ReviewBritish journal of clinical pharmacology2012
Using text-mining techniques in electronic patient records to identify ADRs from medicine use.
Review in British journal of clinical pharmacology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of Natural Language Processing (NLP) in Detecting and Preventing Suicide Ideation: A Systematic Review.International journal of environmental research and public health · 2023Pooled it
- Monitoring Adverse Drug Events in Web Forums: Evaluation of a Pipeline and Use Case Study.Journal of medical Internet research · 2024Article
- Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review.Drug safety · 2023Article
- Drug_SNSMiner: standard pharmacovigilance pipeline for detection of adverse drug reaction using SNS data.Scientific reports · 2023Article
- Language-agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records.Basic & clinical pharmacology & toxicology · 2022Article
- Combining word embeddings to extract chemical and drug entities in biomedical literature.BMC bioinformatics · 2021Article
- Natural language processing and machine learning to assist radiation oncology incident learning.Journal of applied clinical medical physics · 2021Article
- Applications of artificial intelligence in drug development using real-world data.Drug discovery today · 2021Review
- Extraction of Active Medications and Adherence Using Natural Language Processing for Glaucoma Patients.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Ontological Organization and Bioinformatic Analysis of Adverse Drug Reactions From Package Inserts: Development and Usability Study.Journal of medical Internet research · 2020Article
- Identifying Herbal Adverse Events From Spontaneous Reporting Systems Using Taxonomic Name Resolution Approach.Bioinformatics and biology insights · 2020Article
- Drug Abuse Research Trend Investigation with Text Mining.Computational and mathematical methods in medicine · 2020Article
- Linking glycemic dysregulation in diabetes to symptoms, comorbidities, and genetics through EHR data mining.eLife · 2019Article
- Phenotyping to Facilitate Accrual for a Cardiovascular Intervention.Journal of clinical medicine research · 2019Article
- Development and validation of an algorithm to identify drug-induced anaphylaxis in the Beijing Pharmacovigilance Database.International journal of clinical pharmacy · 2018Article
- Pharmacovigilance in China: development and challenges.International journal of clinical pharmacy · 2018Review
- Ontology-based literature mining and class effect analysis of adverse drug reactions associated with neuropathy-inducing drugs.Journal of biomedical semantics · 2018Article
- Evaluation of a Novel System to Enhance Clinicians' Recognition of Preadmission Adverse Drug Reactions.Applied clinical informatics · 2018Article
- Automated Screening of Emergency Department Notes for Drug-Associated Bleeding Adverse Events Occurring in Older Adults.Applied clinical informatics · 2017Article
- Content Analysis of Student Essays after Attending a Problem-Based Learning Course: Facilitating the Development of Critical Thinking and Communication Skills in Japanese Nursing Students.Healthcare (Basel, Switzerland) · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This literature review included studies that use text-mining techniques in narrative documents stored in electronic patient records (EPRs) to investigate ADRs. We searched PubMed, Embase, Web of Science and International Pharmaceutical Abstracts without restrictions from origin until July 2011. We included empirically based studies on text mining of electronic patient records (EPRs) that focused on detecting ADRs, excluding those that investigated adverse events not related to medicine use. We extracted information on study populations, EPR data sources, frequencies and types of the identified ADRs, medicines associated with ADRs, text-mining algorithms used and their performance. Seven studies, all from the United States, were eligible for inclusion in the review. Studies were published from 2001, the majority between 2009 and 2010. Text-mining techniques varied over time from simple free text searching of outpatient visit notes and inpatient discharge summaries to more advanced techniques involving natural language processing (NLP) of inpatient discharge summaries. Performance appeared to increase with the use of NLP, although many ADRs were still missed. Due to differences in study design and populations, various types of ADRs were identified and thus we could not make comparisons across studies. The review underscores the feasibility and potential of text mining to investigate narrative documents in EPRs for ADRs. However, more empirical studies are needed to evaluate whether text mining of EPRs can be used systematically to collect new information about 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.