.8
• 作者: Brice, Syaribah Noor;Boutilier, Justin J.;Gartner, Daniel;Harper, Paul;Knight, Vincent;Lloyd, Jen;Pusponegoro, Aryono Djuned;Rini, Asti Puspita;Turnbull-Ross, Jonathan;Tuson, Mark
• 通讯作者: Tuson, Mark