Literature DB >> 24454585

Lessons learned from developing a drug evidence base to support pharmacovigilance.

J C Smith1, J C Denny, Q Chen, H Nian2, A Spickard, S T Rosenbloom, R A Miller.   

Abstract

OBJECTIVE: 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.

Entities:  

Keywords:  Drug therapy; adverse effects; drug product labeling; knowledge bases; unified medical language system

Mesh:

Year:  2013        PMID: 24454585      PMCID: PMC3885918          DOI: 10.4338/ACI-2013-08-RA-0062

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


  28 in total

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Authors:  Joshua C Denny; Jeffrey D Smithers; Randolph A Miller; Anderson Spickard
Journal:  J Am Med Inform Assoc       Date:  2003-03-28       Impact factor: 4.497

2.  Clinical decision support and electronic prescribing systems: a time for responsible thought and action.

Authors:  Randolph A Miller; Reed M Gardner; Kevin B Johnson; George Hripcsak
Journal:  J Am Med Inform Assoc       Date:  2005-05-19       Impact factor: 4.497

3.  Extracting drug-drug interaction articles from MEDLINE to improve the content of drug databases.

Authors:  Stephany Duda; Constantin Aliferis; Randolph Miller; Alexander Statnikov; Kevin Johnson
Journal:  AMIA Annu Symp Proc       Date:  2005

4.  Assessing the impact of HL7/FDA Structured Product Label (SPL) content for medication knowledge management.

Authors:  Gunther Schadow
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

5.  Active computerized pharmacovigilance using natural language processing, statistics, and electronic health records: a feasibility study.

Authors:  Xiaoyan Wang; George Hripcsak; Marianthi Markatou; Carol Friedman
Journal:  J Am Med Inform Assoc       Date:  2009-03-04       Impact factor: 4.497

6.  Identifying QT prolongation from ECG impressions using a general-purpose Natural Language Processor.

Authors:  Joshua C Denny; Randolph A Miller; Lemuel Russell Waitman; Mark A Arrieta; Joshua F Peterson
Journal:  Int J Med Inform       Date:  2008-10-19       Impact factor: 4.046

7.  UMLS-Query: a perl module for querying the UMLS.

Authors:  Nigam H Shah; Nigam Shah; Mark A Muse; Mark Musen
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

8.  A framework for characterizing drug information sources.

Authors:  Mark Sharp; Olivier Bodenreider; Nina Wacholder
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

9.  Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study.

Authors:  Elizabeth S Chen; George Hripcsak; Hua Xu; Marianthi Markatou; Carol Friedman
Journal:  J Am Med Inform Assoc       Date:  2007-10-18       Impact factor: 4.497

10.  Development and evaluation of an ensemble resource linking medications to their indications.

Authors:  Wei-Qi Wei; Robert M Cronin; Hua Xu; Thomas A Lasko; Lisa Bastarache; Joshua C Denny
Journal:  J Am Med Inform Assoc       Date:  2013-04-10       Impact factor: 4.497

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Journal:  Drug Saf       Date:  2014-10       Impact factor: 5.606

2.  An updated, computable MEDication-Indication resource for biomedical research.

Authors:  Neil S Zheng; V Eric Kerchberger; Victor A Borza; H Nur Eken; Joshua C Smith; Wei-Qi Wei
Journal:  Sci Rep       Date:  2021-09-23       Impact factor: 4.996

3.  Evaluation of a Novel System to Enhance Clinicians' Recognition of Preadmission Adverse Drug Reactions.

Authors:  Joshua C Smith; Qingxia Chen; Joshua C Denny; Dan M Roden; Kevin B Johnson; Randolph A Miller
Journal:  Appl Clin Inform       Date:  2018-05-09       Impact factor: 2.342

4.  Trans-ethnic association study of blood pressure determinants in over 750,000 individuals.

Authors:  Ayush Giri; Jacklyn N Hellwege; Jacob M Keaton; Jihwan Park; Chengxiang Qiu; Helen R Warren; Eric S Torstenson; Csaba P Kovesdy; Yan V Sun; Otis D Wilson; Cassianne Robinson-Cohen; Christianne L Roumie; Cecilia P Chung; Kelly A Birdwell; Scott M Damrauer; Scott L DuVall; Derek Klarin; Kelly Cho; Yu Wang; Evangelos Evangelou; Claudia P Cabrera; Louise V Wain; Rojesh Shrestha; Brian S Mautz; Elvis A Akwo; Muralidharan Sargurupremraj; Stéphanie Debette; Michael Boehnke; Laura J Scott; Jian'an Luan; Jing-Hua Zhao; Sara M Willems; Sébastien Thériault; Nabi Shah; Christopher Oldmeadow; Peter Almgren; Ruifang Li-Gao; Niek Verweij; Thibaud S Boutin; Massimo Mangino; Ioanna Ntalla; Elena Feofanova; Praveen Surendran; James P Cook; Savita Karthikeyan; Najim Lahrouchi; Chunyu Liu; Nuno Sepúlveda; Tom G Richardson; Aldi Kraja; Philippe Amouyel; Martin Farrall; Neil R Poulter; Markku Laakso; Eleftheria Zeggini; Peter Sever; Robert A Scott; Claudia Langenberg; Nicholas J Wareham; David Conen; Colin Neil Alexander Palmer; John Attia; Daniel I Chasman; Paul M Ridker; Olle Melander; Dennis Owen Mook-Kanamori; Pim van der Harst; Francesco Cucca; David Schlessinger; Caroline Hayward; Tim D Spector; Marjo-Riitta Jarvelin; Branwen J Hennig; Nicholas J Timpson; Wei-Qi Wei; Joshua C Smith; Yaomin Xu; Michael E Matheny; Edward E Siew; Cecilia Lindgren; Karl-Heinz Herzig; George Dedoussis; Joshua C Denny; Bruce M Psaty; Joanna M M Howson; Patricia B Munroe; Christopher Newton-Cheh; Mark J Caulfield; Paul Elliott; J Michael Gaziano; John Concato; Peter W F Wilson; Philip S Tsao; Digna R Velez Edwards; Katalin Susztak; Christopher J O'Donnell; Adriana M Hung; Todd L Edwards
Journal:  Nat Genet       Date:  2018-12-21       Impact factor: 38.330

  4 in total

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