Developing a Just-in-Time Refresher Trainer for Advanced Life Support in Austere Regions

Early recognition of impending decompensation and appropriate intervention is critical to patient survival in many situations; yet, military personnel receive limited training about the early signs of decompensation through established training courses. Descriptions of respiratory distress, shock, and poor perfusion may be offered in training, but with little opportunity to practice recognizing these signs in a range of patients, performance is likely to suffer in real-world contexts. Furthermore, skills learned in Advanced Cardiac Life Support, and Pediatric Advanced Life Support are likely to degrade through lack of use as the majority of patients medics encounter are adult military personnel in good physical condition. Unveil will team with the University of Florida to fill this training gap. We will develop a tablet-based trainer to support combat medics deployed in austere environments with a focus on recognizing signs of decompensation in a range of patients, including children and civilian adults. The proposed trainer will offer just-in-time refresher training and assess learner readiness. Objectives for this Phase I effort are: 1) Create a prototype simulation-based medical emergency recognition and response refresher tool; 2) Develop a proof of concept performance assessment capability; and 3) Evaluate the prototype’s operation in the target environment. For Objective 1, we will design and develop the Trainer for Advanced Life Support in Austere Regions (TALSAR). TALSAR will employ brief training scenarios using high-fidelity virtual patients that learners will interact with using a touch-based interface. The project team will interview expert clinicians to identify critical cues of impending decompensation in a variety of patient populations and conditions. These critical cues will inform the design of one pediatric and one adult scenario. For Objective 2, we will develop a method of assessing learners’ readiness to use these skills in a deployed setting. This assessment strategy will go beyond traditional knowledge tests, to evaluate how well learners are able to apply abstract knowledge in the context of challenging patient scenarios. TALSAR will evaluate learners’ diagnostic assessment skills as they assess a virtual patient’s condition by tracking which critical cues learners identify within the scenario and comparing learners’ performance to an expert model. This method will help learners develop key recognition skills that will enhance their performance in real-world contexts. TALSAR will also evaluate the quality of the learners’ intervention skills by tracking whether correct interventions were applied appropriately. These performance data will complement traditional measures to provide a more nuanced assessment of learners’ readiness. For Objective 3, we will ensure the trainer is able to operate in austere environments without access to communications infrastructure.