Integrating natural language processing expertise with patient safety event review committees to improve the analysis of medication events

Highlights • NLP models categorized medication related events into pharmacy delays, dispensing errors, Pyxis discrepancies, and prescriber errors. • This study highlights and discusses differences when incorporating brief factual descriptions and resolutions free-texts in NLP models. • We demonstrat...

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Bibliographic Details
Published in:	International journal of medical informatics (Shannon, Ireland) Vol. 104; pp. 120 - 125
Main Authors:	Fong, Allan, Harriott, Nicole, Walters, Donna M, Foley, Hanan, Morrissey, Richard, Ratwani, Raj R
Format:	Journal Article
Language:	English
Published:	Ireland Elsevier B.V 01-08-2017
Subjects:	Advisory Committees Data Interpretation, Statistical Drug-Related Side Effects and Adverse Reactions - prevention & control Humans Internal Medicine Machine learning Medication Medication Errors - prevention & control Natural Language Processing Other Patient Safety Patient safety events Pharmaceutical Preparations Risk Management Visualization Patient safety events Medication Visualization Natural language processing Machine learning
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Summary:	Highlights • NLP models categorized medication related events into pharmacy delays, dispensing errors, Pyxis discrepancies, and prescriber errors. • This study highlights and discusses differences when incorporating brief factual descriptions and resolutions free-texts in NLP models. • We demonstrate the integration of NLP models and discuss the importance of having mechanisms for users to update the models over time.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1386-5056 1872-8243
DOI:	10.1016/j.ijmedinf.2017.05.005