ArticleJournal of the American Medical Informatics Association : JAMIA2013
Combing signals from spontaneous reports and electronic health records for detection of adverse drug reactions.
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 90 papers, 1 of them a synthesis that pooled it.
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Who cites it
90 citing papers in PubMed, 1 synthesis or guideline pooled it.
- An OMOP-CDM based pharmacovigilance data-processing pipeline (PDP) providing active surveillance for ADR signal detection from real-world data sources.BMC medical informatics and decision making · 2021Pooled it
- Strengthening Signal Detection by Proactive Adverse Event Case Identification in Electronic Health Records Using a Text-Mining Tool.Drug safety · 2026Article
- Development and external validation of a machine learning model for predicting drug-induced immune thrombocytopenia in a real-world hospital cohort.BMC medical informatics and decision making · 2025Article
- Predicting rare drug-drug interaction events with dual-granular structure-adaptive and pair variational representation.Nature communications · 2025Article
- Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.Drug safety · 2025Article
- Exploring Health Informatics in the Battle against Drug Addiction: Digital Solutions for the Rising Concern.Journal of personalized medicine · 2024Review
- Detection of novel drug-adverse drug reaction signals in rheumatoid arthritis and ankylosing spondylitis: analysis of Korean real-world biologics registry data.Scientific reports · 2024Article
- Integrating electronic health records with other data sources for postmarket drug safety signal identification: a review.Frontiers in drug safety and regulation · 2024Review
- High-Throughput Computing to Automate Population-Based Studies to Detect the 30-Day Risk of Adverse Outcomes After New Outpatient Medication Use in Older Adults with Chronic Kidney Disease: A Clinical Research Protocol.Canadian journal of kidney health and disease · 2024Article
- Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review.JMIR medical informatics · 2023Review
- Article
- Challenges and opportunities of big data analytics in healthcare.Health care science · 2023Review
- Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review.Drug safety · 2023Article
- Early Detection of Adverse Drug Reaction Signals by Association Rule Mining Using Large-Scale Administrative Claims Data.Drug safety · 2023Article
- LiSA: an assisted literature search pipeline for detecting serious adverse drug events with deep learning.BMC medical informatics and decision making · 2022Article
- iADRGSE: A Graph-Embedding and Self-Attention Encoding for Identifying Adverse Drug Reaction in the Earlier Phase of Drug Development.International journal of molecular sciences · 2022Article
- Detection of statin-induced rhabdomyolysis and muscular related adverse events through data mining technique.BMC medical informatics and decision making · 2022Article
- Explainable detection of adverse drug reaction with imbalanced data distribution.PLoS computational biology · 2022Article
- Identifying Antidepressants Less Likely to Cause Hyponatremia: Triangulation of Retrospective Cohort, Disproportionality, and Pharmacodynamic Studies.Clinical pharmacology and therapeutics · 2022Article
- Intelligent Telehealth in Pharmacovigilance: A Future Perspective.Drug safety · 2022Review
30 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
objectiveData-mining algorithms that can produce accurate signals of potentially novel adverse drug reactions (ADRs) are a central component of pharmacovigilance. We propose a signal-detection strategy that combines the adverse event reporting system (AERS) of the Food and Drug Administration and electronic health records (EHRs) by requiring signaling in both sources. We claim that this approach leads to improved accuracy of signal detection when the goal is to produce a highly selective ranked set of candidate ADRs. MATERIALS AND
methodsOur investigation was based on over 4 million AERS reports and information extracted from 1.2 million EHR narratives. Well-established methodologies were used to generate signals from each source. The study focused on ADRs related to three high-profile serious adverse reactions. A reference standard of over 600 established and plausible ADRs was created and used to evaluate the proposed approach against a comparator.
resultsThe combined signaling system achieved a statistically significant large improvement over AERS (baseline) in the precision of top ranked signals. The average improvement ranged from 31% to almost threefold for different evaluation categories. Using this system, we identified a new association between the agent, rasburicase, and the adverse event, acute pancreatitis, which was supported by clinical review.
conclusionsThe results provide promising initial evidence that combining AERS with EHRs via the framework of replicated signaling can improve the accuracy of signal detection for certain operating scenarios. The use of additional EHR data is required to further evaluate the capacity and limits of this system and to extend the generalizability of these results.
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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.