Prolonged, High-Fidelity Simulation for Study of Patient Care in Resource-Limited Medical Contexts and for Technology Comparative Effectiveness Testing.

Jeremy C Pamplin, Sena R Veazey, Joanne De Howitt, Katy Cohen, Stacie Barczak, Mark Espinoza, Dave Luellen, Kevin Ross, Maria Serio-Melvin, Mary McCarthy, Christopher J Colombo
Author Information
  1. Jeremy C Pamplin: Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fredrick, MD.
  2. Sena R Veazey: U.S. Army Institute of Surgical Research, U.S. Army Medical Research and Development Command, San Antonio, TX.
  3. Joanne De Howitt: Department of Virtual Health, Madigan Army Medical Center, Tacoma, WA.
  4. Katy Cohen: Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fredrick, MD.
  5. Stacie Barczak: Department of Virtual Health, Madigan Army Medical Center, Tacoma, WA.
  6. Mark Espinoza: U.S. Army Institute of Surgical Research, U.S. Army Medical Research and Development Command, San Antonio, TX.
  7. Dave Luellen: U.S. Army Institute of Surgical Research, U.S. Army Medical Research and Development Command, San Antonio, TX.
  8. Kevin Ross: DocBox, Waltham, MA.
  9. Maria Serio-Melvin: U.S. Army Institute of Surgical Research, U.S. Army Medical Research and Development Command, San Antonio, TX.
  10. Mary McCarthy: Center for Nursing Science and Clinical Inquiry, Madigan Army Medical Center, Tacoma, WA.
  11. Christopher J Colombo: Department of Medicine, Uniformed Services University, Bethesda, MD.

Abstract

Most high-fidelity medical simulation is of limited duration, used for education and training, and rarely intended to study medical technology. U.S. caregivers working in prehospital, resource-limited settings may need to manage patients for extended periods (hours to days). This "prolonged casualty care" occurs during military, wilderness, humanitarian, disaster, and space medicine. We sought to develop a standardized simulation model that accurately reflects prolonged casualty care in order to study caregiver decision-making and performance, training requirements, and technology use in prolonged casualty care.
DESIGN: Model development.
SETTING: High-fidelity simulation laboratory.
SUBJECTS: None.
INTERVENTIONS: We interviewed subject matter experts to identify relevant prolonged casualty care medical challenges and selected two casualty types to further develop our model: a large thermal burn model and a severe hypoxia model. We met with a multidisciplinary group of experts in prolonged casualty care, nursing, and critical care to describe how these problems could evolve over time and how to contextualize the problems with a background story and clinical environment with expected resource availability. Following initial scenario drafting, we tested the models with expert clinicians. After multiple tests, we selected the hypoxia model for refinement and testing with inexperienced providers. We tested and refined this model until two research teams could proctor the scenario consistently despite subject performance variability.
MEASUREMENTS AND MAIN RESULTS: We developed a 6-8-hour simulation model that represented a 14-hour scenario. This model of pneumonia evolved from presentation to severe hypoxia necessitating advanced interventions including airway, breathing, and shock management. The model included: context description, caregiver orientation scripts, hourly progressive physiology tracks corresponding to caregiver interventions, intervention/procedure-specific physiology tracks, intervention checklists, equipment lists, prestudy checklists, photographs of setups, procedure, telementor, and role player scripts, business rules, and data collection methods.
CONCLUSIONS: This is the first standardized, high-fidelity simulation model of prolonged casualty care described in the literature. It may be used to assess caregiver performance and patient outcomes resulting from that performance during a complex, 14-hour prolonged casualty care scenario. Because it is standardized, the model may be used to compare differences in the impact of new technologies upon caregiver performance and simulated patient outcomes..

Keywords

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Word Cloud

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