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Evaluation of high-fidelity simulation training in radiation oncology using an outcomes logic model

PURPOSE: To evaluate the feasibility and educational value of high-fidelity, interprofessional team-based simulation in radiation oncology. METHODS: The simulation event was conducted in a radiation oncology department during a non-clinical day. It involved 5 simulation scenarios that were run over...

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Autores principales: Giuliani, Meredith, Gillan, Caitlin, Wong, Olive, Harnett, Nicole, Milne, Emily, Moseley, Doug, Thompson, Robert, Catton, Pamela, Bissonnette, Jean-Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155118/
https://www.ncbi.nlm.nih.gov/pubmed/25169674
http://dx.doi.org/10.1186/1748-717X-9-189
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author Giuliani, Meredith
Gillan, Caitlin
Wong, Olive
Harnett, Nicole
Milne, Emily
Moseley, Doug
Thompson, Robert
Catton, Pamela
Bissonnette, Jean-Pierre
author_facet Giuliani, Meredith
Gillan, Caitlin
Wong, Olive
Harnett, Nicole
Milne, Emily
Moseley, Doug
Thompson, Robert
Catton, Pamela
Bissonnette, Jean-Pierre
author_sort Giuliani, Meredith
collection PubMed
description PURPOSE: To evaluate the feasibility and educational value of high-fidelity, interprofessional team-based simulation in radiation oncology. METHODS: The simulation event was conducted in a radiation oncology department during a non-clinical day. It involved 5 simulation scenarios that were run over three 105 minute timeslots in a single day. High-acuity, low-frequency clinical situations were selected and included HDR brachytherapy emergency, 4D CT artifact management, pediatric emergency clinical mark-up, electron scalp trial set-up and a cone beam CT misregistration incident. A purposive sample of a minimum of 20 trainees was required to assess recruitment feasibility. A faculty radiation oncologist (RO), medical physicist (MP) or radiation therapist (RTT), facilitated each case. Participants completed a pre event survey of demographic data and motivation for participation. A post event survey collected perceptions of familiarity with the clinical content, comfort with interprofessional practice, and event satisfaction, scored on a 1–10 scale in terms of clinical knowledge, clinical decision making, clinical skills, exposure to other trainees and interprofessional communication. Means and standard deviations were calculated. RESULTS: Twenty-one trainees participated including 6 ROs (29%), 6 MPs (29%), and 9 RTTs (43%). All 12 cases (100%) were completed within the allocated 105 minutes. Nine faculty facilitators, (3MP, 2 RO, 4 RTTs) were required for 405 minutes each. Additional costs associated with this event were 154 hours to build the high fidelity scenarios, 2 standardized patients (SPs) for a total of 15.5 hours, and consumables.The mean (±SD) educational value score reported by participants with respect to clinical knowledge was 8.9 (1.1), clinical decision making 8.9 (1.3), clinical skills 8.9 (1.1), exposure to other trainees 9.1 (2.3) and interprofessional communication 9.1 (1.0). Fifteen (71%) participants reported the cases were of an appropriate complexity. The importance of further simulation events was rated highly at 9.1/10. CONCLUSIONS: High-fidelity simulation training is feasible and effective in a radiation oncology context. However, such educational activities require significant resources, including personnel and equipment.
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spelling pubmed-41551182014-09-06 Evaluation of high-fidelity simulation training in radiation oncology using an outcomes logic model Giuliani, Meredith Gillan, Caitlin Wong, Olive Harnett, Nicole Milne, Emily Moseley, Doug Thompson, Robert Catton, Pamela Bissonnette, Jean-Pierre Radiat Oncol Research PURPOSE: To evaluate the feasibility and educational value of high-fidelity, interprofessional team-based simulation in radiation oncology. METHODS: The simulation event was conducted in a radiation oncology department during a non-clinical day. It involved 5 simulation scenarios that were run over three 105 minute timeslots in a single day. High-acuity, low-frequency clinical situations were selected and included HDR brachytherapy emergency, 4D CT artifact management, pediatric emergency clinical mark-up, electron scalp trial set-up and a cone beam CT misregistration incident. A purposive sample of a minimum of 20 trainees was required to assess recruitment feasibility. A faculty radiation oncologist (RO), medical physicist (MP) or radiation therapist (RTT), facilitated each case. Participants completed a pre event survey of demographic data and motivation for participation. A post event survey collected perceptions of familiarity with the clinical content, comfort with interprofessional practice, and event satisfaction, scored on a 1–10 scale in terms of clinical knowledge, clinical decision making, clinical skills, exposure to other trainees and interprofessional communication. Means and standard deviations were calculated. RESULTS: Twenty-one trainees participated including 6 ROs (29%), 6 MPs (29%), and 9 RTTs (43%). All 12 cases (100%) were completed within the allocated 105 minutes. Nine faculty facilitators, (3MP, 2 RO, 4 RTTs) were required for 405 minutes each. Additional costs associated with this event were 154 hours to build the high fidelity scenarios, 2 standardized patients (SPs) for a total of 15.5 hours, and consumables.The mean (±SD) educational value score reported by participants with respect to clinical knowledge was 8.9 (1.1), clinical decision making 8.9 (1.3), clinical skills 8.9 (1.1), exposure to other trainees 9.1 (2.3) and interprofessional communication 9.1 (1.0). Fifteen (71%) participants reported the cases were of an appropriate complexity. The importance of further simulation events was rated highly at 9.1/10. CONCLUSIONS: High-fidelity simulation training is feasible and effective in a radiation oncology context. However, such educational activities require significant resources, including personnel and equipment. BioMed Central 2014-08-28 /pmc/articles/PMC4155118/ /pubmed/25169674 http://dx.doi.org/10.1186/1748-717X-9-189 Text en © Giuliani et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Giuliani, Meredith
Gillan, Caitlin
Wong, Olive
Harnett, Nicole
Milne, Emily
Moseley, Doug
Thompson, Robert
Catton, Pamela
Bissonnette, Jean-Pierre
Evaluation of high-fidelity simulation training in radiation oncology using an outcomes logic model
title Evaluation of high-fidelity simulation training in radiation oncology using an outcomes logic model
title_full Evaluation of high-fidelity simulation training in radiation oncology using an outcomes logic model
title_fullStr Evaluation of high-fidelity simulation training in radiation oncology using an outcomes logic model
title_full_unstemmed Evaluation of high-fidelity simulation training in radiation oncology using an outcomes logic model
title_short Evaluation of high-fidelity simulation training in radiation oncology using an outcomes logic model
title_sort evaluation of high-fidelity simulation training in radiation oncology using an outcomes logic model
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155118/
https://www.ncbi.nlm.nih.gov/pubmed/25169674
http://dx.doi.org/10.1186/1748-717X-9-189
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