Yoo Junsang, Hur Sujeong, Hwang Wonil, Cha Won Chul
Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Korea.
AVOMD Inc, Seoul, Korea.
Healthc Inform Res. 2023 Jan;29(1):64-74. doi: 10.4258/hir.2023.29.1.64. Epub 2023 Jan 31.
Although medical artificial intelligence (AI) systems that assist healthcare professionals in critical care settings are 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 regarding medical AI; explore their expected responses to recommendations by medical AI that contradicted their judgments; and derive strategies to implement medical AI in practice successfully.
Semi-structured interviews were conducted with 15 healthcare professionals working in the emergency room and intensive care unit in a tertiary teaching hospital in Seoul. 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 related to process improvement.
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 distortions in the workflow, deskilling, alert fatigue, and unsophisticated algorithms. If medical AI decisions contradicted their judgment, most participants would consult other medical staff and thereafter reconsider their initial judgment.
Healthcare professionals wanted to use medical AI in practice and emphasized that artificial intelligence systems should be trustworthy from the standpoint of healthcare professionals. They also highlighted the importance of alert fatigue management and the integration of AI systems into the workflow.
尽管人们期望在重症监护环境中协助医疗保健专业人员的医学人工智能（AI）系统能改善医疗保健状况，但对于其潜力是否已得到充分发挥仍存在怀疑态度。因此，我们旨在对医生和护士进行定性研究，以了解他们对医学人工智能的需求、期望和担忧；探讨他们对与自己判断相矛盾的医学人工智能建议的预期反应；并得出在实践中成功实施医学人工智能的策略。
对首尔一家三级教学医院急诊室和重症监护室的15名医疗保健专业人员进行了半结构化访谈。使用总结性内容分析法对数据进行解读。总共从访谈中提取了26个医学人工智能主题。其中8个与治疗建议相关，7个与诊断预测相关，7个与流程改进相关。
虽然参与者表示期望医学人工智能能改善患者的治疗效果、提高工作效率并降低医院运营成本，但他们也提到了对工作流程扭曲、技能退化、警报疲劳和算法不够完善的担忧。如果医学人工智能的决策与他们的判断相矛盾，大多数参与者会咨询其他医务人员，然后重新考虑他们最初的判断。
医疗保健专业人员希望在实践中使用医学人工智能，并强调从医疗保健专业人员的角度来看，人工智能系统应该是值得信赖的。他们还强调了警报疲劳管理以及将人工智能系统整合到工作流程中的重要性。
