Evidence map›Paper›PMID 38560278›Full record

ArticleOphthalmology science

Variations in Electronic Health Record-Based Definitions of Diabetic Retinopathy Cohorts: A Literature Review and Quantitative Analysis.

Jimmy S Chen, Ivan A Copado, Cecilia Vallejos, Fritz Gerald P Kalaw, Priyanka Soe, Cindy X Cai, Brian C Toy, Durga Borkar, Catherine Q Sun, Jessica G Shantha and 1 more

Open access · goldAbstract read
In one paragraph

Article in Ophthalmology science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.4field-weighted citation impact, top 12% of its field
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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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

11 authors at 5 institutions in 1 country.

Jimmy S ChenDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California.
Ivan A CopadoDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California.
Cecilia VallejosDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California.
Fritz Gerald P KalawDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California.
Priyanka SoeDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California.
Cindy X CaiWilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland.
Brian C ToyDepartment of Ophthalmology, Roski Eye Institute, Keck School of Medicine, University of Southern California, Los Angeles, California.
Durga BorkarDepartment of Ophthalmology, Duke Eye Center, Duke University, Durham, North Carolina.
Catherine Q SunF.I. Proctor Foundation, University of California San Francisco, San Francisco, California.
Jessica G ShanthaF.I. Proctor Foundation, University of California San Francisco, San Francisco, California.
Sally L BaxterDivision of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California.
University of California San Diego · USUniversity of California, San Francisco · USDuke University · USJohns Hopkins University · USUniversity of Southern California · US

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 Dirk-Uwe G Bartsch · 2012 to 2026
$10.3M
San Diego Biomedical Informatics Education & Research (SABER)T15LM011271 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SHAMIM NEMATI · 2012 to 2026
$9.7M
iGLAMOUR Study: Innovations in Glaucoma Adherence and monitoring Of Under-Represented minoritiesR01MD014850 · NIMHD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI COLEMAN, TODD P, WEINREB, ROBERT N · 2021 to 2024
$2.1M
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
Real-world outcomes of proliferative diabetic retinopathyK23EY032637 · NEI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SUN, CATHERINE QING · 2021 to 2025
$1.3M
Short-Term Research training In Vision and Eye health (STRIVE)T35EY033704 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Jolene Rudell, LINDA M ZANGWILL · 2022 to 2026
$144k
NEI NIH HHS K23 EY032637NEI NIH HHS P30 EY022589NEI NIH HHS R01 EY034146NEI NIH HHS T35 EY033704NIH HHS DP5 OD029610NIH HHS OT2 OD032644NIMHD NIH HHS R01 MD014850NLM NIH HHS T15 LM011271
6 · The paper itself

Abstract

Purpose: Use of the electronic health record (EHR) has motivated the need for data standardization. A gap in knowledge exists regarding variations in existing terminologies for defining diabetic retinopathy (DR) cohorts. This study aimed to review the literature and analyze variations regarding codified definitions of DR. Design: Literature review and quantitative analysis. Subjects: Published manuscripts. Methods: Four graders reviewed PubMed and Google Scholar for peer-reviewed studies. Studies were included if they used codified definitions of DR (e.g., billing codes). Data elements such as author names, publication year, purpose, data set type, and DR definitions were manually extracted. Each study was reviewed by ≥ 2 authors to validate inclusion eligibility. Quantitative analyses of the codified definitions were then performed to characterize the variation between DR cohort definitions. Main Outcome Measures: Number of studies included and numeric counts of billing codes used to define codified cohorts. Results: In total, 43 studies met the inclusion criteria. Half of the included studies used datasets based on structured EHR data (i.e., data registries, institutional EHR review), and half used claims data. All but 1 of the studies used billing codes such as the International Classification of Diseases 9th or 10th edition (ICD-9 or ICD-10), either alone or in addition to another terminology for defining disease. Of the 27 included studies that used ICD-9 and the 20 studies that used ICD-10 codes, the most common codes used pertained to the full spectrum of DR severity. Diabetic retinopathy complications (e.g., vitreous hemorrhage) were also used to define some DR cohorts. Conclusions: Substantial variations exist among codified definitions for DR cohorts within retrospective studies. Variable definitions may limit generalizability and reproducibility of retrospective studies. More work is needed to standardize disease cohorts. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

Big dataData standardizationDiabetic retinopathyElectronic health recordsInformatics

Identifiers

PMID38560278
PMCPMC10973665
OpenAlexW4391188938

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.