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A Natural Language Processing System That Links Medical Terms in Electronic Health Record Notes to Lay Definitions:

Jinying Chen1, Emily Druhl2, Balaji Polepalli Ramesh3

  • 1Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States.

Journal of Medical Internet Research
|January 24, 2018
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Summary
This summary is machine-generated.

NoteAid is a new tool that translates medical jargon in electronic health records (EHR) into plain language, improving patient understanding of their health information. This system was developed to enhance patient portal usability and comprehension of EHR notes.

Keywords:
computer softwareconsumer health informaticselectronic health recordsnatural language processingusability testing

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Area of Science:

  • Health Informatics
  • Natural Language Processing
  • Medical Communication

Background:

  • Patient portals increasingly provide access to electronic health records (EHR).
  • Medical terminology in EHR notes can hinder patient comprehension.
  • This can limit the benefits of patients accessing their own health information.

Purpose of the Study:

  • To develop and evaluate NoteAid, a web-based system using natural language processing.
  • NoteAid links medical terms in EHR notes to definitions understandable by laypeople.
  • The goal is to improve patient understanding of their health records.

Main Methods:

  • Developed CoDeMed (lexical resource of lay definitions) and MedLink (linking computational unit).
  • Utilized an adapted distant supervision algorithm to prioritize medical terms for EHR comprehension.
  • Ten physician experts evaluated NoteAid's usability and content quality via cognitive walkthroughs and questionnaires.

Main Results:

  • Physician feedback was mixed, with positive comments on ease of use, display, speed, and definition adequacy.
  • Identified areas for improvement included definition display, term inclusion, context-specific definitions, and medicine definition scope.
  • NoteAid's interface and definitions were improved, and 4502 new definitions were added to CoDeMed.

Conclusions:

  • Physician feedback facilitated content validation and refinement of NoteAid.
  • The tool shows potential to enhance patient EHR comprehension and portal experience.
  • Future work includes developing algorithms for ambiguous terms and patient-focused evaluations.