Abstract
ABSTRACT Misdiagnosis of retinal disease is a common problem in primary care that can lead to irreversible vision loss and false-positive referrals, resulting in inappropriate use of health services. Clinical decision support systems describe tools that leverage information technology to provide timely recommendations that assist clinicians in the decisions they make about the care of a patient. They, therefore, have the potential to reduce the rate of misdiagnosis by promoting evidence-based medicine and more effective and efficient healthcare. This narrative review aims to support primary care practitioners in better understanding the current and emerging capacity of clinical decision support systems in eye care. Different types of clinical decision support systems are discussed, using current examples and evidence from the available literature to demonstrate how they may improve diagnostic effectiveness and aid the management of retinal disease. Comments are made on the future directions of clinical decision support in primary eye care and the potential applications of artificial intelligence.
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