Predicting Exploration Crew Medical Officer Training Needs Applying Evidence Based Predictive Analytics to Space Medicine Training

Abstract Predictive analytics may be a useful adjunct to identify training needs for exploration class medical officers onboard deep space vehicles. This study used a preliminary version of NASA’s newest medical predictive analytics tool, the Medical Extensible Database Probabilistic Risk Assessment Tool (MEDPRAT), to test the application of predictive analytics to Exploration Crew Medical Officer (exploration CMO) curriculum design for 5 distinct mission profiles. Curriculum elements were identified using a leave-one-out analysis and a threshold of 5% risk increase over the fully treated baseline. This proof-of-concept study demonstrated that predictive analytics can rapidly generate generic and mission profile specific exploration CMO curricula using an evidence-based process driven by optimizing mission risk reduction. This technique may serve as part of a human-machine team approach to medical curriculum planning for future space missions. It has significant potential to improve astronaut health and save time and effort for both planners and trainees.