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Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction

BACKGROUND: Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction. AIMS: Aifred is an artificial intelligence-powered clinical...

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Autores principales: Benrimoh, David, Tanguay-Sela, Myriam, Perlman, Kelly, Israel, Sonia, Mehltretter, Joseph, Armstrong, Caitrin, Fratila, Robert, Parikh, Sagar V., Karp, Jordan F., Heller, Katherine, Vahia, Ipsit V., Blumberger, Daniel M., Karama, Sherif, Vigod, Simone N., Myhr, Gail, Martins, Ruben, Rollins, Colleen, Popescu, Christina, Lundrigan, Eryn, Snook, Emily, Wakid, Marina, Williams, Jérôme, Soufi, Ghassen, Perez, Tamara, Tunteng, Jingla-Fri, Rosenfeld, Katherine, Miresco, Marc, Turecki, Gustavo, Gomez Cardona, Liliana, Linnaranta, Outi, Margolese, Howard C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058891/
https://www.ncbi.nlm.nih.gov/pubmed/33403948
http://dx.doi.org/10.1192/bjo.2020.127
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author Benrimoh, David
Tanguay-Sela, Myriam
Perlman, Kelly
Israel, Sonia
Mehltretter, Joseph
Armstrong, Caitrin
Fratila, Robert
Parikh, Sagar V.
Karp, Jordan F.
Heller, Katherine
Vahia, Ipsit V.
Blumberger, Daniel M.
Karama, Sherif
Vigod, Simone N.
Myhr, Gail
Martins, Ruben
Rollins, Colleen
Popescu, Christina
Lundrigan, Eryn
Snook, Emily
Wakid, Marina
Williams, Jérôme
Soufi, Ghassen
Perez, Tamara
Tunteng, Jingla-Fri
Rosenfeld, Katherine
Miresco, Marc
Turecki, Gustavo
Gomez Cardona, Liliana
Linnaranta, Outi
Margolese, Howard C.
author_facet Benrimoh, David
Tanguay-Sela, Myriam
Perlman, Kelly
Israel, Sonia
Mehltretter, Joseph
Armstrong, Caitrin
Fratila, Robert
Parikh, Sagar V.
Karp, Jordan F.
Heller, Katherine
Vahia, Ipsit V.
Blumberger, Daniel M.
Karama, Sherif
Vigod, Simone N.
Myhr, Gail
Martins, Ruben
Rollins, Colleen
Popescu, Christina
Lundrigan, Eryn
Snook, Emily
Wakid, Marina
Williams, Jérôme
Soufi, Ghassen
Perez, Tamara
Tunteng, Jingla-Fri
Rosenfeld, Katherine
Miresco, Marc
Turecki, Gustavo
Gomez Cardona, Liliana
Linnaranta, Outi
Margolese, Howard C.
author_sort Benrimoh, David
collection PubMed
description BACKGROUND: Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction. AIMS: Aifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician–patient interaction. METHOD: Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback. RESULTS: All 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician–patient interaction. CONCLUSIONS: The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician–patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.
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spelling pubmed-80588912021-05-04 Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction Benrimoh, David Tanguay-Sela, Myriam Perlman, Kelly Israel, Sonia Mehltretter, Joseph Armstrong, Caitrin Fratila, Robert Parikh, Sagar V. Karp, Jordan F. Heller, Katherine Vahia, Ipsit V. Blumberger, Daniel M. Karama, Sherif Vigod, Simone N. Myhr, Gail Martins, Ruben Rollins, Colleen Popescu, Christina Lundrigan, Eryn Snook, Emily Wakid, Marina Williams, Jérôme Soufi, Ghassen Perez, Tamara Tunteng, Jingla-Fri Rosenfeld, Katherine Miresco, Marc Turecki, Gustavo Gomez Cardona, Liliana Linnaranta, Outi Margolese, Howard C. BJPsych Open Papers BACKGROUND: Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction. AIMS: Aifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician–patient interaction. METHOD: Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback. RESULTS: All 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician–patient interaction. CONCLUSIONS: The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician–patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials. Cambridge University Press 2021-01-06 /pmc/articles/PMC8058891/ /pubmed/33403948 http://dx.doi.org/10.1192/bjo.2020.127 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
spellingShingle Papers
Benrimoh, David
Tanguay-Sela, Myriam
Perlman, Kelly
Israel, Sonia
Mehltretter, Joseph
Armstrong, Caitrin
Fratila, Robert
Parikh, Sagar V.
Karp, Jordan F.
Heller, Katherine
Vahia, Ipsit V.
Blumberger, Daniel M.
Karama, Sherif
Vigod, Simone N.
Myhr, Gail
Martins, Ruben
Rollins, Colleen
Popescu, Christina
Lundrigan, Eryn
Snook, Emily
Wakid, Marina
Williams, Jérôme
Soufi, Ghassen
Perez, Tamara
Tunteng, Jingla-Fri
Rosenfeld, Katherine
Miresco, Marc
Turecki, Gustavo
Gomez Cardona, Liliana
Linnaranta, Outi
Margolese, Howard C.
Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction
title Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction
title_full Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction
title_fullStr Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction
title_full_unstemmed Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction
title_short Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction
title_sort using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician–patient interaction
topic Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058891/
https://www.ncbi.nlm.nih.gov/pubmed/33403948
http://dx.doi.org/10.1192/bjo.2020.127
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