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@ARTICLE{Maassen:893858,
author = {Maassen, Oliver and Fritsch, Sebastian and Palm, Julia and
Deffge, Saskia and Kunze, Julian and Marx, Gernot and
Riedel, Morris and Schuppert, Andreas and Bickenbach,
Johannes},
title = {{F}uture {M}edical {A}rtificial {I}ntelligence
{A}pplication {R}equirements and {E}xpectations of
{P}hysicians in {G}erman {U}niversity {H}ospitals:
{W}eb-{B}ased {S}urvey},
journal = {Journal of medical internet research},
volume = {23},
number = {3},
issn = {1438-8871},
address = {Richmond, Va.},
publisher = {Healthcare World},
reportid = {FZJ-2021-02882},
pages = {e26646 -},
year = {2021},
abstract = {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 of medicine to be a mix of
human and artificial intelligence (273/303, $90.1\%)$ but
also requested a scientific evaluation before the routine
implementation of AI-based systems (276/303, $91.1\%).$
Physicians were most optimistic that AI applications would
identify drug interactions (280/303, $92.4\%)$ to improve
patient care substantially but were quite reserved regarding
AI-supported diagnosis of psychiatric diseases (62/303,
$20.5\%).$ Of the respondents, $82.5\%$ (250/303) agreed
that there should be open access to anonymized patient
databases for medical and biomedical research.Conclusions:
Physicians in stationary patient care in German university
hospitals show a generally positive attitude towards using
most AI applications in medicine. Along with this optimism
comes several expectations and hopes that AI will assist
physicians in clinical decision making. Especially in fields
of medicine where huge amounts of data are processed (eg,
imaging procedures in radiology and pathology) or data are
collected continuously (eg, cardiology and intensive care
medicine), physicians’ expectations of AI to substantially
improve future patient care are high. In the study, the
greatest potential was seen in the application of AI for the
identification of drug interactions, assumedly due to the
rising complexity of drug administration to polymorbid,
polypharmacy patients. However, for the practical usage of
AI in health care, regulatory and organizational challenges
still have to be mastered.},
cin = {JSC},
ddc = {610},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / SMITH -
Medizininformatik-Konsortium (BMBF-01ZZ1803K)},
pid = {G:(DE-HGF)POF4-5112 / G:(DE-82)BMBF-01ZZ1803K},
typ = {PUB:(DE-HGF)16},
pubmed = {33666563},
UT = {WOS:000625869900002},
doi = {10.2196/26646},
url = {https://juser.fz-juelich.de/record/893858},
}