Implementing an AI Diabetic Retinopathy Screening Program in Primary Care
Optometrist Juan Ding, OD, PhD (above) and co-investigator James Ledwith, MD, assistant professor of Family Medicine and Community Health, were awarded the annual Herman G. Berkman Diabetes Clinical Innovation grant to implement an artificial intelligence (AI) diabetic retinopathy screening program in Family Medicine clinics to identify eye disease and improve comprehensive care for people living with diabetes.
“Despite vast improvements in screening and treatment of diabetic retinopathy in previous years, it remains a leading cause of vision loss in the United States,” said Dr. Ding, Director of Optometry Service, UMass Eye Center. “Many people face barriers to accessing quality eye care, including income, transportation, and health insurance. It’s important to improve methods of screening for diabetic retinopathy and make it widely available.”
Recent studies have identified AI-based algorithms as promising tools for screening and early identification of diabetic retinopathy, helping to identify those at risk. UMass Memorial Health partnered with digital health company AEYE Health to test the diagnostic accuracy of a handheld AI-assisted camera designed for primary care physicians to screen at-risk individuals for retinal changes indicative of diabetic retinopathy.
The Berkman Fund will support efficient retinal imaging at primary care locations, and the program will analyze the impact of offering primary care screening and its sustainability. "Many of our practices only have completion rates of 30-40% for the annual retinopathy exam, reaching 60% in a few well-resourced sites," said Dr. Ledwith. "Many factors contribute to this; however, we expect performing the initial screening during routine primary care visits to improve screening rates and early disease detection greatly."
The current screening process requires primary care physicians to refer all their patients to an ophthalmologist for an annual eye exam. During this pilot program, people with diabetes who visit their primary care physician or nurse practitioner at UMass Memorial HealthAlliance Fitchburg Family Practice may be screened for retinopathy by a medical assistant or resident using an AI-assisted retinal camera. Retinal images from each eye are uploaded to a cloud-based service, which provides a report to the physician within a minute. If necessary, the patient can be referred to Dr. Ding or one of her colleagues at the UMass Memorial Eye Center for further evaluation.
“This technology may also be offered to patients within the UMass Memorial diabetes clinic to screen for eye disease so we can address it immediately,” said Dr. Ding.
Herman G. Berkman Diabetes Clinical Innovation Fund Recipients
On-Demand Diabetes Education Videos for Patients and Families
A series of short, on-demand videos addressing common diabetes topics, will be created, including blood glucose monitoring, insulin use, sick-day management and diabetes technology. The evidence-based videos are designed to reinforce, not replace, education provided by Certified Diabetes Care and Education Specialists. Patients, families and caregivers will be able to watch, pause and replay the videos as needed, providing convenient online access to reliable diabetes information. The project, led by nurse practitioner Clare Foley, DNP, and Adam Edelstein, also aims to make the videos available broadly throughout UMass Memorial Health so providers can easily share them electronically.
Using Artificial Intelligence to Improve Diabetes Medication Safety After Hospital Discharge
This project will develop and test an artificial intelligence tool designed to help patients better understand changes to their diabetes medications when leaving the hospital. The goal is to reduce misunderstandings and help patients return home with greater knowledge and confidence to safely manage their diabetes medications. The team consisting of Alok Kapoor, MD, Adrian Zai, MD, PhD, and Alexandra Albert, MD, PhD, will evaluate the tool's accuracy, safety and usability with patients starting new diabetes medications or whose medications changed during hospitalization.
Clinical Study on Diabetes Management During Pregnancy
A clinical study at UMass Memorial Medical Center is comparing continuous glucose monitoring (CGM) to multiple daily fingersticks for pregnant women with type 2 diabetes. The randomized study, led by Gianna Wilkie, MD, Assistant Professor of Obstetrics and Gynecology, was awarded funds to conduct includes maternal blood glucose control, patient satisfaction, and other perinatal outcomes.
Implementing a Liver Disease Screening Process in the Adult Diabetes Clinic
Liver disease is strongly associated with type 2 diabetes and obesity. It remains underdiagnosed and undertreated, and many people living with T2D are unaware they have it. This project, led by endocrinologist Madona Azar, MD, implemented a new process in the UMass Memorial diabetes clinic that uses a screening tool to analyze clinically available data to determine patients' risk of liver fibrosis.
AI Diabetic Retinopathy Screening in Primary Care
This project implemented an artificial intelligence (AI)- based diabetic retinopathy screening program in Family Medicine clinics to detect eye disease and improve comprehensive care for people living with diabetes. Recent studies have identified AI-based algorithms as promising tools for screening and early detection of diabetic retinopathy, helping those at risk. This study, led by optometrist Juan Ding, OD, PhD, tested the diagnostic accuracy of a hand-held AI-assisted camera used by primary care physicians to screen at-risk individuals for retinal changes indicative of diabetic retinopathy.
Analying the Benefits of Continuous Glucose Monitors to Reduce Hospitalizations and Diabetic Complications
This randomized clinical trial provided continuous glucose monitors (CGM) to people with diabetes who were currently not using one and arrived at the Emergency Room with high or low blood sugar, or other diabetes-related complications. The recently completed study, led by endocrinologist Dr. Mark O’Connor, analyzes whether CGM successfully prevents people from returning to the ER with diabetes-related issues, compared with the control group who do not wear a device to monitor their blood sugar.
Improving Inpatient Blood Glucose Management
This project aimed to implement a carbohydrate-counting system for hospitalized inpatients with diabetes across the UMass Memorial Health system. Endocrinologist Leslie Domalik, MD, evaluated whether adopting a flexible meal dosing option based on carb counting would improve the outcomes of hospitalized patients with diabetes. By coordinating the timing of blood glucose testing, insulin dosing, and the administration of rapid-acting mealtime insulin, she wanted to ensure carbohydrate counts are listed for all food served to hospitalized patients and to better coordinate insulin delivery with meal delivery.
Improving Care Access for the Highest Risk Diabetes Patients
The inaugural Herman Berkman Diabetes Clinical Innovation funding was awarded to Daniel Amante, PhD, and Adarsha Bajracharya, MD, in 2019. It led to Dr. Amante receiving a three-year KL2 Mentored Career Development Training grant to develop a Diabetes Mellitus program using Behavioral economics to Optimize Outreach and Self-management support with Technology (DM-BOOST).
ID PLUS Care was a multidisciplinary, collaborative approach to improve care access, quality, and management for at-risk patients with diabetes. The program monitored Electronic Health Record data to identify UMass Medicare Accountable Care Organization patients at risk for negative outcomes and proactively contacted them to nudge them toward recommended services.