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

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.

The Ability of Military Critical Care Air Transport Members to Visually Estimate Percent Systolic Pressure Variation.

INTRODUCTION: Inappropriate fluid management during patient transport may lead to casualty morbidity. Percent systolic pressure variation (%SPV) is one of several technologies that perform a dynamic assessment of fluid responsiveness (FT-DYN). Trained anesthesia providers can visually estimate and use %SPV to limit the incidence of erroneous volume management decisions to 1-4%. However, the accuracy of visually estimated %SPV by other specialties is unknown. The aim of this article is to determine the accuracy of estimated %SPV and the incidence of erroneous volume management decisions for Critical Care Air Transport (CCAT) team members before and after training to visually estimate and utilize %SPV. MATERIAL AND METHODS: In one sitting, CCAT team providers received didactics defining %SPV and indicators of fluid responsiveness and treatment with %SPV ≤7 and ≥14.5 defining a fluid nonresponsive and responsive patient, respectively; they were then shown ten 45-second training arterial waveforms on a simulated Propaq M portable monitor's screen. Study subjects were asked to visually estimate %SPV for each arterial waveform and queried whether they would treat with a fluid bolus. After each training simulation, they were told the true %SPV. Seven days post-training, the subjects were shown a different set of ten 45-second testing simulations and asked to estimate %SPV and choose to treat, or not. Nonparametric limits of agreement for differences between true and estimated %SPV were analyzed using Bland-Altman graphs. In addition, three errors were defined: (1) %SPV visual estimate errors that would label a volume responsive patient as nonresponsive, or vice versa; (2) incorrect treatment decisions based on estimated %SPV (algorithm application errors); and (3) incorrect treatment decisions based on true %SPV (clinically significant treatment errors). For the training and testing simulations, these error rates were compared between, and within, provider groups. RESULTS: Sixty-one physicians (MDs), 64 registered nurses (RNs), and 53 respiratory technicians (RTs) participated in the study. For testing simulations, the incidence and 95% CI for %SPV estimate errors with sufficient magnitude to result in a treatment error were 1.4% (0.5%, 3.2%), 1.6% (0.6%, 3.4%), and 4.1% (2.2%, 6.9%) for MDs, RNs, and RTs, respectively. However, clinically significant treatment errors were statistically more common for all provider types, occurring at a rate of 7%, 10%, and 23% (all P < .05). Finally, students did not show clinically relevant reductions in their errors between training and testing simulations. CONCLUSIONS: Although most practitioners correctly visually estimated %SPV and all students completed the training in interpreting and applying %SPV, all groups persisted in making clinically significant treatment errors with moderate to high frequency. This suggests that the treatment errors were more often driven by misapplying FT-DYN algorithms rather than by inaccurate visual estimation of %SPV. Furthermore, these errors were not responsive to training, suggesting that a decision-making cognitive aid may improve CCAT teams' ability to apply FT-DYN technologies.

Effect of prior cardiopulmonary resuscitation knowledge on compression performance by hospital providers.

INTRODUCTION: The purpose of this study was to determine cardiopulmonary resuscitation (CPR) knowledge of hospital providers and whether knowledge affects performance of effective compressions during a simulated cardiac arrest. METHODS: This cross-sectional study evaluated the CPR knowledge and performance of medical students and ED personnel with current CPR certification. We collected data regarding compression rate, hand placement, depth, and recoil via a questionnaire to determine knowledge, and then we assessed performance using 60 seconds of compressions on a simulation mannequin. RESULTS: Data from 200 enrollments were analyzed by evaluators blinded to subject knowledge. Regarding knowledge, 94% of participants correctly identified parameters for rate, 58% for hand placement, 74% for depth, and 94% for recoil. Participants identifying an effective rate of ≥100 performed compressions at a significantly higher rate than participants identifying <100 (µ=117 vs. 94, p<0.001). Participants identifying correct hand placement performed significantly more compressions adherent to guidelines than those identifying incorrect placement (µ=86% vs. 72%, p<0.01). No significant differences were found in depth or recoil performance based on knowledge of guidelines. CONCLUSION: Knowledge of guidelines was variable; however, CPR knowledge significantly impacted certain aspects of performance, namely rate and hand placement, whereas depth and recoil were not affected. Depth of compressions was poor regardless of prior knowledge, and knowledge did not correlate with recoil performance. Overall performance was suboptimal and additional training may be needed to ensure consistent, effective performance and therefore better outcomes after cardiopulmonary arrest.