Competencies for the Use of Artificial Intelligence in Primary Care
The artificial intelligence (AI) revolution has arrived for the health care sector and is finally penetrating the far-reaching but perpetually underfinanced primary care platform. While AI has the potential to facilitate the achievement of the Quintuple Aim (better patient outcomes, population healt...
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Veröffentlicht in: | Annals of family medicine 2022-11, Vol.20 (6), p.559-563 |
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description | The artificial intelligence (AI) revolution has arrived for the health care sector and is finally penetrating the far-reaching but perpetually underfinanced primary care platform. While AI has the potential to facilitate the achievement of the Quintuple Aim (better patient outcomes, population health, and health equity at lower costs while preserving clinician well-being), inattention to primary care training in the use of AI-based tools risks the opposite effects, imposing harm and exacerbating inequalities. The impact of AI-based tools on these aims will depend heavily on the decisions and skills of primary care clinicians; therefore, appropriate medical education and training will be crucial to maximize potential benefits and minimize harms. To facilitate this training, we propose 6 domains of competency for the effective deployment of AI-based tools in primary care: (1) foundational knowledge (what is this tool?), (2) critical appraisal (should I use this tool?), (3) medical decision making (when should I use this tool?), (4) technical use (how do I use this tool?), (5) patient communication (how should I communicate with patients regarding the use of this tool?), and (6) awareness of unintended consequences (what are the "side effects" of this tool?). Integrating these competencies will not be straightforward because of the breadth of knowledge already incorporated into family medicine training and the constantly changing technological landscape. Nonetheless, even incremental increases in AI-relevant training may be beneficial, and the sooner these challenges are tackled, the sooner the primary care workforce and those served by it will begin to reap the benefits. |
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While AI has the potential to facilitate the achievement of the Quintuple Aim (better patient outcomes, population health, and health equity at lower costs while preserving clinician well-being), inattention to primary care training in the use of AI-based tools risks the opposite effects, imposing harm and exacerbating inequalities. The impact of AI-based tools on these aims will depend heavily on the decisions and skills of primary care clinicians; therefore, appropriate medical education and training will be crucial to maximize potential benefits and minimize harms. To facilitate this training, we propose 6 domains of competency for the effective deployment of AI-based tools in primary care: (1) foundational knowledge (what is this tool?), (2) critical appraisal (should I use this tool?), (3) medical decision making (when should I use this tool?), (4) technical use (how do I use this tool?), (5) patient communication (how should I communicate with patients regarding the use of this tool?), and (6) awareness of unintended consequences (what are the "side effects" of this tool?). Integrating these competencies will not be straightforward because of the breadth of knowledge already incorporated into family medicine training and the constantly changing technological landscape. Nonetheless, even incremental increases in AI-relevant training may be beneficial, and the sooner these challenges are tackled, the sooner the primary care workforce and those served by it will begin to reap the benefits.</description><identifier>ISSN: 1544-1709</identifier><identifier>EISSN: 1544-1717</identifier><identifier>DOI: 10.1370/afm.2887</identifier><identifier>PMID: 36443071</identifier><language>eng</language><publisher>United States: Annals of Family Medicine</publisher><subject>Analysis ; Artificial Intelligence ; Clinical competence ; Clinical Decision-Making ; Communication ; Humans ; Medical personnel ; Primary Health Care ; Special Reports ; Technology ; Technology application ; Training</subject><ispartof>Annals of family medicine, 2022-11, Vol.20 (6), p.559-563</ispartof><rights>2022 Annals of Family Medicine, Inc.</rights><rights>COPYRIGHT 2022 Annals of Family Medicine</rights><rights>2022 Annals of Family Medicine, Inc. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c508t-1d4e03de79bbabbe9c5f04af172c0e19e4d99c60f26be735f1c0f84fa25aca1c3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9705044/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9705044/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36443071$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liaw, Winston</creatorcontrib><creatorcontrib>Kueper, Jacqueline K</creatorcontrib><creatorcontrib>Lin, Steven</creatorcontrib><creatorcontrib>Bazemore, Andrew</creatorcontrib><creatorcontrib>Kakadiaris, Ioannis</creatorcontrib><title>Competencies for the Use of Artificial Intelligence in Primary Care</title><title>Annals of family medicine</title><addtitle>Ann Fam Med</addtitle><description>The artificial intelligence (AI) revolution has arrived for the health care sector and is finally penetrating the far-reaching but perpetually underfinanced primary care platform. While AI has the potential to facilitate the achievement of the Quintuple Aim (better patient outcomes, population health, and health equity at lower costs while preserving clinician well-being), inattention