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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Detecting possible vaccine adverse events in clinical notes of the electronic medical record
Brian Hazlehurst1, Allison Naleway, John Mullooly
1Center for Health Research, Kaiser Permanente Northwest, Portland, OR 97215, USA. Brian.hazlehuhrst@kpchr.org
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.
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