ReviewDrug safety2017
Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.
Review in Drug safety, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
93 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Methods for drug safety signal detection using routinely collected observational electronic health care data: A systematic review.Pharmacoepidemiology and drug safety · 2023Pooled it
- Using Natural Language Processing to Measure and Improve Quality of Diabetes Care: A Systematic Review.Journal of diabetes science and technology · 2021Pooled it
- Assessment of Natural Language Processing of Electronic Health Records to Measure Goals-of-Care Discussions as a Clinical Trial Outcome.JAMA network open · 2023Trial
- Natural language processing to enhance rheumatoid arthritis care in clinical studies: a scoping review of applications, data, approaches, challenges and future directions.Rheumatology international · 2026Article
- Artificial Intelligence for Opioid Safety Surveillance from Clinical Text: A Clinically Focused Review.Journal of clinical medicine · 2026Review
- Harmonizing self-reported and free text medication data: a reproducible pipeline for gerontological research.BMC medical informatics and decision making · 2025Article
- An empirical evaluation of dimensionality reduction and class balancing for medical text classification.Scientific reports · 2025Article
- On the use of natural language processing to implement the target trial framework using unstructured data from the electronic health record.Global epidemiology · 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
- Probing Large Language Model Hidden States for Adverse Drug Reaction Knowledge.medRxiv : the preprint server for health sciences · 2025Article
- Hybrid natural language processing tool for semantic annotation of medical texts in Spanish.BMC bioinformatics · 2025Article
- With big data comes big responsibility: Strategies for utilizing aggregated, standardized, de-identified electronic health record data for research.Clinical and translational science · 2025Article
- Developing electronic health records as a source of real-world data for veterinary pharmacoepidemiology.Frontiers in veterinary science · 2025Article
- Development and validation of a multi-agent AI pipeline for automated credibility assessment of tobacco misinformation: a proof-of-concept study.Frontiers in artificial intelligence · 2025Article
- Evaluating the effectiveness of AI-enhanced "One Body, Two Wings" pharmacovigilance models in China: a nationwide survey on medication safety and risk management.Frontiers in health services · 2025Article
- Article
- Post-marketing surveillance of anticancer drugs using natural language processing of electronic medical records.NPJ digital medicine · 2024Article
- Triangulation of Questionnaires, Qualitative Data and Natural Language Processing: A Differential Approach to Religious Bahá'í Fasting in Germany.Journal of religion and health · 2024Observational
- Northwestern University resource and education development initiatives to advance collaborative artificial intelligence across the learning health system.Learning health systems · 2024Article
- An innovative method to strengthen evidence for potential drug safety signals using Electronic Health Records.Journal of medical systems · 2024Article
33 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
The goal of pharmacovigilance is to detect, monitor, characterize and prevent adverse drug events (ADEs) with pharmaceutical products. This article is a comprehensive structured review of recent advances in applying natural language processing (NLP) to electronic health record (EHR) narratives for pharmacovigilance. We review methods of varying complexity and problem focus, summarize the current state-of-the-art in methodology advancement, discuss limitations and point out several promising future directions. The ability to accurately capture both semantic and syntactic structures in clinical narratives becomes increasingly critical to enable efficient and accurate ADE detection. Significant progress has been made in algorithm development and resource construction since 2000. Since 2012, statistical analysis and machine learning methods have gained traction in automation of ADE mining from EHR narratives. Current state-of-the-art methods for NLP-based ADE detection from EHRs show promise regarding their integration into production pharmacovigilance systems. In addition, integrating multifaceted, heterogeneous data sources has shown promise in improving ADE detection and has become increasingly adopted. On the other hand, challenges and opportunities remain across the frontier of NLP application to EHR-based pharmacovigilance, including proper characterization of ADE context, differentiation between off- and on-label drug-use ADEs, recognition of the importance of polypharmacy-induced ADEs, better integration of heterogeneous data sources, creation of shared corpora, and organization of shared-task challenges to advance the state-of-the-art.
Indexed as
Identifiers
28643174What OpenQuestion holds
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.