ArticleApplied clinical informatics2023
Validation of an Automated Symptom-Based Triage Tool in Ophthalmology.
Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Real-World Performance of a New Online Eye Symptom Triage Tool (Eye+Dot) in an Emergency Eye Clinic: Mixed Methods Evaluation Study.JMIR human factors · 2026Article
- Real-World Evaluation of the Eye+Dot Online Triage Support Tool in Community Optometry Practices: Mixed Methods Evaluation Study.JMIR human factors · 2026Article
- Symptoms as an Indicator of Microbial Keratitis Severity and Its Association With Visual Acuity.Eye & contact lens · 2025Observational
- Ocular complaints and diagnoses in spaceflight.NPJ microgravity · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesAcute care ophthalmic clinics often suffer from inefficient triage, leading to suboptimal patient access and resource utilization. This study reports the preliminary results of a novel, symptom-based, patient-directed, online triage tool developed to address the most common acute ophthalmic diagnoses and associated presenting symptoms.
methodsA retrospective chart review of patients who presented to a tertiary academic medical center's urgent eye clinic after being referred for an urgent, semi-urgent, or nonurgent visit by the ophthalmic triage tool between January 1, 2021 and January 1, 2022 was performed. Concordance between triage category and severity of diagnosis on the subsequent clinic visit was assessed.
resultsThe online triage tool was utilized 1,370 and 95 times, by the call center administrators (phone triage group) and patients directly (web triage group), respectively. Of all patients triaged with the tool, 8.50% were deemed urgent, 59.2% semi-urgent, and 32.3% nonurgent. At the subsequent clinic visit, the history of present illness had significant agreement with symptoms reported to the triage tool (99.3% agreement, weighted kappa = 0.980,
conclusionThe automated ophthalmic triage algorithm was able to safely and effectively triage patients based on symptoms. Future work should focus on the utility of this tool to reduce nonurgent patient load in urgent clinical settings and to improve access for patients who require urgent medical care.
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