Priority Assignment for Emergency Medical Service Provision in Disaster by Considering Resource Limitation

재난 발생 시 이송 및 병원 자원 제약을 고려한 이송환자 우선순위 결정 연구

  • Shin, Kyohong (Department of Industrial & Systems Engineering, KAIST) ;
  • Lee, Taesik (Department of Industrial & Systems Engineering, KAIST)
  • 신교홍 (한국과학기술원(KAIST) 산업 및 시스템 공학과) ;
  • 이태식 (한국과학기술원(KAIST) 산업 및 시스템 공학과)
  • Received : 2014.02.14
  • Accepted : 2014.03.31
  • Published : 2014.04.30


EMS resources management is one of the determinants to maximize the number of survivors effective first response in the aftermath of mass casualties. This paper concerns a problem of patient prioritization for EMS provision by constructing a Markov Decision Processes( MDP) model. While prior research tends to focus solely on transport resources (i.e., ambulance), we show that factors on the involved hospitals (i.e., capacity and capability) in the disaster response affect optimal response policies. Experiments on hypothetical scenarios are conducted to compare the proposed model with the existing algorithms from the literature, including the standard triage practice known as START(Simple Triage And Rapid Treatment). We show that considering hospital factors can save more patients than the other algorithms in most scenarios. The results of the study suggest that capacity and capability of the hospitals participating in the response should be factored into decision makings in the EMS response to maximize the life savings.

재난으로 인해 다수 환자가 동시에 발생하는 경우, 효과적인 가용자원 운용을 위해서 고려해야할 요인으로 응급의료서비스 제공의 우선순위 결정과 해당 환자를 이송할 병원 선정이 있다. 이에 본 연구에서는 두 가지 요인을 동시에 결정하는 연구를 진행하였다. 각 병원의 서비스율과 중증 환자에 대한 치료 역량이 고려된 Markov Decision Processes 모델을 설계하여 기대 생존 환자 수를 최대화 하는 최적 결정을 구했다. 모델로부터 얻어진 최적 결정은, 재난 현장 주변 병원의 진료 자원 여유 상태에 따라 우선적으로 이송해야하는 환자 집단이 달라짐을 보여준다. 계산된 최적 결정의 성능을 평가하기 위해 최근 관련 연구 문헌의 알고리즘 및 실제 재난 현장에서 일반적으로 사용되고 있는 START(Simple Triage And Rapid Treatment)방법과의 비교를 수행하였고, 타 알고리즘에 비해 대부분의 시나리오에서 더 많은 환자를 살릴 수 있다는 결과를 얻었다. 이러한 결과에 바탕하여, 발전된 재난사고 대처가 이루어지도록 재난 발생 시사고 현장 주변의 응급실 정보를 신속하게 공유하여 이송환자 우선순위를 결정하는 것을 제안한다.



Grant : 국지적 재난시 피해자 대응, 이송, 처치 시뮬레이션 개발

Supported by : 소방방재청


  1. Cormen, T.H., Leiserson, C.E., Rivest, R.L., and Stein C. (2001) Introduction to Algorithms, 2nd ed, MIT Press, Cambridge, MA.
  2. Frykberg, E.R. (2005) Triage: Principles and practice, Scandinavian Journal of Surgery, Vol. 94, No. 4, pp. 272-278.
  3. Garner, A., Lee, A., Harrison, K., and Schultz, C.H. (2001) Comparative analysis of multiple-casualty incident triage algorithms, Annals of Emergency Medicine, Vol 38, No. 5, pp. 541-548.
  4. Jacobson, E.U., Argon, N.T., and Ziya, S. (2012) Priority Assignment in Emergency Response, Operation Research, Vol. 60, No. 4, pp. 813-832.
  5. Jenkins, J.L., McCarthy, M.L., Sauer, L.M., Green, G.B., Stuart, S., Thomas, T.L., and Hsu, E.B. (2008) Mass-casualty triage:Time for an evidence-based approach, Prehospital and Disaster Medicine, Vol. 23, No. 1, pp. 3-8.
  6. Kang, S., Yun, S., Jung, H., Kim, J., Han, S., Kim, J., and Paik, J. (2013) An Evauation of the Disaster Medical System after an Accident which Occurred after a Bus fell off the Incheon Bridge, Journal of The Korean Society of Emergency Medicine, Vol. 24, No. 1, pp. 1-6.
  7. Kashiyama, A., Uchiyama, A., and Higashino, T. (2013) Depth limited treatment planning and scheduling for electronic triage system in MCI, Wireless Mobile Communication and Healthcare, Vol. 61, pp. 224-233.
  8. Li, D. and Glazebrook, K.D. (2010) An approximate dynamic programing approach to the development of heuristics for the scheduling of impatient jobs in a clearing system, Navel Research Logistics, Vol. 57, No. 3, pp. 225-236.
  9. Mills, A.F., Argon, N. T., and Ziya, S. (2013) Resource-Based Patient Prioritization in Mass-Casualty Incidents, Manufacturing & Service Operations Management, Vol. 15, No. 3, pp. 1-17.
  10. Ministry of Health & Welfare (2009) 2010-2012 Plan for Advancement of Emergency Medical Service.
  11. Mizumoto, T., Sun, W., Yasumoto, K., and Ito, M. (2011) Transportation scheduling method for patients in mci using electronic triage tag, eTELEMED 2011, The Third International Conference on eHealth, Telemedicine, and Social Medicine, pp. 156-163.
  12. National Emergency Medical Center URLs, (, Access on August 27 2013.
  13. Puterman, M.L. (1994) Markov Decision Processes: Discrete Stochastic Dynamic Programming, Wiley, New York, United States of America.
  14. Ross, S.M. (1996) Stochastic processes Second ed, Wiley series in probability and mathematical statistics.
  15. Sacco, W.J., Navin, D.M., Fiedler, K.E., Waddell II, R.K., Long, W.B., and Buckman Jr, R.F. (2005) Precise Formulation and Evidence-based Application of Resource-constrained Triage, Academic Emergency Medicine, Vol. 12, No. 8, pp. 759-770.
  16. Sung, I. and Lee, T. (2012) Modeling Requirements for An Emergency Medical Service System Design Evaluator, In Proceedings of the 2012 Winter Simulation Conference.