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A Qualitative Thematic Analysis of Addressing the Why: An Artificial Intelligence (AI) in Healthcare Symposium
Healthcare managers and clinicians are inefficient in the processes of workflows and documentation. The inefficiency is due in part by increasing demands of insurance companies, regulatory demands from the government, and human error. Artificial intelligence (AI) can improve healthcare processes by...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060766/ https://www.ncbi.nlm.nih.gov/pubmed/35510027 http://dx.doi.org/10.7759/cureus.23704 |
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author | Borgstadt, Joshua T Kalpas, Edward A Pond, Hayden M |
author_facet | Borgstadt, Joshua T Kalpas, Edward A Pond, Hayden M |
author_sort | Borgstadt, Joshua T |
collection | PubMed |
description | Healthcare managers and clinicians are inefficient in the processes of workflows and documentation. The inefficiency is due in part by increasing demands of insurance companies, regulatory demands from the government, and human error. Artificial intelligence (AI) can improve healthcare processes by decreasing variability, thus improving patient and physician experience and patient outcomes. This project brings together a panel of five experts to discuss problems in medicine and some of the tools available through AI and technology to address these problems. The symposium modeled a "flipped classroom" format. The first five 20-minute modules were uploaded to a web-based platform for viewing in advance of the 60-minute moderated roundtable (Zoom, Zoom Video Communications, San Jose, CA, USA). The following themes emerged after reviewing the transcribed data: data privacy and access (N=3, number of times identified); process improvement (N=2); physician experience (N=1); value in data (N=2); and bias in healthcare and AI (N=3). For AI to become implemented on a large scale in healthcare, many areas will need continued discussion and research, including a continued look into how AI can add value to workflow and knowledge augmentation. In addition, standards for the implementation of AI and a methodical approach to the analysis of the effectiveness of algorithms coupled with training of healthcare professionals in the language of AI algorithms will be helpful to ensure that AI is integrated safely. |
format | Online Article Text |
id | pubmed-9060766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-90607662022-05-03 A Qualitative Thematic Analysis of Addressing the Why: An Artificial Intelligence (AI) in Healthcare Symposium Borgstadt, Joshua T Kalpas, Edward A Pond, Hayden M Cureus Quality Improvement Healthcare managers and clinicians are inefficient in the processes of workflows and documentation. The inefficiency is due in part by increasing demands of insurance companies, regulatory demands from the government, and human error. Artificial intelligence (AI) can improve healthcare processes by decreasing variability, thus improving patient and physician experience and patient outcomes. This project brings together a panel of five experts to discuss problems in medicine and some of the tools available through AI and technology to address these problems. The symposium modeled a "flipped classroom" format. The first five 20-minute modules were uploaded to a web-based platform for viewing in advance of the 60-minute moderated roundtable (Zoom, Zoom Video Communications, San Jose, CA, USA). The following themes emerged after reviewing the transcribed data: data privacy and access (N=3, number of times identified); process improvement (N=2); physician experience (N=1); value in data (N=2); and bias in healthcare and AI (N=3). For AI to become implemented on a large scale in healthcare, many areas will need continued discussion and research, including a continued look into how AI can add value to workflow and knowledge augmentation. In addition, standards for the implementation of AI and a methodical approach to the analysis of the effectiveness of algorithms coupled with training of healthcare professionals in the language of AI algorithms will be helpful to ensure that AI is integrated safely. Cureus 2022-03-31 /pmc/articles/PMC9060766/ /pubmed/35510027 http://dx.doi.org/10.7759/cureus.23704 Text en Copyright © 2022, Borgstadt et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Quality Improvement Borgstadt, Joshua T Kalpas, Edward A Pond, Hayden M A Qualitative Thematic Analysis of Addressing the Why: An Artificial Intelligence (AI) in Healthcare Symposium |
title | A Qualitative Thematic Analysis of Addressing the Why: An Artificial Intelligence (AI) in Healthcare Symposium |
title_full | A Qualitative Thematic Analysis of Addressing the Why: An Artificial Intelligence (AI) in Healthcare Symposium |
title_fullStr | A Qualitative Thematic Analysis of Addressing the Why: An Artificial Intelligence (AI) in Healthcare Symposium |
title_full_unstemmed | A Qualitative Thematic Analysis of Addressing the Why: An Artificial Intelligence (AI) in Healthcare Symposium |
title_short | A Qualitative Thematic Analysis of Addressing the Why: An Artificial Intelligence (AI) in Healthcare Symposium |
title_sort | qualitative thematic analysis of addressing the why: an artificial intelligence (ai) in healthcare symposium |
topic | Quality Improvement |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060766/ https://www.ncbi.nlm.nih.gov/pubmed/35510027 http://dx.doi.org/10.7759/cureus.23704 |
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