Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.
Who will be affected?
Readers: No access to all 28 journals. We recommend accessing our articles via PubMed Central
Authors: No access to the submission form or your user account.
Reviewers: No access to your user account. Please download manuscripts you are reviewing for offline reading before Wednesday, July 01, 2020 at 7:00 PM.
Editors: No access to your user account to assign reviewers or make decisions.
Copyeditors: No access to user account. Please download manuscripts you are copyediting before Wednesday, July 01, 2020 at 7:00 PM.
Cresswell K, De Keizer NF, Magrabi F, Williams R, Rigby M, Prgomet M, Kukhareva P, Wong ZSY, Scott P, Craven CK, Georgiou A, Medlock S, Brender J, Ammenwerth E
Evaluating Artificial Intelligence in Clinical Settings—Let Us Not Reinvent the Wheel
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Evaluating Artificial Intelligence in clinical settings - let's not reinvent the wheel
Kathrin Cresswell;
Nicolette F De Keizer;
Farah Magrabi;
Robin Williams;
Michael Rigby;
Mirela Prgomet;
Polina Kukhareva;
Zoie Shui-Yee Wong;
Philip Scott;
Catherine K Craven;
Andrew Georgiou;
Stephanie Medlock;
Jytte Brender;
Elske Ammenwerth
ABSTRACT
There is an urgent need to incorporate theory-informed health information technology evaluation frameworks into existing and emerging guidelines for the evaluation of Artificial Intelligence. Such frameworks can help developers, implementers, and strategic decision makers to build on existing experience and the existing empirical evidence base.
We here provide concrete examples on how existing theory-informed health information technology evaluation frameworks may be used to inform the safe implementation of AI in healthcare settings considering technology, design, use by health and care professionals and organisations, and implementation strategy within and across organisations over time.
Citation
Please cite as:
Cresswell K, De Keizer NF, Magrabi F, Williams R, Rigby M, Prgomet M, Kukhareva P, Wong ZSY, Scott P, Craven CK, Georgiou A, Medlock S, Brender J, Ammenwerth E
Evaluating Artificial Intelligence in Clinical Settings—Let Us Not Reinvent the Wheel