C.K. Medina1, S. Jeffs1, P. Frankiewicz1, S. Thornton2, E. Horne7, S. Ngeve6, T. Thomason1, D. Anani-Wolf1, R. Hueckel3, C. Chumpitazi3,4, E.R. Hanlin3, R. O’Brian3,4, E. Tracy5, E. Greenwald3,4 1Duke University Medical Center, School Of Medicine, Durham, NC, USA 2Duke University Medical Center, Department Of Surgery, Durham, NC, USA 3Duke University Medical Center, Department Of Emergency Medicine, Durham, NC, USA 4Duke University Medical Center, Division Of Pediatric Emergency Medicine, Durham, NC, USA 5University Of North Carolina At Chapel Hill, Division Of Pediatric Surgery, Chapel Hill, NC, USA 6University Of North Carolina At Chapel Hill, School Of Medicine, Chapel Hill, NC, USA 7Johns Hopkins University School Of Medicine, Department Of Surgery, Baltimore, MD, USA
Introduction: Children are disproportionately affected by mass casualty incidents (MCIs) given their anatomic, physiologic, and developmental vulnerabilities. However, children are often not considered in MCI preparation to be able to appropriately triage patients and prioritize resources. May existing MCI simulations rely on high-fidelity patient simulators or standardized patients, which are cost-prohibitive and often exclude pediatric patients. To address the need for rapidly deployable, low-fidelity pediatric MCI simulations, we developed and evaluated a cost-conscious model to teach the principles of JumpSTART,?the pediatric variation of the?simple triage and rapid treatment (START) algorithm.
Methods: This prospective study examined a low-fidelity pediatric MCI triage simulation. Pediatric trauma patients were represented by 2D, life-sized drawings (Figure 1). These models included all pertinent information needed to triage using JumpSTART. Learners included both prehospital and hospital staff with variable training backgrounds. Learners were divided into two multidisciplinary teams and assigned five unique patients with varying triage and acuity levels. Primary outcomes measured were the accuracy of assigned triage categories and Broselow lengths, and time to triage completion. Likert-surveys assessed learner attitudes towards the exercise.
Results: Two MCI simulations were conducted using this curriculum. The first simulation included a total of 18 multidisciplinary participants, and the second 16. Participants included surgery residents, emergency medicine residents, emergency medicine nurses, transport paramedics, an emergency department technician, students, and a respiratory therapist. The first cohort correctly used the JumpSTART Triage Algorithm to assign appropriate triage categories to 9/10 patients, as determined by post-scenario consensus. Only one patient was over-triaged. The second cohort correctly assigned triage categories to 10/10 patients. Broselow lengths were correctly assigned to all patients. Median time to assign a triage category and communicate pertinent findings to the receiving team per patient was 67 seconds (range 30–135) for the first cohort and 64 seconds (range 30-116) for the second cohort. Participant feedback was universally positive.
Conclusion: This simulation curriculum allows for effective teaching of and reflection on a high acuity scenario in a safe and structured environment. This low-fidelity training model for a pediatric MCI creates a simple but dynamic hands-on experience for participants around the JumpSTART Pediatric Triage Algorithm and is easily replicable across environments.