Improving Emergency Medical System using Machine Learning through E-mergency to Overcome Trauma Care Problems in Indonesia

Main Article Content



Introduction In Indonesia, the number of road traffic accidents (RTA) in 2019 shows an increasing trend, where they caused high mortality and morbidity rate. It is crucial to establish adequate early management of RTA victims by shortening the time needed to mobilize the victims into nearby hospitals and for the bystanders to perform first aid care. Despite its importance, the Indonesian citizens’ knowledge in first aid seems to be low, and there are no current systems capable of solving RTA prehospital care-related problem gaps.

Method This paper is created through the discussion outcomes with several stakeholders and analysis of journal articles and media reports in Indonesia.

Findings No concrete studies examined Indonesian citizens’ knowledge about first aid care, and no proposals regarding emergency-designed applications had all the qualities we look for.

Proposed solution(s) We proposed E-mergency, which uses Machine Learning in its back-end to provide features for (1) reporting RTAs based on their precise location, (2) sending the best suggestion to the integrated networks of nearby ambulances, trauma centers, health facilities, or hospitals, (3) describing the overall situation of RTAs and general status of the victims, (4) Badan Penyelenggara Jaminan Sosial (BPJS) insurance payment options via digital wallets to the assigned hospital that would accept the patients, and (5) providing instructional first aid videos that the users can watch as guidance for them to help the victims before paramedics come to prevent most of the mortality and morbidity rate caused by RTA in Indonesia.

Conclusion Comprehension and capability of first aid by bystanders and the victim themselves could be an effective way to optimize golden hour usage and thus, prevent most of the mortality and morbidity rate caused by RTA in Indonesia. Developing E-mergency by utilizing smartphone technology could be a new solution to overcome the trauma problems in Indonesia.

Article Details

How to Cite
Tatyana Milenia, Shaffana Hidayat, Anis Rohmasari and Haya Sabrina Eka Putri (2021) “Improving Emergency Medical System using Machine Learning through E-mergency to Overcome Trauma Care Problems in Indonesia”, Journal of Asian Medical Students’ Association. Kuala Lumpur, Malaysia. Available at: (Accessed: 7July2022).
White Papers (AMSA Intl Academic Competition)


World Health Organization (WHO). Global health estimates: Leading causes of death [Internet]. 2020 [cited 2021 Feb 28]. Available from:

World Health Organization (WHO). Global Health Estimates 2019: DALYs by cause and region, 2019 and 2000 [Internet]. 2020 [cited 2021 Feb 28]. Available from:

Choi SJ, Oh MY, Kim NR, Jung YJ, Ro YS, Shin S Do. Comparison of trauma care systems in Asian countries: A systematic literature review. EMA - Emerg Med Australas. 2017;29(6):697–711.

WHO. INJURIES VIOLENCE THE FACTS The magnitude and causes of injuries. Geneva World Heal Organ [Internet]. 2014;20. Available from:

Kim YJ. Relationship of trauma centre characteristics and patient outcomes: A systematic review. J Clin Nurs. 2014;23(3–4):301–14.

Haedar A, Dradjat RS. The quality of trauma care in emergency department of Saiful Anwar General Hospital, Malang, Indonesia. Biotika. 2018;24(5):20–6.

Subdirektorat Statistik Transportasi. STATISTIK TRANSPORTASI DARAT 2019. Subdirektorat Statistik Transportasi, editor. BPS RI; 2019.

Khairani AF, Azka AN, Faried A, Amelia I, Ardisasmita MN, Tanzilah S, et al. Characteristic of Motor Vehicle Accident Patients Presenting to a National Referral Hospital in West Java, Indonesia. Southeast Asian J Trop Med Public Health. 2018;49(5):887–93.

Muhtar. Analisis biaya kecelakaan lalulintas di kota makassar. J Transp. 2007;7(2):161–8.

Abhilash KP, Sivanandan A. Early management of trauma: The golden hour. Curr Med Issues. 2020;18(1):36.

Rinawan FR, Susanti AI, Amelia I, Ardisasmita MN, Dewi RK, Ferdian D, Purnama WG, Purbasari A. Understanding mobile application development and implementation to monitor Posyandu data in Indonesia: a 3-years hybrid action research to build “a bridge” from the community to national use. Under review by BMC Public Health, preprint: