Article ID Journal Published Year Pages File Type
4193615 American Journal of Preventive Medicine 2010 9 Pages PDF
Abstract

BackgroundThe U.S. military leadership has recently increased its efforts to reduce the number of lost-workday injuries for both the active duty and civilian employee components of the total force. The detailed causes and circumstances of those nonfatal injuries—information needed for injury prevention—has largely been unexplored. The purpose of this project was to determine the utility of Air Force safety data for nonfatal injury prevention.MethodsIn 2004, events associated with injury-producing mishaps reported through the U.S. Air Force (USAF) Ground Safety Automated System from 1993–2002 (n = 32,812 injuries) were reconstructed. Essential data elements necessary to reconstruct event causes and circumstances were identified in both coded data and in free-text mishap narratives. Activities and mechanisms were coded in a format similar to that of the ICD-10. A taxonomy was then developed to identify hazard scenarios associated with injury-producing activities or mechanisms.ResultsCoded data provided only four data elements (activity, injury event/exposure, nature of injury/body part, and outcome) that were sufficiently descriptive for prevention purposes. Therefore, narrative information was coded and analyzed to obtain additional information. The assembled data enabled identification and description of hazard scenarios associated with the most common injury-producing activities and mechanisms.ConclusionsSafety reports from the USAF provide detailed mishap descriptions for lost-workday injuries that could support in-depth analysis and more effective preventive efforts. However, some of the most valuable information is found in the pre-text narratives that require coding and classification, such as was conducted for this report in order to be optimally useful for injury epidemiology and prevention.

Related Topics
Health Sciences Medicine and Dentistry Public Health and Health Policy
Authors
, , , ,