ArticleJournal of the American Medical Informatics Association : JAMIA2013
Comparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records.
Article in Journal of the American Medical Informatics Association : JAMIA, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Comparison of Active Pharmacovigilance Strategies Used to Monitor Adverse Events to Antiviral Agents: A Systematic Review.Drug safety · 2024Pooled it
- A real-world disproportionality analysis of FDA adverse event reporting system (FAERS) events for lecanemab.Frontiers in pharmacology · 2025Article
- Disproportionality analysis of satralizumab in FDA adverse event reporting system and Japanese adverse drug event report: a pharmacovigilance study.Frontiers in immunology · 2025Article
- Valproate sodium-associated acute pancreatitis: a case report and systematic analysis of antiepileptic drug adverse events in FAERS.American journal of translational research · 2025Article
- Precision Adverse Drug Reactions Prediction with Heterogeneous Graph Neural Network.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Exploring Health Informatics in the Battle against Drug Addiction: Digital Solutions for the Rising Concern.Journal of personalized medicine · 2024Review
- Adverse event reporting of the IGF-1R monoclonal antibody teprotumumab: a real-world study based on the US food and drug administration adverse event reporting system.Frontiers in pharmacology · 2024Article
- Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review.Drug safety · 2023Article
- Enhancing antidepressant safety surveillance: comparative analysis of adverse drug reaction signals in spontaneous reporting and healthcare claims databases.Frontiers in pharmacology · 2023Article
- A Data-Driven Reference Standard for Adverse Drug Reaction (RS-ADR) Signal Assessment: Development and Validation.Journal of medical Internet research · 2022Article
- Artificial Intelligence-Based Pharmacovigilance in the Setting of Limited Resources.Drug safety · 2022Review
- A statistical quality assessment method for longitudinal observations in electronic health record data with an application to the VA million veteran program.BMC medical informatics and decision making · 2021Article
- SGLT-2 inhibitors and atrial fibrillation in the Food and Drug Administration adverse event reporting system.Cardiovascular diabetology · 2021Article
- Active Pharmacovigilance of Drug-Induced Liver Injury Using Electronic Health Records.Allergy, asthma & immunology research · 2020Article
- The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities.Statistics in medicine · 2020Article
- Development of a Controlled Vocabulary-Based Adverse Drug Reaction Signal Dictionary for Multicenter Electronic Health Record-Based Pharmacovigilance.Drug safety · 2019Article
- PregOMICS-Leveraging systems biology and bioinformatics for drug repurposing in maternal-child health.American journal of reproductive immunology (New York, N.Y. : 1989) · 2018Article
- Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning.JMIR public health and surveillance · 2018Article
- An MCEM Framework for Drug Safety Signal Detection and Combination from Heterogeneous Real World Evidence.Scientific reports · 2018Article
- Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
objectiveMedication safety requires that each drug be monitored throughout its market life as early detection of adverse drug reactions (ADRs) can lead to alerts that prevent patient harm. Recently, electronic medical records (EMRs) have emerged as a valuable resource for pharmacovigilance. This study examines the use of retrospective medication orders and inpatient laboratory results documented in the EMR to identify ADRs.
methodsUsing 12 years of EMR data from Vanderbilt University Medical Center (VUMC), we designed a study to correlate abnormal laboratory results with specific drug administrations by comparing the outcomes of a drug-exposed group and a matched unexposed group. We assessed the relative merits of six pharmacovigilance measures used in spontaneous reporting systems (SRSs): proportional reporting ratio (PRR), reporting OR (ROR), Yule's Q (YULE), the χ(2) test (CHI), Bayesian confidence propagation neural networks (BCPNN), and a gamma Poisson shrinker (GPS).
resultsWe systematically evaluated the methods on two independently constructed reference standard datasets of drug-event pairs. The dataset of Yoon et al contained 470 drug-event pairs (10 drugs and 47 laboratory abnormalities). Using VUMC's EMR, we created another dataset of 378 drug-event pairs (nine drugs and 42 laboratory abnormalities). Evaluation on our reference standard showed that CHI, ROR, PRR, and YULE all had the same F score (62%). When the reference standard of Yoon et al was used, ROR had the best F score of 68%, with 77% precision and 61% recall.
conclusionsResults suggest that EMR-derived laboratory measurements and medication orders can help to validate previously reported ADRs, and detect new ADRs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.