7 Mass casualty incidents: a review of triage severity planning assumptions. Issue 12 (23rd November 2017) - Hunt, Paul
Abstract : Background: Recent events involving a significant number of casualties have emphasised the importance of appropriate preparation for receiving hospitals, especially Emergency Departments, during the initial response phase of a major incident. Development of a mass casualty resilience and response framework in the Northern Trauma Network included a review of existing planning assumptions in order to ensure effective resource allocation, both in local receiving hospitals and system-wide. Existing planning assumptions regarding categorisation by triage level are generally stated as a ratio for P1:P2:P3 of 25%:25%:50% of the total number of injured survivors. This may significantly over-, or underestimate, the number in each level of severity in the case of a large-scale incident. Methods: A pilot literature review was conducted of the available evidence from historical incidents in order to gather data regarding the confirmed number of overall casualties, 'critical' cases, admitted cases, and non-urgent or discharged cases. This data was collated and grouped by mechanism in order to calculate an appropriate severity ratio for each incident type. Results: 12 articles regarding mass casualty incidents from the last two decades were identified covering three main incident types: (1) Mass transportation crash, (2) Building fire, and (3) Bomb and related terrorist attacks and involving a total of 3615 injured casualties. The overall mortality rate was calculated as 12.3%. Table 1 summarises the available patient casualty data from each of the specific incidents reported and calculated proportions of critical ('P1'), admitted ('P2'), and non-urgent or ambulatory cases ('P3'). Conclusions: Despite the heterogeneity of data and range of incident type there is sufficient evidence to suggest that current planning assumptions are incorrect and a more refined model is required. An important finding is the variation in proportion of critical cases depending upon the mechanism. For example, a greater than expected proportion results from incidents involving a building fire whereas the existing model may over-estimate critical caseload in more 'conventional' incidents such as a transportation accident or even in terrorism-related incidents. A new model suggesting the proportions of casualties expected by severity categorisation and incident type is shown in table 2 . A more detailed investigation is planned to further refine and develop this model.