Assessing the Feasibility of On-Shift Simulation to Improve Capacity Assessments by EMS Clinicians A Pilot Project
Main Article Content
Abstract
Objective
Determining the decision-making capacity of patients in the prehospital setting is a high-risk area for EMS systems. This risk is only enhanced by the growing prevalence of mental, neurological, and substance use disorders. This study sought to evaluate the feasibility of on-shift simulation as an educational method, in this case to improve EMS clinicians’ ability and confidence in performing capacity assessments.
Methods
This was a prospective experimental feasibility study performed at an urban, tertiary, academic medical center that operates its own EMS service. All participants were active EMTs or Paramedics. Subjects completed a pretest containing 10 patient scenarios addressing specific components of a complete capacity assessment. For each, participants were asked to decide if the patient had capacity and to rate how confident they were. They then participated in a simulated encounter with a standardized patient, designed to evaluate and teach skills in capacity assessment. A post-scenario debrief and didactic session were conducted. Lastly, subjects took a post-test consisting of the same 10 scenarios and confidence assessments.
Results
22 subjects completed the study. While there was no significant difference between the number of scenarios answered correctly before and after the intervention (9.18 vs 9.27), participants’ confidence scores did significantly increase (87.2 to 95.2, p < 0.001). This increase was driven by scenarios pertaining to mild dementia, pediatrics, and substance use.
Conclusions
Prehospital clinicians were able to correctly assess capacity in a variety of scenarios. A didactic session including a simulated patient encounter led to a significant increase in participants’ confidence in performing capacity assessments. This study revealed specific areas in which clinicians would likely benefit from further education, but further research is needed to ensure generalizability.
Article Details
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