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Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners

OBJECTIVE: The study sought to understand the potential roles of a future artificial intelligence (AI) documentation assistant in primary care consultations and to identify implications for doctors, patients, healthcare system, and technology design from the perspective of general practitioners. MAT...

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Autores principales: Kocaballi, A Baki, Ijaz, Kiran, Laranjo, Liliana, Quiroz, Juan C, Rezazadegan, Dana, Tong, Huong Ly, Willcock, Simon, Berkovsky, Shlomo, Coiera, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671614/
https://www.ncbi.nlm.nih.gov/pubmed/32845984
http://dx.doi.org/10.1093/jamia/ocaa131
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author Kocaballi, A Baki
Ijaz, Kiran
Laranjo, Liliana
Quiroz, Juan C
Rezazadegan, Dana
Tong, Huong Ly
Willcock, Simon
Berkovsky, Shlomo
Coiera, Enrico
author_facet Kocaballi, A Baki
Ijaz, Kiran
Laranjo, Liliana
Quiroz, Juan C
Rezazadegan, Dana
Tong, Huong Ly
Willcock, Simon
Berkovsky, Shlomo
Coiera, Enrico
author_sort Kocaballi, A Baki
collection PubMed
description OBJECTIVE: The study sought to understand the potential roles of a future artificial intelligence (AI) documentation assistant in primary care consultations and to identify implications for doctors, patients, healthcare system, and technology design from the perspective of general practitioners. MATERIALS AND METHODS: Co-design workshops with general practitioners were conducted. The workshops focused on (1) understanding the current consultation context and identifying existing problems, (2) ideating future solutions to these problems, and (3) discussing future roles for AI in primary care. The workshop activities included affinity diagramming, brainwriting, and video prototyping methods. The workshops were audio-recorded and transcribed verbatim. Inductive thematic analysis of the transcripts of conversations was performed. RESULTS: Two researchers facilitated 3 co-design workshops with 16 general practitioners. Three main themes emerged: professional autonomy, human-AI collaboration, and new models of care. Major implications identified within these themes included (1) concerns with medico-legal aspects arising from constant recording and accessibility of full consultation records, (2) future consultations taking place out of the exam rooms in a distributed system involving empowered patients, (3) human conversation and empathy remaining the core tasks of doctors in any future AI-enabled consultations, and (4) questioning the current focus of AI initiatives on improved efficiency as opposed to patient care. CONCLUSIONS: AI documentation assistants will likely to be integral to the future primary care consultations. However, these technologies will still need to be supervised by a human until strong evidence for reliable autonomous performance is available. Therefore, different human-AI collaboration models will need to be designed and evaluated to ensure patient safety, quality of care, doctor safety, and doctor autonomy.
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spelling pubmed-76716142020-11-30 Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners Kocaballi, A Baki Ijaz, Kiran Laranjo, Liliana Quiroz, Juan C Rezazadegan, Dana Tong, Huong Ly Willcock, Simon Berkovsky, Shlomo Coiera, Enrico J Am Med Inform Assoc Research and Applications OBJECTIVE: The study sought to understand the potential roles of a future artificial intelligence (AI) documentation assistant in primary care consultations and to identify implications for doctors, patients, healthcare system, and technology design from the perspective of general practitioners. MATERIALS AND METHODS: Co-design workshops with general practitioners were conducted. The workshops focused on (1) understanding the current consultation context and identifying existing problems, (2) ideating future solutions to these problems, and (3) discussing future roles for AI in primary care. The workshop activities included affinity diagramming, brainwriting, and video prototyping methods. The workshops were audio-recorded and transcribed verbatim. Inductive thematic analysis of the transcripts of conversations was performed. RESULTS: Two researchers facilitated 3 co-design workshops with 16 general practitioners. Three main themes emerged: professional autonomy, human-AI collaboration, and new models of care. Major implications identified within these themes included (1) concerns with medico-legal aspects arising from constant recording and accessibility of full consultation records, (2) future consultations taking place out of the exam rooms in a distributed system involving empowered patients, (3) human conversation and empathy remaining the core tasks of doctors in any future AI-enabled consultations, and (4) questioning the current focus of AI initiatives on improved efficiency as opposed to patient care. CONCLUSIONS: AI documentation assistants will likely to be integral to the future primary care consultations. However, these technologies will still need to be supervised by a human until strong evidence for reliable autonomous performance is available. Therefore, different human-AI collaboration models will need to be designed and evaluated to ensure patient safety, quality of care, doctor safety, and doctor autonomy. Oxford University Press 2020-08-26 /pmc/articles/PMC7671614/ /pubmed/32845984 http://dx.doi.org/10.1093/jamia/ocaa131 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Research and Applications
Kocaballi, A Baki
Ijaz, Kiran
Laranjo, Liliana
Quiroz, Juan C
Rezazadegan, Dana
Tong, Huong Ly
Willcock, Simon
Berkovsky, Shlomo
Coiera, Enrico
Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners
title Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners
title_full Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners
title_fullStr Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners
title_full_unstemmed Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners
title_short Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners
title_sort envisioning an artificial intelligence documentation assistant for future primary care consultations: a co-design study with general practitioners
topic Research and Applications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671614/
https://www.ncbi.nlm.nih.gov/pubmed/32845984
http://dx.doi.org/10.1093/jamia/ocaa131
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