Abstract
Purpose: The method of diagnosing diabetic retinopathy (DR) through artificial intelligence (AI)-based systems has been commercially available since 2018. This introduces new ethical challenges with regard to obtaining informed consent from patients. The purpose of this work is to develop a checklist of items to be disclosed when diagnosing DR with AI systems in a primary care setting.Methods: Two systematic literature searches were conducted in PubMed and Web of Science databases: a narrow search focusing on DR and a broad search on general issues of AI-based diagnosis. An ethics content analysis was conducted inductively to extract two features of included publications: (1) novel information content for AI-aided diagnosis and (2) the ethical justification for its disclosure.Results: The narrow search yielded n = 537 records of which n = 4 met the inclusion criteria. The information process was scarcely addressed for primary care setting. The broad search yielded n = 60 records of which n = 11 were included. In total, eight novel elements were identified to be included in the information process for ethical reasons, all of which stem from the technical specifics of medical AI.Conclusions: Implications for the general practitioner are two-fold: First, doctors need to be better informed about the ethical implications of novel technologies and must understand them to properly inform patients. Second, patient's overconfidence or fears can be countered by communicating the risks, limitations, and potential benefits of diagnostic AI systems. If patients accept and are aware of the limitations of AI-aided diagnosis, they increase their chances of being diagnosed and treated in time.
Highlights
The timely referral of patients with diabetic retinopathy (DR) to ophthalmic examination is crucial to avoid visual impairment and blindness [1]
A novel and unique feature of this Artificial intelligence (AI)-aided device requires a critical assessment: the IDx-DR intentionally generates an autonomous recommendation that is a diagnosis without needing the oversight of a physician, physicians are normally responsible for diagnosis
The research question is as follows: What new information should be included in the information process to ethically secure informed consent when AI is used for DR diagnosis? To answer this question, we developed a list of contents and their ethical justification based on a systematic literature search
Summary
The timely referral of patients with diabetic retinopathy (DR) to ophthalmic examination is crucial to avoid visual impairment and blindness [1]. The system, called IDx-DR, runs on a retinal camera (Topcon NW400) and analyzes images of the eye utilizing an AI algorithm [6]. The system’s output is a recommendation either to refer patients to an eye care professional when it identifies more than mild DR or to suggest rescreening in 12 months. It is the first device that provides an autonomous screening decision, receiving market approval by the US Food and Drug Administration (FDA) [5]. A novel and unique feature of this AI-aided device requires a critical assessment: the IDx-DR intentionally generates an autonomous recommendation that is a diagnosis without needing the oversight of a physician, physicians are normally responsible for diagnosis
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