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

Alan G. Palestine, Pauline T. Merrill, Sophia M. Saleem, Douglas A. Jabs, Jennifer E. Thorne

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1186-1190
Number of pages5
JournalJAMA ophthalmology
Issue number10
StatePublished - Oct 2018

ASJC Scopus subject areas

  • Ophthalmology


Dive into the research topics of 'Assessing the Precision of ICD-10 Codes for Uveitis in 2 Electronic Health Record Systems'. Together they form a unique fingerprint.

Cite this