Anatomy of Mine Rescue Teams' Casualty Incidents: A Basis for Medical Emergency Preparedness and Injury Prevention

Disaster Med Public Health Prep. 2019 Aug;13(4):695-699. doi: 10.1017/dmp.2018.140. Epub 2019 Mar 5.

Abstract

Objective: Mine rescue teams bear a high risk of injury. To improve medical emergency preparedness and injury prevention, this work analyzed the causes and severity of mine rescue teams' casualty incidents, the primary injuries, and the link between the causes and the occurrences of the casualty incidents.

Methods: A total of 81 cases from 1953 to 2013 were used to analyze the casualty incidents of mine rescue teams based on the frequency of accidents. A panel with 4 rescue experts was set up to ensure the accuracy of the analysis.

Results: The 81 casualty incidents occurred in 7 types of rescue work and were due to 6 causes. Organizational and personal factors were the leading cause, followed by rescue skill and equipment factors. Problems with decision-making and command have gradually become the primary inducement of casualty incidents in recent years, with an average death toll reaching up to 6 to 7 people. The main injuries causing death to team members were blast injury, burns, poisoning, suffocation, blunt trauma, and overwork injury. Some of the injured died because of medical emergency response failure.

Conclusion: The construction of emergency medical teams and the preparedness of disaster medicine need to be improved to reduce the mortality of the injured team members. Actions according to the causes of casualty incidents should be adopted for injury prevention. (Disaster Med Public Health Preparedness. 2019;13:695-699).

Keywords: casualty incident; injury prevention; medical emergency preparedness; mine rescue team; rescue.

MeSH terms

  • Accidents / statistics & numerical data
  • Civil Defense / standards*
  • Civil Defense / statistics & numerical data
  • Humans
  • Mining / statistics & numerical data*
  • Rescue Work / methods
  • Rescue Work / statistics & numerical data*
  • Risk Management / classification
  • Risk Management / statistics & numerical data*
  • Wounds and Injuries / prevention & control