Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review
BackgroundAs the adoption of artificial intelligence (AI) in health care increases, it will become increasingly crucial to involve health care professionals (HCPs) in developing, validating, and implementing AI-enabled technologies. However, because of a lack of AI literacy,...
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| Format: | Article |
| Language: | English |
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JMIR Publications
2021-12-01
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| Series: | JMIR Medical Education |
| Online Access: | https://mededu.jmir.org/2021/4/e31043 |
| _version_ | 1797735455947489280 |
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| author | Rebecca Charow Tharshini Jeyakumar Sarah Younus Elham Dolatabadi Mohammad Salhia Dalia Al-Mouaswas Melanie Anderson Sarmini Balakumar Megan Clare Azra Dhalla Caitlin Gillan Shabnam Haghzare Ethan Jackson Nadim Lalani Jane Mattson Wanda Peteanu Tim Tripp Jacqueline Waldorf Spencer Williams Walter Tavares David Wiljer |
| author_facet | Rebecca Charow Tharshini Jeyakumar Sarah Younus Elham Dolatabadi Mohammad Salhia Dalia Al-Mouaswas Melanie Anderson Sarmini Balakumar Megan Clare Azra Dhalla Caitlin Gillan Shabnam Haghzare Ethan Jackson Nadim Lalani Jane Mattson Wanda Peteanu Tim Tripp Jacqueline Waldorf Spencer Williams Walter Tavares David Wiljer |
| author_sort | Rebecca Charow |
| collection | DOAJ |
| description |
BackgroundAs the adoption of artificial intelligence (AI) in health care increases, it will become increasingly crucial to involve health care professionals (HCPs) in developing, validating, and implementing AI-enabled technologies. However, because of a lack of AI literacy, most HCPs are not adequately prepared for this revolution. This is a significant barrier to adopting and implementing AI that will affect patients. In addition, the limited existing AI education programs face barriers to development and implementation at various levels of medical education.
ObjectiveWith a view to informing future AI education programs for HCPs, this scoping review aims to provide an overview of the types of current or past AI education programs that pertains to the programs’ curricular content, modes of delivery, critical implementation factors for education delivery, and outcomes used to assess the programs’ effectiveness.
MethodsAfter the creation of a search strategy and keyword searches, a 2-stage screening process was conducted by 2 independent reviewers to determine study eligibility. When consensus was not reached, the conflict was resolved by consulting a third reviewer. This process consisted of a title and abstract scan and a full-text review. The articles were included if they discussed an actual training program or educational intervention, or a potential training program or educational intervention and the desired content to be covered, focused on AI, and were designed or intended for HCPs (at any stage of their career).
ResultsOf the 10,094 unique citations scanned, 41 (0.41%) studies relevant to our eligibility criteria were identified. Among the 41 included studies, 10 (24%) described 13 unique programs and 31 (76%) discussed recommended curricular content. The curricular content of the unique programs ranged from AI use, AI interpretation, and cultivating skills to explain results derived from AI algorithms. The curricular topics were categorized into three main domains: cognitive, psychomotor, and affective.
ConclusionsThis review provides an overview of the current landscape of AI in medical education and highlights the skills and competencies required by HCPs to effectively use AI in enhancing the quality of care and optimizing patient outcomes. Future education efforts should focus on the development of regulatory strategies, a multidisciplinary approach to curriculum redesign, a competency-based curriculum, and patient-clinician interaction.
