Abstract:
:Structured Product Labels follow an XML-based document markup standard approved by the Health Level Seven organization and adopted by the US Food and Drug Administration as a mechanism for exchanging medical products information. Their current organization makes their secondary use rather challenging. We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81 percent and 92 percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record's ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.
journal_name
Health Informatics Jjournal_title
Health informatics journalauthors
Pandey A,Kreimeyer K,Foster M,Dang O,Ly T,Wang W,Forshee R,Botsis Tdoi
10.1177/1460458217749883subject
Has Abstractpub_date
2019-12-01 00:00:00pages
1232-1243issue
4eissn
1460-4582issn
1741-2811journal_volume
25pub_type
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