April 2011
Volume 52, Issue 14
ARVO Annual Meeting Abstract  |   April 2011
Accuracy and Speed of Electronic Health Record Documentation Strategies in Ophthalmology
Author Affiliations & Notes
  • Patrick Chan
    Columbia University Harkness Eye Institute, New York, New York
  • Preeti J. Thyparampil
    Columbia University Harkness Eye Institute, New York, New York
  • Michael F. Chiang
    Departments of Ophthalmology and Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon
  • Footnotes
    Commercial Relationships  Patrick Chan, None; Preeti J. Thyparampil, None; Michael F. Chiang, None
  • Footnotes
    Support  Supported by an unrestricted departmental grant from Research to Prevent Blindness (New York, NY)
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 5551. doi:
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      Patrick Chan, Preeti J. Thyparampil, Michael F. Chiang; Accuracy and Speed of Electronic Health Record Documentation Strategies in Ophthalmology. Invest. Ophthalmol. Vis. Sci. 2011;52(14):5551.

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

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Purpose: : Electronic health records (EHRs) are a potential means to improve the quality of patient care while decreasing cost. EHRs in ophthalmology face unique challenges due to the complexity of the eye exam, dependence on images, and lack of standardization in documentation. We evaluate the accuracy and speed of different EHR strategies for ophthalmic data.

Methods: : Templates for 2 EHR strategies were developed using a software kit (Visual Basic 2008; Microsoft Corp., Redmond, WA). The first strategy required keyboard input; the second required mouse-driven menu input. A third strategy using a paper examination template was used for comparison. Ophthalmology trainees were presented 5 clinical exams from a public repository of ophthalmic cases (http://webeye.ophth.uiowa.edu/eyeforum/cases.htm). Positive and negative clinical findings were identified in each exam by author consensus. Subjects documented findings on each template after oral case presentations. For each template-case pair, the total time for charting the findings was used to calculate time per exam finding. Accuracy was calculated based on sensitivity and positive predictive value (PPV).

Results: : Twenty subjects were enrolled. A total of 258 findings were identified in the 5 cases, resulting in 300 template-case pairs and 77,400 total findings documented by subjects. Mean (±;SD) documentation time was significantly slower for the keyboard (2.40±;1.11 sec/finding) and mouse-driven (2.22±;0.711 sec/finding) strategies, compared to the paper (1.99±;0.809 sec/finding) strategy. Sensitivity was 89.1% for the EHR keyboard strategy, 87.2% for the EHR mouse-driven strategy, and 88.6% for the paper-based strategy (NS). PPV was 99.4% for the EHR keyboard strategy, 98.9% for the EHR mouse-driven strategy, and 99.9% for the paper strategy (p<0.001 between mouse-driven and paper strategies, NS between other pairs).

Conclusions: : Physician time for data entry is slower using the EHR strategies in this study, compared to a paper-based strategy. Accuracy of documentation was imperfect, although there were no major differences among strategies. Further studies involving total physician time, along with the cost-benefit impact of ophthalmic EHRs, are required.

Keywords: clinical (human) or epidemiologic studies: systems/equipment/techniques • clinical (human) or epidemiologic studies: health care delivery/economics/manpower • clinical (human) or epidemiologic studies: biostatistics/epidemiology methodology 

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