Research Article
C Uptegraf and Catherine
Abstract
Occupational dispositions (profiles) are the top reason active duty service members are not medically ready to deploy or fulfill their job responsibilities. An audit across multiple U.S. Air Force (AF) medical treatment facilities revealed significant shortcomings in how medical providers assign profiles. We aimed to create a predictive model and a decision-support tool that estimates profile duration. Using retrospective profiles (n=1,546,805) from the Aeromedical Services Information Management System between 1 Feb 2007 and 31 Jan 2017, we built and validated a decision-support tool that estimates profile length. Multivariate quantile regressions (n=2,575) were performed across five quantiles and six levels of diagnostic specificity for every diagnostic code with 2,100 or more observations. The models universally estimated profile duration with very poor accuracy (pseudoR2 0.000 to 0.168); however, predictive ability was directly correlated with quantile level with minimal variation by diagnostic specificity. Age, O4 to O6+ ranks, very heavy job class, and co-morbid conditions were all significant in more than 25.0% of regressions down all levels of diagnostic specificity. Age, co-morbid conditions, E7-E9 ranks, O4 to O6+ ranks, and light job class all added days to profile duration while E1 to E4 ranks, heavy, and very heavy job class subtracted days. While this study failed to produce an accurate tool, several findings, the indirect correlation between profile duration and very heavy job class and the assignment of durations based on convenient calendar times, warrant further investigation. For now, providers may consult existing decision-support tools when building profiles for AF service members, heeding attention that they were built with nonrepresentative civilian populations.