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Brief Report
October 2018

Assessing the Precision of ICD-10 Codes for Uveitis in 2 Electronic Health Record Systems

Author Affiliations
  • 1Department of Ophthalmology, University of Colorado School of Medicine, Aurora
  • 2Illinois Retina Associates, SC, Chicago
  • 3Department of Ophthalmology, Rush University, Chicago, Illinois
  • 4Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York
  • 5Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
  • 6Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
  • 7Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, Maryland
JAMA Ophthalmol. 2018;136(10):1186-1190. doi:10.1001/jamaophthalmol.2018.3001
Key Points

Question  Do 2 different electronic health record systems generate the same International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes for a specific uveitic diagnostic entity?

Findings  Comparison of 2 electronic health record platforms demonstrated that 13 of 27 uveitides were represented by imprecise ICD-10 codes. Multiple codes were used to describe 4 diseases, and there were also 6 cases in which individual ICD-10 codes were used to describe more than 1 specific disease.

Meaning  As the development of big-data analyses of electronic health records combining data from multiple platforms are used to research disease associations, outcomes, and reimbursement, imprecise ICD-10 coding of uveitic disease might lead to inaccurate and difficult-to-interpret conclusions.


Importance  Electronic health record (EHR) systems based on International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) coding of disease entities are increasingly being used to generate large data sets for analysis. However, the reproducibility of ICD-10 coding in uveitis has not been assessed across EHR platforms, and imprecision in coding may lead to improper conclusions in big-data analyses.

Objective  To compare ICD-10 coding of uveitis using 2 EHR systems.

Design, Setting, and Participants  This study compares ICD-10 codes for 27 uveitic diseases generated by the Epic and MDIntelleSys EHR systems to the ICD-10 descriptions associated with the codes. No patient data were assessed in this study.

Main Outcomes and Measures  The number of diseases for which ICD-10 coding differed between the 2 systems.

Results  Thirteen of 27 uveitic diseases were coded differently by the 2 EHR systems. Coding imprecision was notable in that the Epic system returned 16 ICD-10 codes and the MDIntelleSys returned 12 ICD-10 codes to describe 13 diseases; 4 diseases had multiple codes returned, and 6 codes were used to describe more than 1 disease. For example, MDIntelleSys uses ICD-10 code H30.13 for both birdshot choroiditis and acute retinal necrosis, while Epic uses H30.9 for both birdshot choroiditis and multiple evanescent white dot syndrome; MDIntelleSys uses this code for multifocal choroiditis. Furthermore, the ICD-10 descriptions for certain codes lack specificity, allowing variable interpretation by the coder.

Conclusions and Relevance  This study suggests there is substantial disparity in the ICD-10 codes that are generated for specific uveitides by the 2 EHR systems studied. This result implies that analysis of large databases generated from the pooling of EHR data could produce results with substantial bias because of misclassification resulting from conflicting and imprecise coding of uveitides. Therefore, research into outcomes, costs, health care utilization, and epidemiology in uveitis might be improved if a more uniform coding system to describe ocular inflammatory disease is implemented.

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