July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
Length and similarity of consecutive ophthalmology encounter notes in the electronic health record
Author Affiliations & Notes
  • Abigail E Huang
    Advanced Clinical, Mountain View, California, United States
    Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Oregon, United States
  • Michelle Hribar
    Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Oregon, United States
  • Haley Lane Dusek
    School of Medicine, Oregon Health & Science University, Oregon, United States
    Department of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Oregon, United States
  • Isaac Goldstein
    Department of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Oregon, United States
  • Bradley Henriksen
    Department of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Oregon, United States
  • Wei-Chun Lin
    Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Oregon, United States
  • Austin Igelman
    School of Medicine, Oregon Health & Science University, Oregon, United States
    Department of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Oregon, United States
  • Michael F Chiang
    Department of Ophthalmology, Casey Eye Institute, Oregon Health & Science University, Oregon, United States
    Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Oregon, United States
  • Footnotes
    Commercial Relationships   Abigail Huang, Advanced Clinical (E); Michelle Hribar, None; Haley Dusek, None; Isaac Goldstein, None; Bradley Henriksen, None; Wei-Chun Lin, None; Austin Igelman, None; Michael Chiang, Inteleretina, LLC (Honolulu, HI) (I), Novartis (Basel, Switzerland) (C), Scientific Advisory Board for Clarity Medical Systems (Pleasanton, CA) (S)
  • Footnotes
    Support  Supported by National Institutes of Health grant R00LM12238, the National Institutes of Health (Bethesda, MD) grant P30EY10572, and unrestricted departmental funding from Research to Prevent Blindness (New York, NY).
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 5497. doi:
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      Abigail E Huang, Michelle Hribar, Haley Lane Dusek, Isaac Goldstein, Bradley Henriksen, Wei-Chun Lin, Austin Igelman, Michael F Chiang; Length and similarity of consecutive ophthalmology encounter notes in the electronic health record. Invest. Ophthalmol. Vis. Sci. 2019;60(9):5497.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Electronic progress notes can contain large amounts of duplicated text that obscure new patient information. In this retrospective chart review, we quantified the average length and redundancy of ophthalmology notes in the outpatient setting. Pairs of consecutive progress notes were compared and percentage of text identical between notes was determined.

Methods : 120 note pairs were analyzed, each consisting of two consecutive follow-up encounters for patients of 8 ophthalmology providers in 4 sub-specialties (comprehensive, cornea, retina, and neuro-ophthalmology). The length of each second note was calculated as number of printed pages and as total number of words. Each second note was also manually divided into sections - Subjective, Objective, Assessment, Plan, Other - and compared to the preceding note. Sections were further divided into subsections to characterize the main contributors to overall word count. The Oregon Health and Science University Institutional Review Board approved this study.

Results : The average length of the encounter note was 6 ± 1.3 pages (range 3-9), or 1129 ± 249 words (range 578-1918). The vast majority of text in the second note was identical in words and word order to the first note (76 ± 11% identical on average). Important sections such as Assessment and Plan comprised only 13.8 ± 5% of the total note text combined. All sections contained about 25% new text except for Plan which was 45% new (mean of 22 new words out of 46 total Plan words). In comparison, large subsections contributing to word count were Exam (205 ± 39 words), Medications (123 ± 86 words), and Past Medical History (73 ± 73 words). A further 304 ± 128 words (27% of the total note length) was composed of Other text (e.g. attribution data, billing information) not traditionally included in a SOAP note.

Conclusions : Our findings support the conclusion that the majority of progress notes text is redundant, whether it be from templated text, EHR-generated text or copy and paste. New information is buried within lengthy notes that vary little between visits. This raises concern for the accessibility of updated information in the patient chart and overall organization of the EHR.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

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