A systematic review of using clinical decision support systems in corneal diseases

• Published in: Digital health 2024-01, Vol.10, p.20552076241303805
• Main Authors: Ebrahimi, Farzad, Ayatollahi, Haleh, Zeraatkar, Kimia
• Format: Article
• Language: English
• Subjects: Review
• ISSN: 2055-2076; 2055-2076
• DOI: 10.1177/20552076241303805

Corneal diseases encompass a wide spectrum of eye diseases, and are among the leading causes of blindness. The use of clinical decision support systems (CDSSs) can assist physicians in timely diagnosis of these diseases and prevent their progression. The present study aimed to conduct a systematic review of using CDSSs in corneal diseases to identify gaps in the current knowledge and propose for future research in designing, implementation, and effective use of health information technology in ophthalmology, with a specific focus on corneal diseases. This systematic review was conducted in 2024. To retrieve relevant articles, PubMed, Web of Knowledge, Scopus, the Cochrane Library, IEEE Xplore, and ProQuest databases as well as Google Scholar were searched until end of September 2024. After assessing the quality of the articles and risk of bias, the results were reported descriptively. Out of 279 articles, only eight articles met the research criteria. The results showed that clinical decision support systems were mainly developed for diagnosing corneal diseases, referring patients with low vision for rehabilitation, and identifying extraocular muscle pathology in strabismus. The systems were developed using different programming languages, their input data were patient data and images, and the output was diagnosis and more information about diseases. Most of the systems were active and used a knowledge base. The performance of the systems was evaluated by comparing physicians' diagnosis and the system outputs, investigating users' perspectives, and calculating accuracy, specificity, and sensitivity values. The use of clinical decision support systems in corneal diseases leads to improve timely diagnosis, error reduction, and user satisfaction. However, further research is recommended to expand the use of new technologies such as artificial intelligence in the diagnosis of corneal diseases.