Artificial Intelligence Improves Patient Follow-Up in a Diabetic Retinopathy Screening Program

Abstract

Eliot R Dow,1– 3 Karen M Chen,1 Cindy S Zhao,1 Austen N Knapp,1 Anuradha Phadke,4 Kirsti Weng,4 Diana V Do,1 Vinit B Mahajan,1 Prithvi Mruthyunjaya,1 Theodore Leng,1 David Myung1,2 1Department of Ophthalmology, Byers Eye Institute at Stanford, Palo Alto, CA, USA; 2Department of Ophthalmology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; 3Department of Ophthalmology, Duke Eye Center, Durham, NC, USA; 4Department of Internal Medicine, Stanford Health Care, Palo Alto, CA, USACorrespondence: David Myung, Byers Eye Institute at Stanford, Palo Alto, CA, 94303, USA, Tel [phone], Email [email protected]: We examine the rate of and reasons for follow-up in an Artificial Intelligence (AI)-based workflow for diabetic retinopathy (DR) screening relative to two human-based workflows.Patients and Methods: A DR screening program initiated September 2019 between one institution and its affiliated primary care and endocrinology clinics screened 2243 adult patients with type 1 or 2 diabetes without a diagnosis of DR in the previous year in the San Francisco Bay Area. For patients who screened positive for more-than-mild-DR (MTMDR), rates of follow-up were calculated under a store-and-forward human-based DR workflow (“Human Workflow”), an AI-based workflow involving IDx-DR (“AI Workflow”), and a two-step hybrid workflow (“AI–Human Hybrid Workflow”). The AI Workflow provided same-day results, whereas the other workflows took 1– 5 days. Patients were surveyed by phone about follow-up decisions.Results: Under the AI Workflow, 279 patients screened positive for MTMDR. Of these, 69.2% followed up with an ophthalmologist within 90 days. Altogether 70.5% (N=48) of patients who followed up chose their location based on primary care referral. Under the Human Workflow and AI–Human Hybrid Workflow, 12.0% (N=14/117) and 11.7% (N=12/103) of patients with a referrable screening result followed up compared to 35.5% of patients under the AI Workflow (N=99/279; χ2df=2 = 36.70, p < 0.00000001).Conclusion: Ophthalmology follow-up after a positive DR screening result is approximately three-fold higher under the AI Workflow than either the Human Workflow or AI–Human Hybrid Workflow. Improved follow-up behavior may be due to the decreased time to screening result.Keywords: telemedicine, teleophthalmology, fundus photography, deep learning, machine learning, referral

Keywords

• telemedicine
• teleophthalmology
• fundus photography
• deep learning
• machine learning
• referral