Hallaj Shahin, Khawaja Anthony P, Rodrigues Ian A S, Boland Michael V, Brown Eric N, Chen Aiyin, Stagg Brian C, Stein Joshua D, Sun Catherine Q, Mahe-Cook Anne-Laure, Swaminathan Swarup S, Wang Sophia Y, Xu Benjamin Y, Weinreb Robert N, Baxter Sally L
Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, La Jolla, California; Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, California; Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, La Jolla, California.
National Institute for Health and Care Research Biomedical Research Centre, Moorfields Eye Hospital National Health Service Foundation Trust and University College London Institute of Ophthalmology, London, UK.
Ophthalmol Glaucoma. 2025 Jan-Feb;8(1):83-91. doi: 10.1016/j.ogla.2024.08.001. Epub 2024 Aug 13.
OBJECTIVE/PURPOSE: Standardization of eye care data is important for clinical interoperability and research. We aimed to address gaps in the representations of glaucoma examination concepts within Systemized Nomenclature of Medicine - Clinical Terms (SNOMED-CT), the preferred terminology of the American Academy of Ophthalmology.
Study of data elements.
Structured eye examination data fields from 2 electronic health records (EHR) systems (Epic Systems and Medisoft) were compared against existing SNOMED-CT codes for concepts representing glaucoma examination findings. Glaucoma specialists from multiple institutions were surveyed to identify high-priority gaps in representation, which were discussed among the SNOMED International Eye Care Clinical Reference Group. Proposals for new codes to address the gaps were formulated and submitted for inclusion in SNOMED-CT.
Gaps in SNOMED-CT glaucoma examination concept representations.
We identified several gaps in SNOMED-CT regarding glaucoma examination concepts. A survey of glaucoma specialists identified high-priority data elements within the categories of tonometry and gonioscopy. For tonometry, there was consensus that we need to define new codes related to maximum intraocular pressure (IOP) and target IOP and delineate all methods of measuring IOP. These new codes were proposed and successfully added to SNOMED-CT for future use. Regarding gonioscopy, the current terminology did not include the ability to denote the gonioscopic grading system used (e.g., Shaffer or Spaeth), degree of angle pigmentation, iris configuration (except for plateau iris), and iris approach. There was also no ability to specify eye laterality or angle quadrant for gonioscopic findings. We proposed a framework for representing gonioscopic findings as observable entities in SNOMED-CT.
There are existing gaps in the standardized representation of findings related to tonometry and gonioscopy within SNOMED-CT. These are important areas for evaluating clinical outcomes and enabling secondary use of EHR data for glaucoma research. This international multi-institutional collaborative process enabled identification of gaps, prioritization, and development of data standards to address these gaps. Addressing these gaps and augmenting SNOMED-CT coverage of glaucoma examination findings could enhance clinical documentation and future research efforts related to glaucoma.
FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
眼科护理数据的标准化对于临床互操作性和研究至关重要。我们旨在解决医学系统化命名法 - 临床术语（SNOMED-CT）（美国眼科学会的首选术语）中青光眼检查概念表示方面的差距。
数据元素研究。
将来自两个电子健康记录（EHR）系统（Epic Systems和Medisoft）的结构化眼科检查数据字段与代表青光眼检查结果的现有SNOMED-CT代码进行比较。对多个机构的青光眼专家进行了调查，以确定表示方面的高优先级差距，这些差距在SNOMED国际眼科护理临床参考小组中进行了讨论。制定了填补差距的新代码提案并提交以纳入SNOMED-CT。
SNOMED-CT青光眼检查概念表示中的差距。
我们在SNOMED-CT中发现了一些关于青光眼检查概念的差距。对青光眼专家的一项调查确定了眼压测量和前房角镜检查类别中的高优先级数据元素。对于眼压测量，大家一致认为我们需要定义与最大眼内压（IOP）和目标眼压相关的新代码，并描述所有测量眼压的方法。这些新代码已被提出并成功添加到SNOMED-CT中以供将来使用。关于前房角镜检查，当前术语不包括表示所使用的前房角镜分级系统（例如，Shaffer或Spaeth）、房角色素沉着程度、虹膜形态（除了高褶虹膜）和虹膜入路的能力。也无法为前房角镜检查结果指定眼别或房角象限。我们提出了一个在SNOMED-CT中将前房角镜检查结果表示为可观察实体的框架。
SNOMED-CT中与眼压测量和前房角镜检查相关的结果标准化表示存在现有差距。这些是评估临床结果以及使EHR数据能够用于青光眼研究二次利用的重要领域。这个国际多机构协作过程能够识别差距、确定优先级并制定数据标准来填补这些差距。填补这些差距并扩大SNOMED-CT对青光眼检查结果的覆盖范围可以加强与青光眼相关的临床记录和未来研究工作。
在本文末尾的脚注和披露中可能会找到专有或商业披露信息。
