Caveats for the use of operational electronic health record data in comparative effectiveness research.
William R. Hersh,Mark G. Weiner,Peter J. Embi,Judith R. Logan,Philip R. O. Payne,Elmer V. Bernstam,Harold P Lehmann,George Hripcsak,Timothy H. Hartzog,James J. Cimino,Joel H. Saltz +10 more
TLDR
A list of caveats is developed to inform would-be users of such data as well as provide an informatics roadmap that aims to insure this opportunity to augment comparative effectiveness research can be best leveraged.Abstract:
The growing amount of data in operational electronic health record systems provides unprecedented opportunity for its reuse for many tasks, including comparative effectiveness research. However, there are many caveats to the use of such data. Electronic health record data from clinical settings may be inaccurate, incomplete, transformed in ways that undermine their meaning, unrecoverable for research, of unknown provenance, of insufficient granularity, and incompatible with research protocols. However, the quantity and real-world nature of these data provide impetus for their use, and we develop a list of caveats to inform would-be users of such data as well as provide an informatics roadmap that aims to insure this opportunity to augment comparative effectiveness research can be best leveraged.read more
Citations
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Key challenges for delivering clinical impact with artificial intelligence.
TL;DR: The safe and timely translation of AI research into clinically validated and appropriately regulated systems that can benefit everyone is challenging, and robust clinical evaluation, using metrics that are intuitive to clinicians and ideally go beyond measures of technical accuracy, is essential.
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Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review
TL;DR: Electronic health records are an increasingly common data source for clinical risk prediction, presenting both unique analytic opportunities and challenges, and there is room for improvement in designing studies using EHR data.
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Launching PCORnet, a national patient-centered clinical research network
Rachael L. Fleurence,Lesley H. Curtis,Robert M. Califf,Richard Platt,Joe V. Selby,Jeffrey S. Brown +5 more
TL;DR: The Patient-Centered Outcomes Research Institute has launched PCORnet, a major initiative to support an effective, sustainable national research infrastructure that will advance the use of electronic health data in comparative effectiveness research (CER) and other types of research.
Journal ArticleDOI
Electronic health records to facilitate clinical research.
Martin R. Cowie,Juuso I. Blomster,Juuso I. Blomster,Lesley H. Curtis,Sylvie Duclaux,Ian Ford,Fleur Fritz,Samantha Goldman,Salim Janmohamed,Jörg Kreuzer,Mark Leenay,Alexander Michel,Seleen Ong,Jill P. Pell,Mary Ross Southworth,Wendy Gattis Stough,Martin Thoenes,Faiez Zannad,Faiez Zannad,Andrew Zalewski +19 more
TL;DR: This manuscript identifies the key steps required to advance the role of electronic health records in cardiovascular clinical research and highlights the importance of collaboration between academia, industry, regulatory bodies, policy makers, patients, and electronic health record vendors.
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Automated machine learning: Review of the state-of-the-art and opportunities for healthcare.
TL;DR: The existing literature in the field of automated machine learning (AutoML) is reviewed to help healthcare professionals better utilize machine learning models "off-the-shelf" with limited data science expertise to help there to be widespread adoption of AutoML in healthcare.
References
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