Weifeng Shen1, Libing Jiang2, Mao Zhang2, Yuefeng Ma2, Guanyu Jiang2, Xiaojun He3. 1. Department of Emergency Medicine, Second Affiliated Hospital, School of Medicine & Institute of Emergency Medicine, Zhejiang University, Hangzhou, Zhejiang 310009, China; Chinese Training Center for Advanced Relief Projects, Harvard Medical International Trauma and Disaster Institute, USA. 2. Department of Emergency Medicine, Second Affiliated Hospital, School of Medicine & Institute of Emergency Medicine, Zhejiang University, Hangzhou, Zhejiang 310009, China. 3. Department of Emergency Medicine, Second Affiliated Hospital, School of Medicine & Institute of Emergency Medicine, Zhejiang University, Hangzhou, Zhejiang 310009, China; Department of Chinese Journal of Emergency Medicine, Hangzhou, Zhejiang 310009, China. Email address: hexiaojun_hz@163.com.
Abstract
OBJECTIVE: To review the research methods of mass casualty incident (MCI) systematically and introduce the concept and characteristics of complexity science and artificial system, computational experiments and parallel execution (ACP) method. DATA SOURCES: We searched PubMed, Web of Knowledge, China Wanfang and China Biology Medicine (CBM) databases for relevant studies. Searches were performed without year or language restrictions and used the combinations of the following key words: "mass casualty incident", "MCI", "research method", "complexity science", "ACP", "approach", "science", "model", "system" and "response". STUDY SELECTION: Articles were searched using the above keywords and only those involving the research methods of mass casualty incident (MCI) were enrolled. RESULTS: Research methods of MCI have increased markedly over the past few decades. For now, dominating research methods of MCI are theory-based approach, empirical approach, evidence-based science, mathematical modeling and computer simulation, simulation experiment, experimental methods, scenario approach and complexity science. CONCLUSIONS: This article provides an overview of the development of research methodology for MCI. The progresses of routine research approaches and complexity science are briefly presented in this paper. Furthermore, the authors conclude that the reductionism underlying the exact science is not suitable for MCI complex systems. And the only feasible alternative is complexity science. Finally, this summary is followed by a review that ACP method combining artificial systems, computational experiments and parallel execution provides a new idea to address researches for complex MCI.
OBJECTIVE: To review the research methods of mass casualty incident (MCI) systematically and introduce the concept and characteristics of complexity science and artificial system, computational experiments and parallel execution (ACP) method. DATA SOURCES: We searched PubMed, Web of Knowledge, China Wanfang and China Biology Medicine (CBM) databases for relevant studies. Searches were performed without year or language restrictions and used the combinations of the following key words: "mass casualty incident", "MCI", "research method", "complexity science", "ACP", "approach", "science", "model", "system" and "response". STUDY SELECTION: Articles were searched using the above keywords and only those involving the research methods of mass casualty incident (MCI) were enrolled. RESULTS: Research methods of MCI have increased markedly over the past few decades. For now, dominating research methods of MCI are theory-based approach, empirical approach, evidence-based science, mathematical modeling and computer simulation, simulation experiment, experimental methods, scenario approach and complexity science. CONCLUSIONS: This article provides an overview of the development of research methodology for MCI. The progresses of routine research approaches and complexity science are briefly presented in this paper. Furthermore, the authors conclude that the reductionism underlying the exact science is not suitable for MCI complex systems. And the only feasible alternative is complexity science. Finally, this summary is followed by a review that ACP method combining artificial systems, computational experiments and parallel execution provides a new idea to address researches for complex MCI.