Literature DB >> 20117593

A process to identify military injury prevention priorities based on injury type and limited duty days.

Bruce A Ruscio1, Bruce H Jones, Steven H Bullock, Bruce R Burnham, Michelle Canham-Chervak, Christopher P Rennix, Timothy S Wells, Jack W Smith.   

Abstract

BACKGROUND: Injuries, one of the leading public health problems in an otherwise healthy military population, affect operational readiness, increase healthcare costs, and result in disabilities and fatalities. This paper describes a systematic, data-driven, injury prevention-decision making process to rank potential injury prevention targets.
METHODS: Medical surveillance and safety report data on injuries for 2004 were reviewed. Nonfatal injury diagnoses (ICD-9-CM codes) obtained from the Defense Medical Surveillance System were ranked according to incident visit frequency and estimated limited duty days. Data on the top five injury types resulting in the greatest estimated limited duty days were matched with hospitalization and Service Safety Centers' accident investigation data to identify leading causes. Experts scored and ranked the causes using predetermined criteria that considered the importance of the problem, preventability, feasibility, timeliness of intervention establishment/results, and ability to evaluate. Department of Defense (DoD) and Service-specific injury prevention priorities were identified.
RESULTS: Unintentional injuries lead all other medical conditions for number of medical encounters, individuals affected, and hospital bed days. The top ten injuries resulted in an estimated 25 million days of limited duty. Injury-related musculoskeletal conditions were a leading contributor to days of limited duty. Sports and physical training were the leading cause, followed by falls.
CONCLUSIONS: A systematic approach to injury prevention-decision making supports the DoD's goal of ensuring a healthy, fit force. The methodology described here advances this capability. Immediate follow-up efforts should employ both medical and safety data sets to identify and monitor injury prevention priorities. Published by Elsevier Inc.

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Year:  2010        PMID: 20117593     DOI: 10.1016/j.amepre.2009.10.004

Source DB:  PubMed          Journal:  Am J Prev Med        ISSN: 0749-3797            Impact factor:   5.043


  18 in total

1.  Examination of the Effectiveness of Predictors for Musculoskeletal Injuries in Female Soldiers.

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2.  Association of Injury History and Incident Injury in Cadet Basic Military Training.

Authors:  Kristen L Kucera; Stephen W Marshall; Susanne H Wolf; Darin A Padua; Kenneth L Cameron; Anthony I Beutler
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3.  Normative Data for the NeuroCom Sensory Organization Test in US Military Special Operations Forces.

Authors:  Erin R Pletcher; Valerie J Williams; John P Abt; Paul M Morgan; Jeffrey J Parr; Meleesa F Wohleber; Mita Lovalekar; Timothy C Sell
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4.  Prediction of Injuries and Injury Types in Army Basic Training, Infantry, Armor, and Cavalry Trainees Using a Common Fitness Screen.

Authors:  JoEllen M Sefton; K R Lohse; J S McAdam
Journal:  J Athl Train       Date:  2016-11       Impact factor: 2.860

5.  Rationale for Embedded Musculoskeletal Care in Air Force Training and Operational Units.

Authors:  Nathaniel S Nye; Sarah J de la Motte
Journal:  J Athl Train       Date:  2016-09-29       Impact factor: 2.860

6.  The Interrelationship of Common Clinical Movement Screens: Establishing Population-Specific Norms in a Large Cohort of Military Applicants.

Authors:  Sarah J de la Motte; Timothy C Gribbin; Peter Lisman; Anthony I Beutler; Patricia Deuster
Journal:  J Athl Train       Date:  2016-11-10       Impact factor: 2.860

7.  What Risk Factors Are Associated With Musculoskeletal Injury in US Army Rangers? A Prospective Prognostic Study.

Authors:  Deydre S Teyhen; Scott W Shaffer; Robert J Butler; Stephen L Goffar; Kyle B Kiesel; Daniel I Rhon; Jared N Williamson; Phillip J Plisky
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8.  Identification of Risk Factors Prospectively Associated With Musculoskeletal Injury in a Warrior Athlete Population.

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9.  Sensitivity of a Subject-specific Ankle Sprain Simulation to Extrinsic Versus Intrinsic Biomechanical Factors.

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10.  [Epidemiological aspects of limb fractures related to military exercises in Togo].

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