Improving patients' electronic health record comprehension with NoteAid.
Allowing patients direct access to their electronic health record (EHR) notes has been shown to enhance medical understanding and may improve healthcare management and outcome. However, EHR notes contain medical terms, shortened forms, complex disease and medication names, and other domain specific jargon that make them difficult for patients to fathom. In this paper, we present a BioNLP system, NoteAid, that automatically recognizes medical concepts and links these concepts with consumer oriented, simplified definitions from external resources. We conducted a pilot evaluation for linking EHR notes through NoteAid to three external knowledge resources: MedlinePlus, the Unified Medical Language System (UMLS), and Wikipedia. Our results show that Wikipedia significantly improves EHR note readability. Preliminary analyses show that MedlinePlus and the UMLS need to improve both content readability and content coverage for consumer health information. A demonstration version of fully functional NoteAid is available at http://clinicalnotesaid.org.
Biomedical and Health Informatics, University of Wisconsin Milwaukee, Milwaukee, WI, USA.
Balaji
B
Polepalli Ramesh
Thomas
T
Houston
Cynthia
C
Brandt
Hua
H
Fang
Hong
H
Yu
D032882:Comprehension; D054626:Consumer Health Information / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D055991:Health Records, Personal; D006801:Humans; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D010358:Patient Participation / Q000379:methods*; D012984:Software; D018875:Vocabulary, Controlled; D014956:Writing