Patient Perspectives on Artificial Intelligence-Based Diabetic Retinopathy Screening at an Urban US Medical Center

Area of Science:

• Ophthalmology
• Artificial Intelligence
• Medical Imaging

Background:

• Diabetic retinopathy (DR) screening is crucial for preventing vision loss in diabetes patients.
• Fully autonomous artificial intelligence (AI) offers potential to improve access and efficiency in DR screening.
• Patient perspectives are essential for the successful implementation of novel healthcare technologies like AI in DR screening.

Purpose of the Study:

• To explore patient perspectives on the use of AI in diabetic retinopathy (DR) screening.
• To assess patient awareness, trust, perceived efficiency, and overall receptivity towards AI in eye care.
• To understand patient preferences regarding physician interaction and oversight in AI-assisted DR screening.

Main Methods:

• A survey was administered to 100 adults with diabetes undergoing DR screening with a handheld AI fundus camera.
• Participants responded to questions on AI awareness, trust, efficiency, personal interaction preferences, and overall acceptance.
• Responses were analyzed and stratified by sociodemographic and neighborhood characteristics.

Main Results:

• Most participants (78%) were aware of AI in healthcare, but only 46% knew of its application to eye disease.
• While 76% were comfortable with AI in eye exams and 92% satisfied, 83% preferred physician oversight.
• Only 31% believed AI could replace a doctor visit, with 94% affirming doctors' ultimate diagnostic responsibility.

Conclusions:

• Patients generally accept AI as part of DR screening but value physician supervision.
• A significant gap exists between the concept of fully autonomous AI screening and patient expectations of physician involvement.
• Implementation strategies for autonomous AI DR screening must address patient understanding and preferences for physician roles.