Appl Clin Inform 2023; 14(03): 448-454
DOI: 10.1055/a-2065-4613
Research Article

Validation of an Automated Symptom-Based Triage Tool in Ophthalmology

Autoren

  • Elana Meer#

    1   Department of Ophthalmology, Scheie Eye Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
    2   Department of Ophthalmology, University of California San Francisco, San Francisco, California, United States
  • Meera S. Ramakrishnan#

    1   Department of Ophthalmology, Scheie Eye Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Gideon Whitehead

    1   Department of Ophthalmology, Scheie Eye Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Damien Leri

    3   Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, Pennsylvania, United States
    4   Penn Medicine Center for Health Care Innovation, University of Pennsylvania Health System, Philadelphia, Pennsylvania, United States
  • Roy Rosin

    3   Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, Pennsylvania, United States
    4   Penn Medicine Center for Health Care Innovation, University of Pennsylvania Health System, Philadelphia, Pennsylvania, United States
  • Brian VanderBeek

    1   Department of Ophthalmology, Scheie Eye Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States

Funding None.

Abstract

Objectives Acute 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.

Methods A 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.

Results The 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, p < 0.001). The triage algorithm also had significant agreement with the severity of the physician diagnosis (97.0% agreement, weighted kappa = 0.912, p < 0.001). Zero patients were found to have a diagnosis on exam that should have corresponded to a higher urgency level on the triage tool.

Conclusion The 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.

Note

This study was presented at the Association for Research in Vision and Ophthalmology Meeting 2022.


Ethics Statement

This study was deemed exempt by the University of Pennsylvania Institutional Review Board as it was considered a quality improvement study with no risk or minimal risk to subjects, with all secondary analyses performed on nonidentifiable data.


Authors' Contributions

All authors contributed to the planning, conducting, and reporting of the work described in the article. M.S.R. and E.M. as guarantors for content accept full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish. E.M. attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. All listed authors have approved the present version of the manuscript.


Protection of Human and Animal Subjects

No interventions were performed on human subjects.


# Co-first authors. Elana Meer and Meera S. Ramakrishnan contributed equally to this work.




Publikationsverlauf

Eingereicht: 30. November 2022

Angenommen: 27. März 2023

Accepted Manuscript online:
29. März 2023

Artikel online veröffentlicht:
07. Juni 2023

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