Impact of Rank, Provider Specialty, and Unit Sustainment Training Frequency on Military Critical Care Air Transport Team Readiness

Nicole Leib; Mark Cheney; Joshua N Burkhardt; Eric Nelson; Shannon Diffley; Ann Salvator; Tyler Davis; F Eric Robinson; Daniel J Brown; Lane Frasier; Valerie Sams; Richard J Strilka

doi:10.1093/milmed/usae113

Impact of Rank, Provider Specialty, and Unit Sustainment Training Frequency on Military Critical Care Air Transport Team Readiness

Mil Med. 2024 Apr 30:usae113. doi: 10.1093/milmed/usae113. Online ahead of print.

Authors

Nicole Leib¹, Mark Cheney^{1

2}, Joshua N Burkhardt^{1

3}, Eric Nelson¹, Shannon Diffley¹, Ann Salvator⁴, Tyler Davis⁵, F Eric Robinson⁶, Daniel J Brown^{3

7}, Lane Frasier⁸, Valerie Sams^{1

8}, Richard J Strilka^{1

8}

Affiliations

¹ University of Cincinnati Center for Sustainment of Trauma and Readiness Skills, Cincinnati, OH 45219, USA.
² Department of Anesthesiology, University of Cincinnati, Cincinnati, OH 45219, USA.
³ Department of Emergency Medicine, University of Cincinnati, Cincinnati, OH 45219, USA.
⁴ Air Force Research Laboratory Airman Biosciences Division, Wright-Patterson Air Force Base, Dayton, OH 45433, USA.
⁵ United States Air Force En route Care Research Center/59th MDW/Science and Technology, JBSA-Fort Sam Houston, TX 78234, USA.
⁶ Naval Medical Research Unit Dayton, Wright-Patterson AFB, USA.
⁷ Department of Emergency Medicine, Wright State University, Dayton, OH 45324, USA.
⁸ University of Cincinnati, Department of Surgery, Cincinnati, OH 45219, USA.

PMID: 38687580
DOI: 10.1093/milmed/usae113

Abstract

Background: The Critical Care Air Transport (CCAT) Advanced Course utilizes fully immersive high-fidelity simulations to assess personnel readiness for deployment. This study aims to determine whether simple well-defined demographic identifiers can be used to predict CCAT students' performance at CCAT Advanced.

Materials and methods: CCAT Advanced student survey data and course status (pass/fail) between March 2006 and April 2020 were analyzed. The data included students' Air Force Specialty Code (AFSC), military status (active duty and reserve/guard), CCAT deployment experience (yes/no), prior CCAT Advanced training (yes/no), medical specialty, rank, and unit sustainment training frequency (never, frequency less often than monthly, and frequency at least monthly). Following descriptive analysis and comparative tests, multivariable regression was used to identify the predictors of passing the CCAT Advanced course for each provider type.

Results: A total of 2,576 student surveys were analyzed: 694 (27%) physicians (MDs), 1,051 (40%) registered nurses (RNs), and 842 (33%) respiratory therapists (RTs). The overall passing rates were 92.2%, 90.3%, and 85.4% for the MDs, RNs, and RTs, respectively. The students were composed of 579 (22.5%) reserve/guard personnel, 636 (24.7%) with CCAT deployment experience, and 616 (23.9%) with prior CCAT Advanced training. Regression analysis identified groups with lower odds of passing; these included (1) RNs who promoted from Captain to Major (post-hoc analysis, P = .03), (2) RTs with rank Senior Airman, as compared to Master Sergeants (post-hoc analysis, P = .04), and (3) MDs with a nontraditional AFSC (P = .0004). Predictors of passing included MDs and RNs with CCAT deployment experience, odds ratio 2.97 (P = .02) and 2.65 (P = .002), respectively; and RTs who engaged in unit CCAT sustainment at least monthly (P = .02). The identifiers prior CCAT Advanced training or reserve/guard military status did not confer a passing advantage.

Conclusion: Our main result is that simple readily available metrics available to unit commanders can identify those members at risk for poor performance at CCAT Advanced readiness training; these include RNs with rank Major or above, RTs with rank Senior Airman, and RTs who engage in unit sustainment training less often than monthly. Finally, MD specialties which are nontraditional for CCAT have significantly lower CCAT Advanced passing rates, reserve/guard students did not outperform active duty students, there was no difference in the performance between different RN specialties, and for MD and RN students' previous deployment experience was a strong predictor of passing.

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