ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2012
Analyzing patterns of drug use in clinical notes for patient safety.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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
18 citing papers in PubMed.
- A Sentence Classification-Based Medical Status Extraction Pipeline for Electronic Health Records: Institutional Case Study.JMIR medical informatics · 2026Article
- AI-Enhanced Qualitative Analysis in Healthcare: Unlocking Insight from Interviews of Leadership at Top-Performing Academic Medical Centers.Healthcare (Basel, Switzerland) · 2026Article
- Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review.JMIR medical informatics · 2023Review
- A simple neural vector space model for medical concept normalization using concept embeddings.Journal of biomedical informatics · 2022Article
- A Hybrid Normalization Method for Medical Concepts in Clinical Narrative using Semantic Matching.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Review
- Analyzing Information Seeking and Drug-Safety Alert Response by Health Care Professionals as New Methods for Surveillance.Journal of medical Internet research · 2015Article
- From Molecules to Patients: The Clinical Applications of Translational Bioinformatics.Yearbook of medical informatics · 2015Article
- Analyzing search behavior of healthcare professionals for drug safety surveillance.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2015Article
- Mining Electronic Health Records using Linked Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- Automated detection of off-label drug use.PloS one · 2014Article
- Building the graph of medicine from millions of clinical narratives.Scientific data · 2014Article
- Pharmacovigilance using clinical notes.Clinical pharmacology and therapeutics · 2013Article
- Automated Detection of Systematic Off-label Drug Use in Free Text of Electronic Medical Records.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2013Article
- Network analysis of unstructured EHR data for clinical research.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2013Article
- Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.PloS one · 2013Article
- Annotation Analysis for Testing Drug Safety Signals using Unstructured Clinical Notes.Journal of biomedical semantics · 2012Article
- Using temporal patterns in medical records to discern adverse drug events from indications.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Doctors prescribe drugs for indications that are not FDA approved. Research indicates that 21% of prescriptions filled are for off-label indications. Of those, more than 73% lack supporting scientific evidence. Traditional drug safety alerts may not cover usages that are not FDA approved. Therefore, analyzing patterns of off-label drug usage in the clinical setting is an important step toward reducing the incidence of adverse events and for improving patient safety. We applied term extraction tools on the clinical notes of a million patients to compile a database of statistically significant patterns of drug use. We validated some of the usage patterns learned from the data against sources of known on-label and off-label use. Given our ability to quantify adverse event risks using the clinical notes, this will enable us to address patient safety because we can now rank-order off-label drug use and prioritize the search for their adverse event profiles.
Identifiers
22779054PMC3392046What 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.