diabetic retinopathy screening point-of-care artificial intelligence

Conditions: Diabetic Retinopathy (DR)

Summary: this research study is being conducted to improve eye care by using artificial intelligence (ai) to make diabetic eye screenings faster and more accessible. ai technology mimics human decision-making, enabling computers and systems to analyze medication information. specifically for this screening, ai examines digital images of the eye and based on that information, may identify if a participant has diabetic retinopathy. it can assist doctors in making decisions about a participant's diagnosis, treatment or care plans to improve patient care. this is a collaboration between san ysidro health (syhealth), university of california, san diego (uc san diego), and eyenuk. the kaiser permanente augmented intelligence in medicine and healthcare initiative (aim-hi) awarded syhealth funds to demonstrate the value of ai technologies in diverse, real-world settings.

this study is intended to address unmet medical needs in diabetic eye care in a community health center setting by enhancing and modifying existing clinical practices with the integration of point-of-care (poc) artificial intelligence (ai) technology for diabetic retinopathy (dr) screening. using a special camera and a computer system called eyeart® to make diabetic eye screenings faster and more accessible. eyeart®, is a food drug and administration (fda)-cleared device system for fast, non-invasive diabetic retinopathy screening. this non-invasive dr screening does not require dilation and provides immediate results and facilitates informed discussions with their primary care provider. this study will optimize, implement, and test the impact of a multicomponent intervention that includes: 1) autonomous dr screening, a fast and non-invasive retinal exam into the primary care settings with 2) integration of the results into the ehr and 3) health education/care coordination support (e.g., patient education). primary objective (clinical): evaluate the implementation and effectiveness of a multicomponent ai clinical intervention on dr screenings rate, early stages of dr detection, and referrals to the specialist for follow up on abnormal results. secondary objectives: evaluate the implementation and effectiveness of a multicomponent ai clinical intervention on dr knowledge, attitudes, self-efficacy, and patient satisfaction. participants will be active syhealth patients 22 years of age or older with diabetes mellitus (dm) who have not had a retinal exam in the last 11 months, and have a medical visit scheduled during the intervention period and are able to read and understand either english or spanish in order to provide informed consent and complete study surveys. exclusion criteria: 1) have a prior diagnosis of dr, macular edema, or retinal vascular occlusion; 2) have persistent visual impairment in one or both eyes; 3) history of ocular injections, laser treatment of the retina, or intraocular surgery (excluding cataract surgery); 4) pregnant women; and 5) diagnosis of mental or degenerative disease that prevents self-consent for the study. the study will recruit a cohort of 848 adults from two syhealth clinic sites. once the potential participants arrive at their study visit appointment, they will complete the consent process, pre-survey (knowledge, attitudes and self-efficacy about diabetes and eye health). participants will be randomized into either the dr screening-ai-intervention or retinal screening usual care groups and continue study activities as follows: 1. participants assigned to the dr screening-ai-intervention group will undergo dr screening in-clinic prior to the medical visit using a special camera and the eyeart® artificial intelligence (ai) system (eyenuk, inc.), an fda-cleared ai device for fast, non-invasive dr screening. this screening, which does not require dilation, uses a camera with a smart computer technology using ai that can detect signs of significant diabetic retinopathy in less than five minutes. these results will be immediately integrated into the electronic health record (ehr), enabling informed discussions with their primary care provider at the time of their medical visit and will automatically generate the referrals to an eye specialist for participants with abnormal findings. participants will receive a copy of the results immediately after completion of the screening. after the screening, participants will receive a copy of the results of the screening, health education information on dr and eye health before completing their baseline study visit. subsequently, they will proceed with their medical visit to ensure continuity of their diabetes care. 2. participants in the retinal screening usual care group will receive assistance from the ra to schedule the appointment with an eye care provider according to syhealth's protocols for routine retinal screening, which includes dilation. after the ra scheduled the visit with the eye care provider, participants will receive health education information on dr and eye health before completing their baseline study visit. subsequently, they will proceed with their medical visit to ensure continuity of their diabetes care. appointments with the eye care provider are usually at a different clinic location based on availability, and the retinal screenings are not completed on the same day of the medical visit with their primary care provider. at the time of the visit with the eye care provider will discuss the retinal screening results with the participant and may conduct a comprehensive eye exam, submitting referrals for any abnormal results.

Eligibility criteria:
inclusion criteria: 1. capacity to provide informed consent. individuals must have the capacity to understand the study information, risks, and benefits and voluntarily provide informed consent. 2. stated willingness to comply with all study procedures and availability for the duration of the study. 3. established and active patient of syhealth-cv and kc (having a medical appointment in the last 18 months). 4. person aged 22 and older. 5. established diagnosis of dm. 6. medical appointment(s) (in-person or telehealth) scheduled during the intervention period. 7. has not completed a dilated eye exam or retinal exam in the last 11months. exclusion criteria: 1. have a prior diagnosis of dr, macular edema, or retinal vascular occlusion; 2. have persistent visual impairment in one or both eyes; 3. history of ocular injections, laser treatment of the retina, or intraocular surgery (excluding cataract surgery); 4. pregnant women; and 5. diagnosis of mental or degenerative disease that prevents self-consent for the study.

Keywords: point-of-care (poc) artificial intelligence (ai) technology for dr screening diabetic retinopathy (dr) screening diabetes