Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.4/1736
Título: Mixed-realism simulation of adverse event disclosure: an educational methodology and assessment instrument.
Autor: Matos, FM
Raemer, DB
Palavras-chave: Anestesiologia/ensino
Competência Clínica
Erro Médico
Data: 2013
Citação: Simul Healthc. 2013;8(2):84-90.
Resumo: INTRODUCTION: Physicians have an ethical duty to disclose adverse events to patients or families. Various strategies have been reported for teaching disclosure, but no instruments have been shown to be reliable for assessing them.The aims of this study were to report a structured method for teaching adverse event disclosure using mixed-realism simulation, develop and begin to validate an instrument for assessing performance, and describe the disclosure practice of anesthesiology trainees. METHODS: Forty-two anesthesiology trainees participated in a 2-part exercise with mixed-realism simulation. The first part took place using a mannequin patient in a simulated operating room where trainees became enmeshed in a clinical episode that led to an adverse event and the second part in a simulated postoperative care unit where the learner is asked to disclose to a standardized patient who systematically moves through epochs of grief response. Two raters scored subjects using an assessment instrument we developed that combines a 4-element behaviorally anchored rating scale (BARS) and a 5-stage objective rating scale. RESULTS: The performance scores for elements within the BARS and the 5-stage instrument showed excellent interrater reliability (Cohen's κ = 0.7), appropriate range (mean range for BARS, 4.20-4.47; mean range for 5-stage instrument, 3.73-4.46), and high internal consistency (P < 0.05). CONCLUSIONS: We have demonstrated a comprehensive methodology using a mixed-realism simulation that engages learners in an adverse event and allows them to practice disclosure to a structured range of patient responses. We have developed a reliable 2-part instrument with strong psychometric properties for assessing disclosure performance.
Peer review: yes
URI: http://hdl.handle.net/10400.4/1736
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