Improving Health IT Safety through the Use Natural Language Processing to Improve Accuracy of EHR Documentation

Event Date: February 07, 2017 | 2:00pm – 3:30pm ET

Event Materials:

  • Presentation Slides (PDF, 2.4 MB)
  • Q&A (PDF, 544 KB)


This webinar discussed the development of innovative tools and methods designed to advance health IT safety through improved EHR documentation. Presenters discussed evaluation strategies and findings for a voice-generated enhanced electronic note system and describe concepts related to the use of natural language processing (NLP) technologies for improving accuracy and timeliness of EHR embedded notes and documents.

Learning Objectives:

At the conclusion of this webinar, participants should be able to:

  1. Discuss the development and evaluation of an enhanced electronic note system that leverages voice recognition and NLP technologies to create electronic physician notes in the EHR. 
  2. Discuss the challenges of introducing speech recognition technology into existing medical culture and current clinician workflow, including user preferences and the quality of documents generated by this technology. 
  3. Explain the need for an automated error detection system using NLP for improving the accuracy and quality of speech recognition generated medical documents, and discuss the development and evaluation of such a system.


Professor of Medicine; Adjunct Professor
Departments of Health Services and Biomedical Informatics and Medical Education
Medical Director
Information Technology Services, University of Washington
Assistant Professor of Medicine
Harvard Medical School, Brigham and Women's Hospital


Division of Digital Healthcare Research, Agency for Healthcare Research and Quality

Eligible providers were able to earn up to 1.5 CE/CME contact hours for participating in the live webinar.

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