Evidence map›Paper›PMID 40193233›Full record

ArticleJournal of glaucoma2025

Gap Analysis of Standard Automated Perimetry Concept Representation in Medical Terminologies.

Shahin Hallaj, William Halfpenny, Niloofar Radgoudarzi, Michael V Boland, Swarup S Swaminathan, Sophia Y Wang, Benjamin Y Xu, Dilru C Amarasekera, Brian Stagg, Aiyin Chen and 9 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of glaucoma, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Shahin HallajDivision of Ophthalmology Informatics and Data Science, Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute.ORCID 0000-0002-9541-1915
William HalfpennyDivision of Ophthalmology Informatics and Data Science, Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute.
Niloofar RadgoudarziDivision of Ophthalmology Informatics and Data Science, Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute.
Michael V BolandDepartment of Ophthalmology, Mass Eye and Ear, Harvard Medical School, Cambridge, MA.
Swarup S SwaminathanBascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, FL.
Sophia Y WangByers Eye Institute, Stanford University, Palo Alto, CA.
Benjamin Y XuDepartment of Ophthalmology, Roski Eye Institute, Keck School of Medicine at the University of Southern California, Los Angeles.
Dilru C AmarasekeraGlaucoma Service, Wills Eye Hospital, Thomas Jefferson University, Philadelphia, PA.
Brian StaggDepartment of Ophthalmology and Visual Sciences, John Moran Eye Center, Salt Lake City.
Aiyin ChenDepartment of Ophthalmology, Casey Eye Institute, Portland.
Michelle HribarDepartment of Ophthalmology, Casey Eye Institute, Portland.
Kaveri A ThakoorDepartment of Biomedical Engineering, Columbia University.
Kerry E GoetzOffice of Data Science and Health Informatics, National Eye Institute, National Institutes of Health, Baltimore, MD.
Jonathan S MyersGlaucoma Service, Wills Eye Hospital, Thomas Jefferson University, Philadelphia, PA.
Aaron Y LeeDepartment of Ophthalmology, School of Medicine, University of Washington, Seattle, WA.
Mark A ChristopherDivision of Ophthalmology Informatics and Data Science, Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute.
Linda M ZangwillDivision of Ophthalmology Informatics and Data Science, Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute.
Robert N WeinrebDivision of Ophthalmology Informatics and Data Science, Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute.
Sally L BaxterDivision of Ophthalmology Informatics and Data Science, Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute.ORCID 0000-0002-5271-7690

Funding

Bridge2AI:Salutogenesis Data Generation ProjectOT2OD032644 · OD · WASHINGTON UNIVERSITY · PI BAXTER, SALLY LIU, CHUTE, CHRISTOPHER G · 2022 to 2025
$32.7M
Vision BiostatisticsP30EY022589 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Derek Stuart Welsbie · 2012 to 2026
$10.3M
Multi-modal Health Information Technology Innovations for Precision Management of GlaucomaDP5OD029610 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAXTER, SALLY LIU · 2020 to 2024
$2.1M
Multimodal Artificial Intelligence to Predict Glaucomatous Progression and Surgical InterventionR01EY034146 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAXTER, SALLY LIU, CHRISTOPHER, MARK · 2022 to 2025
$1.8M
Operationalizing Machine Learning and Discrete Event Simulation Models to Improve Clinic EfficiencyR01LM013426 · NLM · OREGON HEALTH & SCIENCE UNIVERSITY · PI HRIBAR, MICHELLE · 2020 to 2023
$1.3M
Translational Vision Research Training at UCSDT32EY026590 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ZANGWILL, LINDA M · 2016 to 2025
$854k
Deep Learning Approaches to Detect Glaucoma and Predict Progression from Spectral Domain Optical Coherence TomographyR00EY030942 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CHRISTOPHER, MARK · 2023 to 2025
$747k
NEI NIH HHS P30 EY022589NEI NIH HHS R00 EY030942NEI NIH HHS R01 EY034146NEI NIH HHS T32 EY026590NIH HHS DP5 OD029610NIH HHS OT2 OD032644NLM NIH HHS R01 LM013426
6 · The paper itself

Abstract

PRÉCIS: In this multi-institutional effort, we identified gaps in SAP data elements within medical terminologies. We proposed new concepts to LOINC to enhance SAP data standards and big data representation and improve interoperability across health care systems. PURPOSE: To identify gaps in the representation of Standard Automated Perimetry (SAP) data elements in Logical Observation Identifiers Names and Codes (LOINC) and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) and propose solutions for those gaps.

methodsSAP source data elements and Digital Imaging and Communications in Medicine (DICOM) standard from 2 commonly used perimeter devices were extracted and compared against existing concepts in standardized terminologies using the OMOP CDM Athena browser and LOINC using the LOINC browser. Gap areas were identified and classified following conventions used by Health Level 7 Fast Healthcare Interoperability Resources and discussed within the OHDSI Eye Care and Vision Research Workgroup in iterative rounds aiming to address gaps. New codes were developed upon reaching a consensus and proposed for inclusion in LOINC.

resultsAmong 107 data elements extracted from the perimeters, 82% (n=88) of SAP data elements lacked representation. Of the 19 remaining elements, 2.8% (n=3) were wider, 1.9% (n=2) were narrower, and 13% (n=14) had equivalent representation. In addition, only 2.6% (n=3) of the 116 DICOM attributes related to SAP had representation in standardized terminologies. Several existing relevant codes were defined ambiguously or erroneously (eg, visual field index, pupil diameter, perimeter format Kowa).

conclusionThere is a lack of representation of some SAP data elements in standardized medical terminologies, hampering interoperability and data sharing. We identified gaps and proposed new concepts for addition to LOINC, aiming to improve SAP data standards and interoperability.

Indexed as

GlaucomaLogical Observation Identifiers Names and CodesTerminology as TopicVisual FieldsVisual Field TestsHumansglaucomaLOINCOMOPperimetrystandardsterminologyvisual field

Identifiers

PMID40193233
PMCPMC13452578

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.