Detecting possible vaccine adverse events in clinical notes of the electronic medical record
- PMID: 19428833
- DOI: 10.1016/j.vaccine.2009.01.105
Detecting possible vaccine adverse events in clinical notes of the electronic medical record
Abstract
The Vaccine Safety Datalink (VSD) is a collaboration between the CDC and eight large HMOs to investigate adverse events following immunization through analyses of clinical data. We modified an existing system, called MediClass, that uses natural language processing to identify clinical events recorded in electronic medical records (EMRs). We customized MediClass so it could detect possible vaccine adverse events (VAEs) generally, and gastrointestinal-related VAEs in particular, in the text clinical notes of encounters recorded in the EMR of a large HMO. Compared to methods that use diagnosis and utilization codes assigned to encounters by clinicians and administrators, the MediClass system can both find more adverse events and improve the positive predictive value for detecting possible VAEs.
Similar articles
-
Understanding the role of human variation in vaccine adverse events: the Clinical Immunization Safety Assessment Network.Pediatrics. 2011 May;127 Suppl 1:S65-73. doi: 10.1542/peds.2010-1722J. Epub 2011 Apr 18. Pediatrics. 2011. PMID: 21502239
-
Safety monitoring in vaccine development and immunization.Acta Paediatr Taiwan. 2006 Jan-Feb;47(1):7-13. Acta Paediatr Taiwan. 2006. PMID: 17016963 Review.
-
Detecting possible vaccination reactions in clinical notes.AMIA Annu Symp Proc. 2005;2005:306-10. AMIA Annu Symp Proc. 2005. PMID: 16779051 Free PMC article.
-
Natural language processing in the electronic medical record: assessing clinician adherence to tobacco treatment guidelines.Am J Prev Med. 2005 Dec;29(5):434-9. doi: 10.1016/j.amepre.2005.08.007. Am J Prev Med. 2005. PMID: 16376707
-
Use of vaccine surveillance data in the evaluation of safety of vaccines.Vaccine. 2004 May 7;22(15-16):2076-9. doi: 10.1016/j.vaccine.2004.01.020. Vaccine. 2004. PMID: 15121327 Review.
Cited by
-
Text Mining of Adverse Events in Clinical Trials: Deep Learning Approach.JMIR Med Inform. 2021 Dec 24;9(12):e28632. doi: 10.2196/28632. JMIR Med Inform. 2021. PMID: 34951601 Free PMC article.
-
Identifying adverse drug reactions from free-text electronic hospital health record notes.Br J Clin Pharmacol. 2022 Mar;88(3):1235-1245. doi: 10.1111/bcp.15068. Epub 2021 Oct 13. Br J Clin Pharmacol. 2022. PMID: 34468999 Free PMC article.
-
The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink.Pharmacoepidemiol Drug Saf. 2020 Feb;29(2):182-188. doi: 10.1002/pds.4919. Epub 2019 Dec 3. Pharmacoepidemiol Drug Saf. 2020. PMID: 31797475 Free PMC article.
-
Challenges of Using Text Classifiers for Causal Inference.Proc Conf Empir Methods Nat Lang Process. 2018 Oct-Nov;2018:4586-4598. Proc Conf Empir Methods Nat Lang Process. 2018. PMID: 31633125 Free PMC article.
-
Using natural language processing of clinical text to enhance identification of opioid-related overdoses in electronic health records data.Pharmacoepidemiol Drug Saf. 2019 Aug;28(8):1143-1151. doi: 10.1002/pds.4810. Epub 2019 Jun 19. Pharmacoepidemiol Drug Saf. 2019. PMID: 31218780 Free PMC article.
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
