Hongkang Wu , Kai Jin , Chee Chew Yip , Victor Koh , Juan Ye
{"title":"基于人工智能的眼病筛查经济评估系统回顾:从可能性到现实性。","authors":"Hongkang Wu , Kai Jin , Chee Chew Yip , Victor Koh , Juan Ye","doi":"10.1016/j.survophthal.2024.03.008","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial Intelligence (AI) has become a focus of research in the rapidly evolving field of ophthalmology. Nevertheless, there is a lack of systematic studies on the health economics of AI in this field. We examine studies from the PubMed, Google Scholar, and Web of Science databases that employed quantitative analysis, retrieved up to July 2023. Most of the studies indicate that AI leads to cost savings and improved efficiency in ophthalmology. On the other hand, some studies suggest that using AI in healthcare may raise costs for patients, especially when taking into account factors such as labor costs, infrastructure, and patient adherence. Future research should cover a wider range of ophthalmic diseases beyond common eye conditions. Moreover, conducting extensive health economic research, designed to collect data relevant to its own context, is imperative.</p></div>","PeriodicalId":22102,"journal":{"name":"Survey of ophthalmology","volume":"69 4","pages":"Pages 499-507"},"PeriodicalIF":5.1000,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0039625724000250/pdfft?md5=79f6dd094ed937590fca0bbb1338be40&pid=1-s2.0-S0039625724000250-main.pdf","citationCount":"0","resultStr":"{\"title\":\"A systematic review of economic evaluation of artificial intelligence-based screening for eye diseases: From possibility to reality\",\"authors\":\"Hongkang Wu , Kai Jin , Chee Chew Yip , Victor Koh , Juan Ye\",\"doi\":\"10.1016/j.survophthal.2024.03.008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Artificial Intelligence (AI) has become a focus of research in the rapidly evolving field of ophthalmology. Nevertheless, there is a lack of systematic studies on the health economics of AI in this field. We examine studies from the PubMed, Google Scholar, and Web of Science databases that employed quantitative analysis, retrieved up to July 2023. Most of the studies indicate that AI leads to cost savings and improved efficiency in ophthalmology. On the other hand, some studies suggest that using AI in healthcare may raise costs for patients, especially when taking into account factors such as labor costs, infrastructure, and patient adherence. Future research should cover a wider range of ophthalmic diseases beyond common eye conditions. Moreover, conducting extensive health economic research, designed to collect data relevant to its own context, is imperative.</p></div>\",\"PeriodicalId\":22102,\"journal\":{\"name\":\"Survey of ophthalmology\",\"volume\":\"69 4\",\"pages\":\"Pages 499-507\"},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2024-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0039625724000250/pdfft?md5=79f6dd094ed937590fca0bbb1338be40&pid=1-s2.0-S0039625724000250-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Survey of ophthalmology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0039625724000250\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OPHTHALMOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Survey of ophthalmology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0039625724000250","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
人工智能(AI)已成为快速发展的眼科领域的研究重点。然而,在这一领域缺乏有关人工智能健康经济学的系统研究。本综述研究了截至 2023 年 7 月从 PubMed、Google Scholar 和 Web of Science 数据库中检索到的采用定量分析的研究。大多数研究表明,人工智能可节省眼科成本并提高效率。另一方面,一些研究表明,在医疗保健领域使用人工智能可能会增加患者的成本,尤其是在考虑到劳动力成本、基础设施和患者依从性等因素的情况下。未来的研究应涵盖常见眼科疾病以外的更多眼科疾病。此外,为了促进人工智能在中国的临床应用,中国必须开展广泛的卫生经济研究,以收集与自身情况相关的数据。
A systematic review of economic evaluation of artificial intelligence-based screening for eye diseases: From possibility to reality
Artificial Intelligence (AI) has become a focus of research in the rapidly evolving field of ophthalmology. Nevertheless, there is a lack of systematic studies on the health economics of AI in this field. We examine studies from the PubMed, Google Scholar, and Web of Science databases that employed quantitative analysis, retrieved up to July 2023. Most of the studies indicate that AI leads to cost savings and improved efficiency in ophthalmology. On the other hand, some studies suggest that using AI in healthcare may raise costs for patients, especially when taking into account factors such as labor costs, infrastructure, and patient adherence. Future research should cover a wider range of ophthalmic diseases beyond common eye conditions. Moreover, conducting extensive health economic research, designed to collect data relevant to its own context, is imperative.
期刊介绍:
Survey of Ophthalmology is a clinically oriented review journal designed to keep ophthalmologists up to date. Comprehensive major review articles, written by experts and stringently refereed, integrate the literature on subjects selected for their clinical importance. Survey also includes feature articles, section reviews, book reviews, and abstracts.