Future medical artificial intelligence application requirements and expectations of physicians in German university hospitals: Web-based survey

BACKGROUND: The increasing development of artificial intelligence (AI) systems in medicine driven by researchers and entrepreneurs goes along with enormous expectations for medical care advancement. AI might change the clinical practice of physicians from almost all medical disciplines and in most areas of health care. While expectations for AI in medicine are high, practical implementations of AI for clinical practice are still scarce in Germany. Moreover, physicians’ requirements and expectations of AI in medicine and their opinion on the usage of anonymized patient data for clinical and biomedical research have not been investigated widely in German university hospitals. OBJECTIVE: This study aimed to evaluate physicians’ requirements and expectations of AI in medicine and their opinion on the secondary usage of patient data for (bio)medical research (eg, for the development of machine learning algorithms) in university hospitals in Germany. METHODS: A web-based survey was conducted addressing physicians of all medical disciplines in 8 German university hospitals. Answers were given using Likert scales and general demographic responses. Physicians were asked to participate locally via email in the respective hospitals. RESULTS: The online survey was completed by 303 physicians (female: 121/303, 39.9%; male: 173/303, 57.1%; no response: 9/303, 3.0%) from a wide range of medical disciplines and work experience levels. Most respondents either had a positive (130/303, 42.9%) or a very positive attitude (82/303, 27.1%) towards AI in medicine. There was a significant association between the personal rating of AI in medicine and the self-reported technical affinity level (H4=48.3, P<.001 a vast majority of physicians expected the future medicine to be mix human and artificial intelligence but also requested scientific evaluation before routine implementation ai-based systems were most optimistic that ai applications would identify drug interactions improve patient care substantially quite reserved regarding ai-supported diagnosis psychiatric diseases respondents agreed there should open access anonymized databases for medical biomedical research. in stationary german university hospitals show generally positive attitude towards using medicine. along with this optimism comes several expectations hopes will assist clinical decision making. especially fields where huge amounts data are processed imaging procedures radiology pathology or collected continuously cardiology intensive high. study greatest potential was seen application identification assumedly due rising complexity administration polymorbid polypharmacy patients. however practical usage health regulatory organizational challenges still have mastered. conclusions:=""></.001>