Healthcare Professionals’ Expectations of Medical Artificial Intelligence and Strategies for its Clinical Implementation: A Qualitative Study
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Objectives: Although medical artificial intelligence (AI) systems that assist healthcare professionals in critical care settingsare expected to improve healthcare, skepticism exists regarding whether their potential has been fully actualized. Therefore,we aimed to conduct a qualitative study with physicians and nurses to understand their needs, expectations, and concerns regardingmedical AI; explore their expected responses to recommendations by medical AI that contradicted their judgments;and derive strategies to implement medical AI in practice successfully. Methods: Semi-structured interviews were conductedwith 15 healthcare professionals working in the emergency room and intensive care unit in a tertiary teaching hospital inSeoul. The data were interpreted using summative content analysis. In total, 26 medical AI topics were extracted from the interviews. Eight were related to treatment recommendation, seven were related to diagnosis prediction, and seven were relatedto process improvement. Results: While the participants expressed expectations that medical AI could enhance their patients’outcomes, increase work efficiency, and reduce hospital operating costs, they also mentioned concerns regarding distortionsin the workflow, deskilling, alert fatigue, and unsophisticated algorithms. If medical AI decisions contradicted theirjudgment, most participants would consult other medical staff and thereafter reconsider their initial judgment. Conclusions:Healthcare professionals wanted to use medical AI in practice and emphasized that artificial intelligence systems should betrustworthy from the standpoint of healthcare professionals. They also highlighted the importance of alert fatigue managementand the integration of AI systems into the workflow.
Abstract
Objectives: Although medical artificial intelligence (AI) systems that assist healthcare professionals in critical care settingsare expected to improve healthcare, skepticism exists regarding whether their potential has been fully actualized. Therefore,we aimed to conduct a qualitative study with physicians and nurses to understand their needs, expectations, and concerns regardingmedical AI; explore their expected responses to recommendations by medical AI that contradicted their judgments;and derive strategies to implement medical AI in practice successfully. Methods: Semi-structured interviews were conductedwith 15 healthcare professionals working in the emergency room and intensive care unit in a tertiary teaching hospital inSeoul. The data were interpreted using summative content analysis. In total, 26 medical AI topics were extracted from the interviews. Eight were related to treatment recommendation, seven were related to diagnosis prediction, and seven were relatedto process improvement. Results: While the participants expressed expectations that medical AI could enhance their patients’outcomes, increase work efficiency, and reduce hospital operating costs, they also mentioned concerns regarding distortionsin the workflow, deskilling, alert fatigue, and unsophisticated algorithms. If medical AI decisions contradicted theirjudgment, most participants would consult other medical staff and thereafter reconsider their initial judgment. Conclusions:Healthcare professionals wanted to use medical AI in practice and emphasized that artificial intelligence systems should betrustworthy from the standpoint of healthcare professionals. They also highlighted the importance of alert fatigue managementand the integration of AI systems into the workflow.
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