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Automation to Improve Efficiency of Field Expedient Injury Prediction Screening

Teyhen, Deydre S.1,2; Shaffer, Scott W.1; Umlauf, Jon A.1; Akerman, Raymond J.1; Canada, John B.1; Butler, Robert J.3; Goffar, Stephen L.1; Walker, Michael J.1; Kiesel, Kyle B.4; Plisky, Phillip J.4

Journal of Strength & Conditioning Research:
doi: 10.1519/JSC.0b013e31825d80e6
Original Research
Abstract

Abstract: Teyhen, DS, Shaffer, SW, Umlauf, JA, Akerman, RJ, Canada, JB, Butler, RJ, Goffar, SL, Walker, MJ, Kiesel, KB, Plisky, PJ. Automation to improve efficiency of field expedient injury prediction screening. J Strength Cond Res 26(7): S61–S72, 2012—Musculoskeletal injuries are a primary source of disability in the U.S. Military. Physical training and sports-related activities account for up to 90% of all injuries, and 80% of these injuries are considered overuse in nature. As a result, there is a need to develop an evidence-based musculoskeletal screen that can assist with injury prevention. The purpose of this study was to assess the capability of an automated system to improve the efficiency of field expedient tests that may help predict injury risk and provide corrective strategies for deficits identified. The field expedient tests include survey questions and measures of movement quality, balance, trunk stability, power, mobility, and foot structure and mobility. Data entry for these tests was automated using handheld computers, barcode scanning, and netbook computers. An automated algorithm for injury risk stratification and mitigation techniques was run on a server computer. Without automation support, subjects were assessed in 84.5 ± 9.1 minutes per subject compared with 66.8 ± 6.1 minutes per subject with automation and 47.1 ± 5.2 minutes per subject with automation and process improvement measures (p < 0.001). The average time to manually enter the data was 22.2 ± 7.4 minutes per subject. An additional 11.5 ± 2.5 minutes per subject was required to manually assign an intervention strategy. Automation of this injury prevention screening protocol using handheld devices and netbook computers allowed for real-time data entry and enhanced the efficiency of injury screening, risk stratification, and prescription of a risk mitigation strategy.

Author Information

1Doctoral Program in Physical Therapy, U.S. Army-Baylor University, Fort Sam Houston, Texas

2U.S. Army Public Health Command Region-South, Fort Sam Houston, Texas

3Division of Physical Therapy, Duke University, Durham, North Carolina

4Doctoral Program in Physical Therapy, University of Evansville, Evansville, Indiana

Address correspondence to Deydre S. Teyhen, deydre.teyhen@amedd.army.mil.

The view(s) expressed in this article do not reflect the official policy or position of Brooke Army Medical Center, the U.S. Army Public Health Command, the U.S. Army Medical Department, the U.S. Army Office of the Surgeon General, the Department of the Army, Department of Defense, or the U.S. Government.

The results of the present study do not constitute endorsement of the products by the authors or the NSCA.

Drs. Kiesel and Plisky own equity in Move2Perform LLC and have developed the Move2Perofrm injury prediction software which is used in this study. Dr. Plisky developed the Y Balance Testtm which is also used in this study.

Copyright © 2012 by the National Strength & Conditioning Association.