The FY16 JPC-1/MSIS Medical Decision Aids - Predictive Markers (SimMarkers) is seeking research that improves healthcare professionalsâ₏™ cognitive and performance skill acquisition or minimizes his/her skill decay. This research is seeking objective markers that could be inserted into a predictive model (one that has not been currently developed) to accurately and appropriately assess a healthcare professionalâ₏™s cognitive and performance status. These cognitive and performance-type markers must be evidence-based and need to align with the respective credentialing or certifying healthcare organization. These cognitive and performance-type markers must also align with regional, local, and organization-specific recommendations, guidelines, and standards, especially if they exceed the credentialing or certifying healthcare organization-specific recommendations, guidelines, and standards. It is anticipated that this research will minimize the use of data/information using hospital EHR and will not concentrate on psychomotor skills; current work sponsored by the DHP is already underway in those areas. It is anticipated that this research will uncover information that clearly delineates the cognitive training differences between training to competency versus training to proficiency, as defined by Kirkpatrick. It is anticipated that from this research there will be clear metrics/evaluation criteria that have been deconstructed that will discriminate between competency and proficiency. It is anticipated that from this research common environmental and/or behavioral factors will be able to be deconstructed to form metrics/evaluation criteria that could be used as markers that will assist in measuring cognitive skill acquisition and minimization of skill decay. This announcement is seeking alternate predictive markers, aside from information from an EHR or from use of currently available simulation systems that assess psychomotor skills. This announcement is seeking predictive markers that could be deconstructed into objective, or at least reliable, observational metrics and/or evaluation criteria that could eventually be inserted into computational models to select, train, sustain, and remediate healthcare professionals, initially at the entry-level healthcare team member. Eventually the long-term goal is that there will be computational models that could possibly be applicable to all healthcare providers, at any experience level. These markers should be task/procedure/skill agnostic, if at all possible, but need to provide enough detail and specifics to demonstrate, through a domain-specific proof of concept, that the markers indeed show some level of predictability. A pilot test in an entry-level medical domain-specific area is needed as an outcome of this research, in addition to the research information and evidence-based methodologies, to demonstrate feasibility of the skill acquisition, maintenance, or decay/degradation model. Linkage of data within the computational algorithms must also be demonstrated as a proof of concept.