Ebrahimi Farzad, Ayatollahi Haleh, Zeraatkar Kimia
School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Health Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran.
Digit Health. 2024 Dec 10;10:20552076241303805. doi: 10.1177/20552076241303805. eCollection 2024 Jan-Dec.
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.
角膜疾病涵盖了广泛的眼部疾病，是导致失明的主要原因之一。临床决策支持系统（CDSS）的使用可以帮助医生及时诊断这些疾病并防止其进展。
本研究旨在对角膜疾病中CDSS的应用进行系统评价，以找出当前知识中的差距，并为眼科健康信息技术的设计、实施和有效应用方面的未来研究提出建议，特别关注角膜疾病。
这项系统评价于2024年进行。为检索相关文章，检索了PubMed、Web of Knowledge、Scopus、Cochrane图书馆、IEEE Xplore和ProQuest数据库以及谷歌学术，直至2024年9月底。在评估文章质量和偏倚风险后，对结果进行描述性报告。
在279篇文章中，只有8篇文章符合研究标准。结果表明，临床决策支持系统主要用于诊断角膜疾病、将低视力患者转诊进行康复治疗以及识别斜视中的眼外肌病变。这些系统使用不同的编程语言开发，其输入数据为患者数据和图像，输出为诊断结果和更多关于疾病的信息。大多数系统处于活跃状态并使用知识库。通过比较医生的诊断结果和系统输出、调查用户观点以及计算准确性、特异性和敏感性值来评估系统的性能。
在角膜疾病中使用临床决策支持系统有助于提高及时诊断率、减少错误并提高用户满意度。然而，建议进一步开展研究以扩大人工智能等新技术在角膜疾病诊断中的应用。
