OR WAIT null SECS
An analysis of the STATUS program suggests the percentage of patients that received an annual eye exam increased from 65.2% to 72.8% in the clinics utilizing the IDx-DR system.
Diabetic eye exams increased in community clinics utilizing an artificial intelligence-based screening system, according to new research presented at the 2023 Association for Research in Vision and Ophthalmology (ARVO) Annual Meeting in New Orleans, Louisiana.1
As a result, the investigative team, led by Austen N Knapp, MD, Byers Eye Institute, Stanford Medicine, suggests in-person follow-up may see an increase with the use of artificial intelligence in remote diabetic retinopathy detection.
“Incorporating artificial intelligence into a remote diabetic retinopathy detection workflow may increase in-person follow-up compared to teleophthalmology alone,” investigators wrote.
Artificial intelligence-based testing platforms for diabetic retinopathy have recently been introduced in clinical use, but there is a paucity of outcomes data on their use. Knapp and colleagues performed a retrospective observational study to report real-world outcomes of follow-up and accessibility to ophthalmologic care in patients with diabetic retinopathy using a community, artificial intelligence-based testing program.
The program called the Stanford Teleophthalmology Autonomous Testing and Universal Screening (STATUS) utilizes the FDA-cleared autonomous AI technology, IDx-DR, to detect diabetic retinopathy. It is used in 7 primary-care and endocrinology clinics in the San Francisco Bay area. Adults with type 1 diabetes (T1D) or type 2 diabetes (T2D) who did not have a prior diagnosis of diabetic retinopathy and dilated fundus exam in the prior 12 months were offered inclusion in the program.
A medical assistant in the clinic collected 2 nonmydriatic fundus images of each eye – one 45-degree image centered on the macula and one centered on the optic disc. Investigators graded sufficient images on the presence or absence of referral-warranted more-than-mild diabetic retinopathy (MTMDR), defined as Early Treatment Diabetic Retinopathy Study (ETDRS) level ≥35, and/or diabetic macular edema (DME), in ≥1 eye. Those with MTMDR or an ungradable image were referred for an ophthalmologic exam.
Knapp and colleagues collected patient demographics and characteristics from those with referrable diseases. Additionally, a random sample of patients was given a survey regarding their experience and follow-up.
Over a 12-month period, a total of 1222 patients were screened with IDx-DR and 145 patients (12%) were diagnosed with MTMDR and referred for in-person ophthalmologic evaluation. Of this population, 93 patients (64.1%) saw an ophthalmologist at a median of 60 days after the screening visit.
Data showed 30.3% of patients were referred after an artificial intelligence-based exam followed up at the university-based eye institute, compared with 11.5% of people referred for follow-up after teleophthalmology screening.
Moreover, Knapp and colleagues indicated the percentage of patients receiving an annual eye exam increased from 65.2% to 72.8% in the clinics utilizing IDx-DR. They noted this exceeded the 90th percentile national benchmark (67.89%) for the Healthcare Effectiveness Data and Information Set (HEDIS) quality measure.
References
Related Content: