"Nothing works without the doctor:" Physicians' perception of clinical decision-making and artificial intelligence

被引:6
|
作者
Samhammer, David [1 ]
Roller, Roland [2 ,3 ,4 ,5 ,6 ]
Hummel, Patrik [7 ]
Osmanodja, Bilgin [3 ,4 ,5 ,6 ]
Burchardt, Aljoscha [2 ]
Mayrdorfer, Manuel [3 ,4 ,5 ,6 ,8 ]
Duettmann, Wiebke [3 ,4 ,5 ,6 ]
Dabrock, Peter [1 ]
机构
[1] Friedrich Alexander Univ Erlangen Nurnberg FAU, Inst Systemat Theol Ethics 2, Erlangen, Germany
[2] German Res Ctr Artificial Intelligence DFKI, Berlin, Germany
[3] Charite Univ Med Berlin, Dept Nephrol & Med Intens Care, Berlin, Germany
[4] Humboldt Univ, Berlin, Germany
[5] Free Univ Berlin, Berlin, Germany
[6] Berlin Inst Hlth, Berlin, Germany
[7] TU Eindhoven, Dept Ind Engn & Innovat Sci, Philosophy & Eth Grp, Eindhoven, Netherlands
[8] Berlin Inst Hlth, Dept Internal Med 3, Div Nephrol & Dialysis, Berlin, Germany
基金
欧盟地平线“2020”;
关键词
artificial intelligence; physician; decision support; health; qualitative content analysis; SUPPORT; CARE;
D O I
10.3389/fmed.2022.1016366
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
IntroductionArtificial intelligence-driven decision support systems (AI-DSS) have the potential to help physicians analyze data and facilitate the search for a correct diagnosis or suitable intervention. The potential of such systems is often emphasized. However, implementation in clinical practice deserves continuous attention. This article aims to shed light on the needs and challenges arising from the use of AI-DSS from physicians' perspectives. MethodsThe basis for this study is a qualitative content analysis of expert interviews with experienced nephrologists after testing an AI-DSS in a straightforward usage scenario. ResultsThe results provide insights on the basics of clinical decision-making, expected challenges when using AI-DSS as well as a reflection on the test run. DiscussionWhile we can confirm the somewhat expectable demand for better explainability and control, other insights highlight the need to uphold classical strengths of the medical profession when using AI-DSS as well as the importance of broadening the view of AI-related challenges to the clinical environment, especially during treatment. Our results stress the necessity for adjusting AI-DSS to shared decision-making. We conclude that explainability must be context-specific while fostering meaningful interaction with the systems available.
引用
收藏
页数:12
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