Finding Asthma: Building a Foundation for Care and Discovery

EHRs contain vast amounts of clinical information necessary for clinical care and research, but only some of the clinical information is stored as structured data elements, including demographics, active diagnoses, medications, physician orders, and (in some health systems) laboratory values and lun...

Full description

Saved in:
Bibliographic Details
Published in:American journal of respiratory and critical care medicine 2017-08, Vol.196 (4), p.401-402
Main Authors: Beuther, David A, Krishnan, Jerry A
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Asthma
Automation
Electronic health records
Genotype & phenotype
Health risk assessment
Humans
Language
Narratives
Natural Language Processing
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:EHRs contain vast amounts of clinical information necessary for clinical care and research, but only some of the clinical information is stored as structured data elements, including demographics, active diagnoses, medications, physician orders, and (in some health systems) laboratory values and lung function data. Compared with chart review, natural language processing demonstrated outstanding sensitivity, specificity, positive predictive value, and negative predictive value (97%, 95%, 90%, and 98%, respectively). Application of a natural language processing algorithm to asthma ascertainment: an automated chart review.
ISSN:1073-449X
1535-4970
DOI:10.1164/rccm.201704-0840ED