Journal
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
Volume 26, Issue 11, Pages 1379-1384Publisher
OXFORD UNIV PRESS
DOI: 10.1093/jamia/ocz125
Keywords
electronic health records; clinical decision support; knowledge representation; artificial intelligence; learning health system
Categories
Funding
- UASOM Informatics Institute the Center for Clinical and Translational Sciences (CCTS) from the National Center for the Advancement of Translational Science (NCATS) [UL1TR001417]
- EASI-PRO grant from the National Center for the Advancement of Translational Science (NCATS) [U01TR001806]
Ask authors/readers for more resources
Complaints about electronic health records, including information overload, note bloat, and alert fatigue, are frequent topics of discussion. Despite substantial effort by researchers and industry, complaints continue noting serious adverse effects on patient safety and clinician quality of life. I believe solutions are possible if we can add information to the record that explains the why of a patient's care, such as relationships between symptoms, physical findings, diagnostic results, differential diagnoses, therapeutic plans, and goals. While this information may be present in clinical notes, I propose that we modify electronic health records to support explicit representation of this information using formal structure and controlled vocabularies. Such information could foster development of more situation-aware tools for data retrieval and synthesis. Informatics research is needed to understand what should be represented, how to capture it, and how to benefit those providing the information so that their workload is reduced.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available