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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Jul 23, 2020
Date Accepted: Jan 18, 2021

The final, peer-reviewed published version of this preprint can be found here:

Contribution of Free-Text Comments to the Burden of Documentation: Assessment and Analysis of Vital Sign Comments in Flowsheets

Yin Z, Liu Y, McCoy AB, Malin BA, Sengstack PR

Contribution of Free-Text Comments to the Burden of Documentation: Assessment and Analysis of Vital Sign Comments in Flowsheets

J Med Internet Res 2021;23(3):e22806

DOI: 10.2196/22806

PMID: 33661128

PMCID: 7974764

The Contribution of Free Text Comments to the Burden of Documentation: An Assessment and Analysis of Vital Signs Comments in Flowsheets

  • Zhijun Yin; 
  • Yongtai Liu; 
  • Allison B. McCoy; 
  • Bradley A. Malin; 
  • Patricia R. Sengstack

ABSTRACT

Background:

Documentation burden is a common problem with modern electronic health record (EHR) systems. To reduce such burden, various recording methods (e.g., voice recorders or motion sensors) have been proposed. However, these solutions are in an early prototype phase and are unlikely to transition into practice in the near future. A more pragmatic alternative is to directly modify the implementation of the existing functionalities of an EHR system.

Objective:

Assess the nature of free text comments entered into EHR flowsheets that supplement the quantitative vital sign values and examine opportunities to simplify functionality and reduce documentation burden.

Methods:

We evaluated 209,055 vital sign comments in flowsheets that were generated in the Epic EHR system at Vanderbilt University Medical Center in 2018. We applied topic modeling, as well as the natural language processing CLAMP software system, to extract general discussed topics and detailed medical terms to investigate the stories communicated within these comments.

Results:

Our analysis showed that 63.3% of the 9,557 users that entered any vital signs made at least one free text comment in vital sign flowsheet entries. The user roles that were most likely to compose comments were Registered Nurse, Technician, and Licensed Nurse. The most frequently identified topics were the notification of a result to healthcare providers (34.7%), the context of a measurement (30.7%), and an inability to obtain a vital sign (22.4%). There were 4,187 unique medical terms/phrases that were extracted from 46,029 (22.0%) comments, including many symptom-related terms such as pain, upset, dizziness, coughing, anxious, distress and fever, and drug-related terms such as Tylenol, anesthesia, cannula, oxygen, Motrin, Rituxan, and labetalol.

Conclusions:

Considering that flowsheet comments are generally not displayed or automatically pulled into any clinical notes, our findings suggested that the flowsheet comment functionality could be simplified (e.g., via structured response fields instead of a text input dialog) to reduce healthcare provider effort. Moreover, the rich and clinically important medical terms such as medications and symptoms should be explicitly recorded in clinical notes for better visibility.


 Citation

Please cite as:

Yin Z, Liu Y, McCoy AB, Malin BA, Sengstack PR

Contribution of Free-Text Comments to the Burden of Documentation: Assessment and Analysis of Vital Sign Comments in Flowsheets

J Med Internet Res 2021;23(3):e22806

DOI: 10.2196/22806

PMID: 33661128

PMCID: 7974764

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