Development of an Open-Source Annotated Glaucoma Medication Dataset From Clinical Notes in the Electronic Health Record

Jimmy S. Chen, Wei Chun Lin, Sen Yang, Michael F. Chiang, Michelle R. Hribar

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Purpose: To describe the methods involved in processing and characteristics of an open dataset of annotated clinical notes from the electronic health record (EHR) annotated for glaucoma medications. Methods: In this study, 480 clinical notes from office visits, medical record numbers (MRNs), visit identification numbers, provider names, and billing codes were extracted for 480 patients seen for glaucoma by a comprehensive or glaucoma ophthalmologist from January 1, 2019, to August 31, 2020. MRNs and all visit data were de-identified using a hash function with salt from the deidentifyr package. All progress notes were annotated for glaucoma medication name, route, frequency, dosage, and drug use using an open-source annotation tool, Doccano. Annotations were saved separately. All protected health information (PHI) in progress notes and annotated files were deidentified using the published de-identifying algorithm Philter. All progress notes and annotations were manually validated by two ophthalmologists to ensure complete deidentification. Results: The final dataset contained 5520 annotated sentences, including those with and without medications, for 480 clinical notes. Manual validation revealed 10 instances of remaining PHI which were manually corrected. Conclusions: Annotated free-text clinical notes can be de-identified for upload as an open dataset. As data availability increases with the adoption of EHRs, free-text open datasets will become increasingly valuable for “big data” research and artificial intelligence development. This dataset is published online and publicly available at https: // Translational Relevance: This open access medication dataset may be a source of raw data for future research involving big data and artificial intelligence research using freetext.

Original languageEnglish (US)
Article number20
JournalTranslational Vision Science and Technology
Issue number11
StatePublished - Nov 2022


  • artificial intelligence
  • big data
  • electronic health records
  • glaucoma
  • medications

ASJC Scopus subject areas

  • Biomedical Engineering
  • Ophthalmology


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