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2015 ; 17
(5
): e110
Nephropedia Template TP
gab.com Text
Twit Text FOAVip
Twit Text #
English Wikipedia
Utilizing the Wikidata system to improve the quality of medical content in
Wikipedia in diverse languages: a pilot study
#MMPMID25944105
Pfundner A
; Schönberg T
; Horn J
; Boyce RD
; Samwald M
J Med Internet Res
2015[May]; 17
(5
): e110
PMID25944105
show ga
BACKGROUND: Wikipedia is an important source of medical information for both
patients and medical professionals. Given its wide reach, improving the quality,
completeness, and accessibility of medical information on Wikipedia could have a
positive impact on global health. OBJECTIVE: We created a prototypical
implementation of an automated system for keeping drug-drug interaction (DDI)
information in Wikipedia up to date with current evidence about clinically
significant drug interactions. Our work is based on Wikidata, a novel,
graph-based database backend of Wikipedia currently in development. METHODS: We
set up an automated process for integrating data from the Office of the National
Coordinator for Health Information Technology (ONC) high priority DDI list into
Wikidata. We set up exemplary implementations demonstrating how the DDI data we
introduced into Wikidata could be displayed in Wikipedia articles in diverse
languages. Finally, we conducted a pilot analysis to explore if adding the ONC
high priority data would substantially enhance the information currently
available on Wikipedia. RESULTS: We derived 1150 unique interactions from the ONC
high priority list. Integration of the potential DDI data from Wikidata into
Wikipedia articles proved to be straightforward and yielded useful results. We
found that even though the majority of current English Wikipedia articles about
pharmaceuticals contained sections detailing contraindications, only a small
fraction of articles explicitly mentioned interaction partners from the ONC high
priority list. For 91.30% (1050/1150) of the interaction pairs we tested, none of
the 2 articles corresponding to the interacting substances explicitly mentioned
the interaction partner. For 7.21% (83/1150) of the pairs, only 1 of the 2
associated Wikipedia articles mentioned the interaction partner; for only 1.48%
(17/1150) of the pairs, both articles contained explicit mentions of the
interaction partner. CONCLUSIONS: Our prototype demonstrated that automated
updating of medical content in Wikipedia through Wikidata is a viable option,
albeit further refinements and community-wide consensus building are required
before integration into public Wikipedia is possible. A long-term endeavor to
improve the medical information in Wikipedia through structured data
representation and automated workflows might lead to a significant improvement of
the quality of medical information in one of the world's most popular Web
resources.