to primary care training in the use of AI-based tools risks the opposite effects, imposing harm and exacerbating inequalities. The impact of AI-based tools on these aims will depend heavily on the decisions and skills of primary care clinicians; therefore, appropriate medical education and training will be crucial to maximize potential benefits and minimize harms. To facilitate this training, we propose 6 domains of competency for the effective deployment of AI-based tools in primary care: (1) foundational knowledge (what is this tool?), (2) critical appraisal (should I use this tool?), (3) medical decision making (when should I use this tool?), (4) technical use (how do I use this tool?), (5) patient communication (how should I communicate with patients regarding the use of this tool?), and (6) awareness of unintended consequences (what are the "side effects" of this tool?). Integrating these competencies will not be straightforward because of the breadth of knowledge already incorporated into family medicine training and the constantly changing technological landscape. Nonetheless, even incremental increases in AI-relevant training may be beneficial, and the sooner these challenges are tackled, the sooner the primary care workforce and those served by it will begin to reap the benefits.</description><subject>Analysis</subject><subject>Artificial Intelligence</subject><subject>Clinical competence</subject><subject>Clinical Decision-Making</subject><subject>Communication</subject><subject>Humans</subject><subject>Medical personnel</subject><subject>Primary Health Care</subject><subject>Special Reports</subject><subject>Technology</subject><subject>Technology application</subject><subject>Training</subject><issn>1544-1709</issn><issn>1544-1717</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNptkktrGzEUhUVpaFK30F9QBIXSzTh6zWhmUzBDH4FAsmjWQqO5slVmJFeSA_33lbFrYjBaSEjfPVfnchD6QMmScklutZ2XrG3lK3RDayEqKql8fTqT7hq9Tek3IYwyzt6ga94IwYmkN6jvw7yFDN44SNiGiPMG8FMCHCxexeysM05P-M5nmCa3LiBg5_FjdLOOf3GvI7xDV1ZPCd4f9wV6-v7tV_-zun_4cdev7itTkzZXdBRA-AiyGwY9DNCZ2hKhLZXMEKAdiLHrTEMsawaQvLbUENsKq1mtjaaGL9DXg-52N8wwGvA56kltD19RQTt1_uLdRq3Ds-okqUlxvEBfjgIx_NlBymp2yRRf2kPYJcWkYE3dtp0s6KcDutYTKOdtKIpmj6uV5IR2bUNpoaoLVBkSlPbBg3Xl-oxfXuDLGmF25mLB5xcFG9BT3qQw7bILPp2DR2smhpQi2NNYKFH7jKiSEbXPSEE_vhzjCfwfCv4PCey1mw</recordid><startdate>20221101</startdate><enddate>20221101</enddate><creator>Liaw, Winston</creator><creator>Kueper, Jacqueline K</creator><creator>Lin, Steven</creator><creator>Bazemore, Andrew</creator><creator>Kakadiaris, Ioannis</creator><general>Annals of Family Medicine</general><general>American Academy of Family Physicians</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20221101</creationdate><title>Competencies for the Use of Artificial Intelligence in Primary Care</title><author>Liaw, Winston ; Kueper, Jacqueline K ; Lin, Steven ; Bazemore, Andrew ; Kakadiaris, Ioannis</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c508t-1d4e03de79bbabbe9c5f04af172c0e19e4d99c60f26be735f1c0f84fa25aca1c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Analysis</topic><topic>Artificial Intelligence</topic><topic>Clinical competence</topic><topic>Clinical Decision-Making</topic><topic>Communication</topic><topic>Humans</topic><topic>Medical personnel</topic><topic>Primary Health Care</topic><topic>Special Reports</topic><topic>Technology</topic><topic>Technology application</topic><topic>Training</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liaw, Winston</creatorcontrib><creatorcontrib>Kueper, Jacqueline K</creatorcontrib><creatorcontrib>Lin, Steven</creatorcontrib><creatorcontrib>Bazemore, Andrew</creatorcontrib><creatorcontrib>Kakadiaris, Ioannis</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Annals of family medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liaw, Winston</au><au>Kueper, Jacqueline K</au><au>Lin, Steven</au><au>Bazemore, Andrew</au><au>Kakadiaris, Ioannis</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Competencies for the Use of Artificial Intelligence in Primary Care</atitle><jtitle>Annals of family medicine</jtitle><addtitle>Ann Fam Med</addtitle><date>2022-11-01</date><risdate>2022</risdate><volume>20</volume><issue>6</issue><spage>559</spage><epage>563</epage><pages>559-563</pages><issn>1544-1709</issn><eissn>1544-1717</eissn><abstract>The artificial intelligence (AI) revolution has arrived for the health care sector and is finally penetrating the far-reaching but perpetually underfinanced primary care platform. 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To facilitate this training, we propose 6 domains of competency for the effective deployment of AI-based tools in primary care: (1) foundational knowledge (what is this tool?), (2) critical appraisal (should I use this tool?), (3) medical decision making (when should I use this tool?), (4) technical use (how do I use this tool?), (5) patient communication (how should I communicate with patients regarding the use of this tool?), and (6) awareness of unintended consequences (what are the "side effects" of this tool?). Integrating these competencies will not be straightforward because of the breadth of knowledge already incorporated into family medicine training and the constantly changing technological landscape. 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subjects | Analysis Artificial Intelligence Clinical competence Clinical Decision-Making Communication Humans Medical personnel Primary Health Care Special Reports Technology Technology application Training |
title | Competencies for the Use of Artificial Intelligence in Primary Care |
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