摘要
目的:分析疫情期间眼科互联网人工智能诊疗服务开展的方式和效果,为眼科医疗机构同行提供参考。方法:纵向观察性研究。观察分析2020年2月期间,患者通过在线专家问诊和人工智能咨询的人次总数、日平均数、每日不同时段数量、服务范围变化,同时与现场患者诊疗数量、2019年同期门急诊量进行比较。结果:中山眼科中心互联网医院线上服务患者共13543人次,线下现场服务患者共8223人次,未发现新冠肺炎病例。夜间时段线上人工智能问诊量远超线上、线下专家服务量。线上线下日均诊疗量显著高于2019年同期节假日门急诊日均水平。结论:眼科互联网人工智能诊疗服务与传统的眼病诊疗模式优势互补,在有效防控新冠疫情的同时,更大地满足了眼病防治需求,可作为新型医疗服务模式推广。
Objective:This study analyzed the operational mode and effectiveness of the ophthalmic internet hospital and its potential to serve the eye disease patients.Methods:This is a longitudinal observational study.We include the service amount of online ophthalmologist consultation,online AI consultation during February 2020,analyzing the total service amount,daily mean service amount,daily trend per hour,service modes transformation,etc.Comparison of clinical service was made between 2020 and 2019 in the corresponding period.Results:During February 2020,the internet hospital hosted by Zhongshan Ophthalmic Center provided online services for 13543,on-site services for 8223 person-time,with no COVID-19 pneumonia patients detected.For the analysis of daily trend per hour,the service amount of online AI consultation during off work exceeded that of consultation by ophthalmologists online or offline.The daily mean amount of service for online consultation and clinic service is significantly higher than 2019 in the corresponding period.Conclusion:The ophthalmic internet hospital is complementary to the traditional mode of ophthalmic disease management.The internet hospital contributed to serving the ophthalmic disease patients especially during the spreading of COVID-19.
作者
吴晓航
陈睛晶
刘臻臻
晏丕松
胡伟玲
吴子健
林怀德
王延东
吴雁凌
陈茗菲
张草贤
郑永欣
柳夏林
林晓峰
刘奕志
林浩添
WU Xiao-hang;CHEN Jing-jing;LIU Zhen-zhen(Zhongshan Ophthalmic Center,Sun Yat-Sen University,State Key Laboratory of Ophthalmology,Guangzhou 510060,Guangdong Province,P.R.C.)
出处
《中国数字医学》
2020年第9期6-11,共6页
China Digital Medicine
基金
国家重点研发计划项目(编号:2018YFC0116500)
广东省重点领域研发计划项目(编号:2018B010109008)。
关键词
互联网医院
人工智能
眼病诊疗
新冠肺炎
Internet hospital
artificial intelligence
ophthalmic disease diagnosis and treatment
COVID-19