Artificial Intelligence for Health Professions Educators

Lomis, Kimberly D.; Jeffries, Pamela R.; Palatta, Anthony; Sage, Melanie; Sheikh, Javaid I.; Sheperis, Carl J.; Whelan, Alison

doi:10.31478/202109a

Cited by 49 publications

(59 citation statements)

References 37 publications

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“…The implementation of AI-based tools in health care has given rise to a variety of practical and ethical concerns, including bias in tool development and justice in the distribution of subsequent health improvements. [4][5][6][7] As adoption increases, clinicians will encounter both beneficial and harmful effects of these tools and will therefore need to acquire baseline competencies for practicing effectively, efficiently, safely, and equitably in AI-influenced health care environments. However, the nature of such competencies has not yet been articulated.…”

Section: Discussionmentioning

confidence: 99%

Competencies for the Use of Artificial Intelligence–Based Tools by Health Care Professionals

et al. 2022

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Purpose The expanded use of clinical tools that incorporate artificial intelligence (AI) methods has generated calls for specific competencies for effective and ethical use. This qualitative study used expert interviews to define AI-related clinical competencies for health care professionals. Method In 2021, a multidisciplinary team interviewed 15 experts in the use of AI-based tools in health care settings about the clinical competencies health care professionals need to work effectively with such tools. Transcripts of the semistructured interviews were coded and thematically analyzed. Draft competency statements were developed and provided to the experts for feedback. The competencies were finalized using a consensus process across the research team. Results Six competency domain statements and 25 subcompetencies were formulated from the thematic analysis. The competency domain statements are: (1) basic knowledge of AI: explain what AI is and describe its health care applications; (2) social and ethical implications of AI: explain how social, economic, and political systems influence AI-based tools and how these relationships impact justice, equity, and ethics; (3) AI-enhanced clinical encounters: carry out AI-enhanced clinical encounters that integrate diverse sources of information in creating patient-centered care plans; (4) evidence-based evaluation of AI-based tools: evaluate the quality, accuracy, safety, contextual appropriateness, and biases of AI-based tools and their underlying data sets in providing care to patients and populations; (5) workflow analysis for AI-based tools: analyze and adapt to changes in teams, roles, responsibilities, and workflows resulting from implementation of AI-based tools; and (6) practice-based learning and improvement regarding AI-based tools: participate in continuing professional development and practice-based improvement activities related to use of AI tools in health care. Conclusions The 6 clinical competencies identified can be used to guide future teaching and learning programs to maximize the potential benefits of AI-based tools and diminish potential harms.

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Section: Discussionmentioning

confidence: 99%

Competencies for the Use of Artificial Intelligence–Based Tools by Health Care Professionals

et al. 2022

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“…Afterwards, the utilization of AI will not be restricted to health care coverage but will likewise be applied to other business areas. "By doing everything, organizations can diminish costs for paying made-up claims and work on cost proficiency, with the goal that the organization's business environment can stay steady and helpful (Lomis et al, 2021).…”

Section: Leverage Ai To Prevent Fraudmentioning

confidence: 99%

Legal status of artificial intelligence-based health insurance services

Riyanti

2022

ijhs

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This study examines various sources of publications to complement the discussion of legal literacy studies on applying artificial intelligence based on health insurance and public services regarding challenges and opportunities in consumer protection. Several studies have been published on artificial intelligence; some even have one regarding health, but the legal status has not been found in consumer protection for technology-based insurance. On that basis, the existence of this research. We obtained data from several electronic searches and analyzed them to answer the research problem. Our approach is that we first analyze the data with an understanding of the questions, then search the data electronically and then review it; it involves a system of data coding, interpretation, and in-depth evaluation. Finally, based on the discussion of the results, it can be concluded that the use of intelligence applications in terms of public services in health insurance is something that helps the implementation of health insurance, which includes very transparent data, where the algorithm has been designed in such a way.

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“… 4 Only recently has it been proposed that AI concepts be included in medical education curricula. 5 , 6 Most suggestions to date have framed training in AI as an added layer to current medical school curricula, hereafter referred to as undergraduate medical education (UME). Recommendations for incorporating AI into UME range widely, covering the gamut from teaching medical students how to code to EHR usage and the ethics surrounding the adoption of AI.…”

Section: Main Textmentioning

confidence: 99%