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| first_indexed | 2024-03-12T12:59:17Z |
| format | Article |
| id | doaj.art-366a6803d3cd41f7a563860090a8f8ef |
| institution | Directory Open Access Journal |
| issn | 2369-3762 |
| language | English |
| last_indexed | 2024-03-12T12:59:17Z |
| publishDate | 2021-12-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Medical Education |
| spelling | doaj.art-366a6803d3cd41f7a563860090a8f8ef2023-08-28T20:00:20ZengJMIR PublicationsJMIR Medical Education2369-37622021-12-0174e3104310.2196/31043Artificial Intelligence Education Programs for Health Care Professionals: Scoping ReviewRebecca Charowhttps://orcid.org/0000-0002-8553-4006Tharshini Jeyakumarhttps://orcid.org/0000-0002-4482-3637Sarah Younushttps://orcid.org/0000-0002-0728-7628Elham Dolatabadihttps://orcid.org/0000-0003-2236-2611Mohammad Salhiahttps://orcid.org/0000-0003-0841-1456Dalia Al-Mouaswashttps://orcid.org/0000-0002-5620-0832Melanie Andersonhttps://orcid.org/0000-0001-9786-1656Sarmini Balakumarhttps://orcid.org/0000-0001-6061-5929Megan Clarehttps://orcid.org/0000-0002-2778-6002Azra Dhallahttps://orcid.org/0000-0001-9806-3664Caitlin Gillanhttps://orcid.org/0000-0002-1612-7423Shabnam Haghzarehttps://orcid.org/0000-0001-7973-2586Ethan Jacksonhttps://orcid.org/0000-0001-8988-302XNadim Lalanihttps://orcid.org/0000-0002-7570-4681Jane Mattsonhttps://orcid.org/0000-0001-8121-6126Wanda Peteanuhttps://orcid.org/0000-0002-0119-3364Tim Tripphttps://orcid.org/0000-0003-3967-2181Jacqueline Waldorfhttps://orcid.org/0000-0003-1922-0575Spencer Williamshttps://orcid.org/0000-0003-3799-5462Walter Tavareshttps://orcid.org/0000-0001-8267-9448David Wiljerhttps://orcid.org/0000-0002-2748-2658 BackgroundAs the adoption of artificial intelligence (AI) in health care increases, it will become increasingly crucial to involve health care professionals (HCPs) in developing, validating, and implementing AI-enabled technologies. However, because of a lack of AI literacy, most HCPs are not adequately prepared for this revolution. This is a significant barrier to adopting and implementing AI that will affect patients. In addition, the limited existing AI education programs face barriers to development and implementation at various levels of medical education. ObjectiveWith a view to informing future AI education programs for HCPs, this scoping review aims to provide an overview of the types of current or past AI education programs that pertains to the programs’ curricular content, modes of delivery, critical implementation factors for education delivery, and outcomes used to assess the programs’ effectiveness. MethodsAfter the creation of a search strategy and keyword searches, a 2-stage screening process was conducted by 2 independent reviewers to determine study eligibility. When consensus was not reached, the conflict was resolved by consulting a third reviewer. This process consisted of a title and abstract scan and a full-text review. The articles were included if they discussed an actual training program or educational intervention, or a potential training program or educational intervention and the desired content to be covered, focused on AI, and were designed or intended for HCPs (at any stage of their career). ResultsOf the 10,094 unique citations scanned, 41 (0.41%) studies relevant to our eligibility criteria were identified. Among the 41 included studies, 10 (24%) described 13 unique programs and 31 (76%) discussed recommended curricular content. The curricular content of the unique programs ranged from AI use, AI interpretation, and cultivating skills to explain results derived from AI algorithms. The curricular topics were categorized into three main domains: cognitive, psychomotor, and affective. ConclusionsThis review provides an overview of the current landscape of AI in medical education and highlights the skills and competencies required by HCPs to effectively use AI in enhancing the quality of care and optimizing patient outcomes. Future education efforts should focus on the development of regulatory strategies, a multidisciplinary approach to curriculum redesign, a competency-based curriculum, and patient-clinician interaction. https://mededu.jmir.org/2021/4/e31043 |
| spellingShingle | Rebecca Charow Tharshini Jeyakumar Sarah Younus Elham Dolatabadi Mohammad Salhia Dalia Al-Mouaswas Melanie Anderson Sarmini Balakumar Megan Clare Azra Dhalla Caitlin Gillan Shabnam Haghzare Ethan Jackson Nadim Lalani Jane Mattson Wanda Peteanu Tim Tripp Jacqueline Waldorf Spencer Williams Walter Tavares David Wiljer Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review JMIR Medical Education |
| title | Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review |
| title_full | Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review |
| title_fullStr | Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review |
| title_full_unstemmed | Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review |
| title_short | Artificial Intelligence Education Programs for Health Care Professionals: Scoping Review |
| title_sort | artificial intelligence education programs for health care professionals scoping review |
| url | https://mededu.jmir.org/2021/4/e31043 |
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