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Development of a Prediction Model for Identification of High-Cost Sports Injury Cases

Proceedings article published in 2013 by Kelly M. Tucker Ms, Melody A. Mullis Ms, Gary B. Wilkerson, Scott L. Bruce
This paper is available in a repository.
This paper is available in a repository.

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Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

and university athletic programs spend thousands of dollars on student-athletes' medical costs each year • ACL injuries among 15-24 year-old athletes cost > $1 billion annually in the US; approximately $17,000 per injury 1,2 • Athletes who possess elevated injury risk prior to sport participation probably impose greater injury treatment costs • NCAA BCS football programs incurred $550,000 of medical expenses associated with 2008 bowl games 3 • Deficiency in the performance capabilities of the core musculature appear to increase risk for sprains or strains 4 • Other injury risk factors include high exposure to game conditions and the existence of low back dysfunction 5 • Strongest predictors of high-cost status among various sports may or may not differ from predictors of injury occurrence • The purpose of this study was to develop a prediction model for identification of athletes who are likely to incur high treatment costs on the basis of injury history, performance tests, joint function ratings, and other relevant characteristics BACKGROUND AND PURPOSE RESULTS