High-fidelity simulation self-training enables novice bronchoscopists to acquire basic bronchoscopy skills comparable to their moderately and highly experienced counterparts.
BMC Med Educ
; 18(1): 191, 2018 Aug 07.
Article
en En
| MEDLINE
| ID: mdl-30086734
ABSTRACT
BACKGROUND:
We sought to determine whether a self-training program on a high-fidelity flexible bronchoscopy (FB) simulator would allow residents who were novices in bronchoscopy to acquire competencies similar to those of experienced bronchoscopists as concerns the visualization of the bronchial tree and the identification of its anatomical elements.METHODS:
We performed a prospective cohort study, categorizing bronchoscopists into three groups according to their experience level novice (Group A, no FBs performed, n = 8), moderate (Group B, 30 ≤ FBs performed ≤200, n = 17) or high (Group C, > 200 FBs performed, n = 9). All were initially evaluated on their ability to perform on a high-fidelity FB simulator a complete visualization/identification of the bronchial tree in the least amount of time possible. The residents in Group A then completed a simulation-based self-training program and underwent a final evaluation thereafter.RESULTS:
The median total procedure time for Group A fell from 561 s (IQR = 134) in the initial evaluation to 216 s (IQR = 257) in the final evaluation (P = 0.002). The visualization and identification scores for Group A also improved significantly in the final evaluation. Resultantly, the overall performance score for Group A climbed from 5.9% (IQR = 5.1) before self-training to 25.5% (IQR = 26.3) after (P = 0.002), thus becoming comparable to the overall performance scores of Group B (25.3%, IQR = 13.8) and Group C (22.2%, IQR = 5.5).CONCLUSIONS:
Novice bronchoscopists who self-train on a high-fidelity simulator acquire basic competencies similar to those of moderately or even highly experienced bronchoscopists. High-fidelity simulation should be rapidly integrated within the learning curriculum and replace traditional, in-patient learning methods.Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Simulación por Computador
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Bronquios
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Broncoscopía
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Competencia Clínica
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Mejoramiento de la Calidad
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Autoaprendizaje como Asunto
Tipo de estudio:
Observational_studies
/
Prognostic_studies
Límite:
Female
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Humans
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Male
País/Región como asunto:
Europa
Idioma:
En
Revista:
BMC Med Educ
Asunto de la revista:
EDUCACAO
Año:
2018
Tipo del documento:
Article
País de afiliación:
Francia