Inter-patient variability is a major contributing factor to adverse outcomes in conscious sedation procedures. For example, two patients of similar height, weight, and age may react very differently to the same sedative, resulting in over sedation or under sedation. In many of these cases, patients who are assessed to be at minimal risk are actually at high risk. Then, problems, such as unexpected respiratory depression, cause an adverse outcome, such as neurologic damage or death. Current training programs mainly train students through lectures and real world experience, which logistically cannot bring students to competency in an acceptable amount of time. To address this problem, this proposal aims to develop an immersive mixed reality (MR) based training simulator for educating students about variability in conscious sedation procedures. Approach: Specifically, the proposed simulation will augment a mannequin patient simulator with a simulation model of variability, an immersive virtual reality patient, and conceptual visualizations of the patient's internal processes. This mixed reality patient will not only offer a wider variety of hands-on experience through the incorporation of patient interviews (e.g., history taking), but it will additionally simulate a variety of external characteristics, such as race, weight, height, and age, and offer conceptual visualizations of highly variable internal characteristics, such as drug sensitivity. Based on these reconfigurable characteristics, the proposed MR-based simulator will give students hands-on experience with a wide variety of simulated patients in a short amount of time. Ultimately, the simulator aims to afford students a deeper understanding of how their procedural decisions can have variable effects on patients.
Specific Aims : 1) develop a simulation model of patient variability in conscious sedation, 2) develop model-driven mixed reality patients and debriefing for a conscious sedation scenario, 3) pilot-study the learning effectiveness of the system and establish face validity. The goal of the proposed simulator is to provide a variety of hands-on experiences and feedback that will accelerate learning, enhance decision making skills, and enable students to more effectively manage variability in conscious sedation.

Public Health Relevance

This research aims to develop an immersive training simulation that can effectively and efficiently educate students on how to manage patient variability during conscious sedation. If students and clinicians can more effectively manage variability, they will more effectively be able to anticipate, detect and prevent potential adverse events. Thus, the ultimate goal of this research is to provide a much needed educational tool that could potentially improve medical skills education and training, help future clinicians understand variability, reduce adverse outcomes, and ultimately improve patient safety.

National Institute of Health (NIH)
National Library of Medicine (NLM)
Exploratory/Developmental Grants (R21)
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Biomedical Library and Informatics Review Committee (BLR)
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Sim, Hua-Chuan
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University of Texas Health Science Center San Antonio
Biostatistics & Other Math Sci
Schools of Arts and Sciences
San Antonio
United States
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