Observational studyDrug safety2015
A Method to Combine Signals from Spontaneous Reporting Systems and Observational Healthcare Data to Detect Adverse Drug Reactions.
Observational study in Drug safety, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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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.
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Who cites it
36 citing papers in PubMed.
- Strengthening Signal Detection by Proactive Adverse Event Case Identification in Electronic Health Records Using a Text-Mining Tool.Drug safety · 2026Article
- Generative Transformers for Pharmacovigilance Signal Detection using Electronic Health Records.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026Article
- Disproportionality Analysis and Causal Inference in Drug Safety.Pharmaceutical medicine · 2025Review
- 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
- A discovery and verification approach to pharmacovigilance using electronic healthcare data.Frontiers in pharmacology · 2024Article
- Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review.Drug safety · 2023Article
- Serially Combining Epidemiological Designs Does Not Improve Overall Signal Detection in Vaccine Safety Surveillance.Drug safety · 2023Article
- Early Detection of Adverse Drug Reaction Signals by Association Rule Mining Using Large-Scale Administrative Claims Data.Drug safety · 2023Article
- A New Drug Safety Signal Detection and Triage System Integrating Sequence Symmetry Analysis and Tree-Based Scan Statistics with Longitudinal Data.Clinical epidemiology · 2023Article
- Enhancing antidepressant safety surveillance: comparative analysis of adverse drug reaction signals in spontaneous reporting and healthcare claims databases.Frontiers in pharmacology · 2023Article
- 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
- A reference set of clinically relevant adverse drug-drug interactions.Scientific data · 2022Article
- Random control selection for conducting high-throughput adverse drug events screening using large-scale longitudinal health data.CPT: pharmacometrics & systems pharmacology · 2021Article
- Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilance.Journal of biomedical informatics · 2021Article
- Combining a Pharmacological Network Model with a Bayesian Signal Detection Algorithm to Improve the Detection of Adverse Drug Events.Frontiers in pharmacology · 2021Article
- Combining Social Media and FDA Adverse Event Reporting System to Detect Adverse Drug Reactions.Drug safety · 2020Article
- Mining and visualizing high-order directional drug interaction effects using the FAERS database.BMC medical informatics and decision making · 2020Article
- Complementing Observational Signals with Literature-Derived Distributed Representations for Post-Marketing Drug Surveillance.Drug safety · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
introductionObservational healthcare data contain information useful for hastening detection of adverse drug reactions (ADRs) that may be missed by using data in spontaneous reporting systems (SRSs) alone. There are only several papers describing methods that integrate evidence from healthcare databases and SRSs. We propose a methodology that combines ADR signals from these two sources.
objectivesThe aim of this study was to investigate whether the proposed method would result in more accurate ADR detection than methods using SRSs or healthcare data alone. RESEARCH
designWe applied the method to four clinically serious ADRs, and evaluated it using three experiments that involve combining an SRS with a single facility small-scale electronic health record (EHR), a larger scale network-based EHR, and a much larger scale healthcare claims database. The evaluation used a reference standard comprising 165 positive and 234 negative drug-ADR pairs. MEASURES: Area under the receiver operator characteristics curve (AUC) was computed to measure performance.
resultsThere was no improvement in the AUC when the SRS and small-scale HER were combined. The AUC of the combined SRS and large-scale EHR was 0.82 whereas it was 0.76 for each of the individual systems. Similarly, the AUC of the combined SRS and claims system was 0.82 whereas it was 0.76 and 0.78, respectively, for the individual systems.
conclusionsThe proposed method resulted in a significant improvement in the accuracy of ADR detection when the resources used for combining had sufficient amounts of data, demonstrating that the method could integrate evidence from multiple sources and serve as a tool in actual pharmacovigilance practice.
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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.