Using a Logic Model to Enable and Evaluate Long-Term Outcomes of a Mass Casualty Training Program: A Single Center Case Study.
Disaster Med Public Health Prep
; 16(3): 1116-1122, 2022 06.
Article
em En
| MEDLINE
| ID: mdl-34044903
PURPOSE: Global health disasters are on the rise and can occur at any time with little advance warning, necessitating preparation. The authors created a comprehensive evidence-based Emergency Preparedness Training Program focused on long-term retention and sustained learner engagement. METHOD: A prospective observational study was conducted of a simulation-based mass casualty event training program designed using an outcomes-based logic model. A total of 25 frontline healthcare workers from multiple hospital sites in the New York metropolitan area participated in an 8-hour immersive workshop. Data was collected from assessments, and surveys provided to participants 3 weeks prior to the workshop, immediately following the workshop, and 3 months after completion of the workshop. RESULTS: The mean percentage of total knowledge scores improved across pre-workshop, post-workshop and retention (3 months post-workshop) assessments (53.2% vs. 64.8% vs. 67.6%, P < 0.05). Average comfort scores in the core MCI competencies increased across pre-workshop, post-workshop and retention self-assessments (P < 0.01). Of the participants assessed at 3 months retention (n = 14, 56%), 50.0% (n = 7) assisted in updating their hospital's emergency operations plan and 50.0% (n = 7) pursued further self-directed learning in disaster preparedness medicine. CONCLUSIONS: The use of the logic model provided a transparent framework for the design, implementation, and evaluation of a competency-based EPT program at a single academic center.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Defesa Civil
/
Planejamento em Desastres
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Medicina de Desastres
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Incidentes com Feridos em Massa
Tipo de estudo:
Observational_studies
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Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article