Application of the Sight Outcomes Research Collaborative Ophthalmology Data Repository for Triaging Patients With Glaucoma and Clinic Appointments During Pandemics Such as COVID-19

Abstract

; SOURCE Consortium IMPORTANCE During the coronavirus disease 2019 (COVID-19) pandemic, eye care professionals caring for patients with sight-threatening diseases, such as glaucoma, have had to determine whether some patient appointments could safely get postponed, weighing the risk that the patient's glaucoma could worsen during the interim vs the morbidity risk of acquiring COVID-19 while seeking ophthalmic care. They also need to prioritize appointment rescheduling during the ramp-up phase (when pandemic-associated service reductions are eased). OBJECTIVE To describe a flexible and scalable scoring algorithm for patients with glaucoma that considers glaucoma severity and progression risk vs the presence of high-risk features for morbidity from COVID-19, using information from a large data repository. DESIGN, SETTING, AND PARTICIPANTS In this cross-sectional study, patients with upcoming clinic appointments for glaucoma from March 16, 2020, to April 16, 2020, at an academic institution enrolled in the Sight Outcomes Research Collaborative (SOURCE) Ophthalmology Electronic Health Record Data Repository were identified. A risk stratification tool was developed that calculated a glaucoma severity and progression risk score and a COVID-19 morbidity risk score. These scores were summed to determine a total score for each patient. MAIN OUTCOMES AND MEASURES Total scores and percentages of clinic appointments recommended for rescheduling. RESULTS Among the 1034 patients with upcoming clinic appointments for glaucoma, the mean (SD) age was 66.7 (14.6) years. There were 575 women (55.6%), 733 White individuals (71%), and 160 Black individuals (15.5%). The mean (SD) glaucoma severity and progression risk score was 4.0 (14.4) points, the mean (SD) COVID-19 morbidity risk score was 27.2 (16.1) points, and the mean (SD) total score was 31.2 (21.4) points. During pandemic-associated reductions in services, using total score thresholds of 0, 25, and 50 points would identify 970 appointments (93.8%), 668 appointments (64.6%), and 275 appointments (26.6%), respectively, for postponement and rescheduling. The algorithm-generated total scores also helped prioritize appointment rescheduling during the ramp-up phase. CONCLUSIONS AND RELEVANCE A tool that considers the risk of underlying ophthalmic disease progression from delayed care receipt and the morbidity risk from COVID-19 exposure was developed and implemented, facilitating the triage of upcoming ophthalmic appointments. Comparable approaches for other ophthalmic and nonophthalmic care during the COVID-19 pandemic and similar crises may be created using this methodology.

Ocular and Systemic Complications of COVID-19: Impact on Patients and Healthcare

“…Adaptations to ophthalmic clinical and emergency services included referral for virtual consultations when possible, minimizing wait times, isolating care teams, and using triaging algorithms. 1,61,62 The American Academy of Ophthalmology, Centers for Disease Control, World Health Organization, and American Society of Retina Surgeons released clinical guidelines. 1 At the National Center for Global Health and Medicine in Japan, flowcharts were created for hospitalists to determine whether to consult ophthalmology for hospitalized patients with COVID-19, based on the consciousness levels and ocular https://doi.org/10.2147/OPTH.S336963…”

“… 63 At the University of Michigan, a risk stratification tool was used to determine patients’ glaucoma severity and risk of glaucoma progression using the Sight Outcomes Research Collaborative (SOURCE) ophthalmology electronic health data repository data to determine when the patients should be evaluated in clinic. 62 The Royal College of Ophthalmologists released guidelines to prioritize urgent and emergent ophthalmic care, including maintaining anti-VEGF therapy every 8 weeks for patients with neoavascular age-related macular degeneration and consider deferring injections for most patients with macular edema from diabetes mellitus or vein occlusions. 64 …”

Diagnostik von Erkrankungen des Sehnervenkopfes in Zeiten von künstlicher Intelligenz und Big Data

“…Bommakanti et al. entwickelten und implementierten beispielsweise ein Tool, welches das individuelle Risiko eines Fortschreitens einer Augenerkrankung – wie einem Glaukom – durch eine verzögerte Inanspruchnahme der Versorgung und das Morbiditätsrisiko durch eine COVID-19-Exposition berücksichtigt und die Triage anstehender Augenarzttermine erleichtert [ 13 ]. Weitere Möglichkeiten von strukturierten großen Datensätzen sind die Anwendung von KI für eine Segmentierung und Klassifikation oder Prädiktion des Krankheitsverlaufs.…”

Evaluation of the Nallasamy Formula: A Stacking Ensemble Machine Learning Method for Refraction Prediction in Cataract Surgery

“…Various studies using data from SOURCE were published. [9][10][11][12][13] Institutional review board approval was obtained for the presented study. All subjects were fully anonymized and, therefore an informed consent was not required for this retrospective study.…”