Appl Clin Inform 2013; 04(04): 596-617
DOI: 10.4338/ACI-2013-08-RA-0062
Research Article
Schattauer GmbH

Lessons Learned from Developing a Drug Evidence Base to Support Pharmacovigilance

J.C. Smith
1  Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
,
J.C. Denny
1  Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
2  Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
,
Q. Chen
1  Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
3  Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
,
H. Nian
3  Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
,
A. Spickard III
1  Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
2  Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
,
S. T. Rosenbloom
1  Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
2  Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
4  School of Nursing, Vanderbilt University, Nashville, Tennessee, USA
5  Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
,
R. A. Miller
1  Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
2  Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
4  School of Nursing, Vanderbilt University, Nashville, Tennessee, USA
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Publikationsverlauf

Received: 23. August 2013

Accepted: 06. November 2013

Publikationsdatum:
19. Dezember 2017 (online)

Summary

Objectives: This work identified challenges associated with extraction and representation of medication-related information from publicly available electronic sources.

Methods: We gained direct observational experience through creating and evaluating the Drug Evidence Base (DEB), a repository of drug indications and adverse effects (ADEs), and supplemented this through literature review. We extracted DEB content from the National Drug File Reference Terminology, from aggregated MEDLINE co-occurrence data, and from the National Library of Medicine’s DailyMed. To understand better the similarities, differences and problems with the content of DEB and the SIDER Side Effect Resource, and Vanderbilt’s MEDI Indication Resource, we carried out statistical evaluations and human expert reviews.

Results: While DEB, SIDER, and MEDI often agreed on medication indications and side effects, cross-system shortcomings limit their current utility. The drug information resources we evaluated frequently employed multiple, disparate vaguely related UMLS concepts to represent a single specific clinical drug indication or adverse effect. Thus, evaluations comparing drug-indication and drug-ADE coverage for such resources will encounter substantial numbers of false negative and false positive matches. Furthermore, our review found that many indication and ADE relationships are too complex – logically and temporally – to represent within existing systems.

Conclusion: To enhance applicability and utility, future drug information systems deriving indications and ADEs from public resources must represent clinical concepts uniformly and as precisely as possible. Future systems must also better represent the inherent complexity of indications and ADEs.

Citation: Smith JC, Denny JC, Chen Q, Nian H, Spickard III A, Rosenbloom ST, Miller RA. Lessons learned from developing a drug evidence base to support pharmacovigilance. Appl Clin Inf 2013; 4: 596–617

http://dx.doi.org/10.4338/ACI-2013-08-RA-0062