Evidence map›Paper›PMID 42382822›Full record

ArticleOphthalmology science2026

Data Volume and the Need for Clinical Decision Support in Glaucoma Care.

Ashley Polski, Ben J Brintz, Rachel Hess, Kensaku Kawamoto, Felipe A Medeiros, Joshua D Stein, Brian C Stagg, SOURCE Consortium

Abstract read
In one paragraph

Article in Ophthalmology science, 2026. 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
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0citing papers in PubMed
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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

8 authors.

Ashley PolskiDepartment of Ophthalmology, Moran Eye Center, University of Utah, Salt Lake City, Utah.
Ben J BrintzDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah.
Rachel HessDivision of Health Systems Innovation and Research, Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah.
Kensaku KawamotoDepartment of Biomedical Informatics, University of Utah, Salt Lake City, Utah.
Felipe A MedeirosDepartment of Ophthalmology, Bascom Palmer Eye Institute, University of Miami, Miami, Florida.
Joshua D SteinDepartment of Ophthalmology, Kellogg Eye Center, University of Michigan, Ann Arbor, Michigan.
Brian C StaggDepartment of Ophthalmology, Moran Eye Center, University of Utah, Salt Lake City, Utah.
SOURCE Consortium

Funding

Enhanced Identification of Ocular Phenotypes and Outcomes in Electronic Health Record DataR01EY032475 · NEI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI STEIN, JOSHUA D · 2022 to 2025
$2.7M
NEI NIH HHS R01 EY032475
6 · The paper itself

Abstract

Purpose: Glaucoma providers longitudinally integrate clinical data to inform treatment decisions. While information overload is an increasingly well-recognized issue in medicine, the volume of information associated with glaucoma care remains poorly understood. In this descriptive study, we aim to quantify the cumulative data volume associated with longitudinal glaucoma care in the Sight Outcomes Research Collaborative (SOURCE) database. Design: Retrospective, multicenter cross-sectional study. Subjects: Patients with glaucoma in SOURCE database who saw an eye care provider in 2021 and >2 years prior. Methods: The number of glaucoma-relevant data points (intraocular pressure [IOP] measurements, retinal nerve fiber layer [RNFL] OCT scans, visual field [VF] tests, prior treatments, comorbidities, and prior eye care providers seen) was determined per patient and stratified by years of database enrollment. Subanalyses based on provider-type and individual year were also performed. Main Outcome Measures: Number of cumulative glaucoma-relevant clinical data points per patient. Results: In 2021, 60 624 patients with glaucoma with median enrollment of 2641 days and a median age of 77 years were seen across 11 sites; 13 426 patients (22.1%) were enrolled for 2 to 5 years, 38 630 (63.7%) for 6 to 8 years, and 8568 (14.1%) for ≥9 years. In total, patients underwent a median of 30 IOP measurements (interquartile range [IQR] 16-52), 2 VF tests (IQR 0-6), and 3 RNFL OCT scans (IQR 0-8) within the study period. After stratifying by enrollment time, patients followed for ≥9 years had up to 636 IOP measurements on record (median 40) and saw up to 76 unique eye care providers (median 8). By 2021, 59 472 (98.1%) patients had >7 glaucoma-relevant clinical data points on record. In 2021, eye care providers saw a median of 31 unique patients with glaucoma each (range 1-1812). Conclusions: The SOURCE database contains a large volume of data associated with longitudinal glaucoma care. As the prevalence of glaucoma is expected to grow substantially in coming decades, improved clinical decision support may be helpful for accurately and efficiently appraising large amounts of clinical data. Understanding the data volume associated with glaucoma care may be useful for developing future clinical decision-support strategies and further studying this topic. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

Clinical decision-makingData volumeGlaucoma

Identifiers

PMID42382822
PMCPMC13316559

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