June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Symptom Based Triage Tool in Ophthalmology
Author Affiliations & Notes
  • Elana Meer
    Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Meera Suja Ramakrishnan
    Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Gideon Whitehead
    Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Brian L VanderBeek
    Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Footnotes
    Commercial Relationships   Elana Meer None; Meera Ramakrishnan None; Gideon Whitehead None; Brian VanderBeek None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 2796 – A0126. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Elana Meer, Meera Suja Ramakrishnan, Gideon Whitehead, Brian L VanderBeek; Symptom Based Triage Tool in Ophthalmology. Invest. Ophthalmol. Vis. Sci. 2022;63(7):2796 – A0126.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose : Acute care ophthalmic clinics can suffer from call overload and inefficient triage, leading to suboptimal patient access. An automated symptom checker and triage tool may offload the call volume while creating a more efficient and effective system for matching patients with their appropriate level of care. Here we describe the development and preliminary results from a novel automated ophthalmology triage tool.

Methods :
A symptom based triage algorithm was developed using the Wills Eye Manual and literature searches of acute ophthalmic diagnoses.[1] This patient facing automated algorithm (Figure 1) used a series of questions and answers to triage patients into 3 different acuity levels based on duration and characterization of symptoms (i.e. eye pain, blurry vision, flashes/floaters, eyelid lesions, etc): 1. Urgent: Same day appointment 2. Semi-Urgent: Appointment in less than 4 weeks 3. Non-Urgent: Appointment in 4 - 9 weeks.

The automated triage tool was built into an academic eye institution’s website, available to both patients and non-clinical personnel for triaging eye-related symptoms. Upon completion of the tool, results were sent via an automatically generated email along with the patient information for review by an ophthalmic technician who would schedule the patient based on triage output.

Basic descriptive statistics were used to present demographic data, tool usage data, and time from symptom presentation to care access across the call center and patient-facing website.

Results :
Via the call center and the clinical website, the automated triage tool was used 1370 and 95 times, respectively. 66.7% of patients utilizing the tool were female, 50.7% identified as African-American, 28.7% Caucasian, 4.4% Asian, and 9.8% Hispanic/Latino. Among call center triage tool users, 33.5% were triaged to non-urgent, 60.4% were triaged to semi-urgent, and 6.1% were triaged to urgent same-day appointments. Among patient-facing website triage tool users, 15.5% were triaged to non-urgent, 39.7% were triaged to semi-urgent, and 44.8% were triaged to urgent same-day appointments.

Conclusions :
Automated Triage algorithms may be beneficial by offloading non-acute phone calls and clinical volume. Similarly, it can be used by non-clinically oriented staff members to guide clinical judgements. Additional work should focus on validation and electronic implementation into EHR systems.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

 

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×