大数据
中国
描述性统计
在线和离线
业务
服务(商务)
秩(图论)
医疗保健
互联网隐私
家庭医学
医学
营销
计算机科学
数据挖掘
地理
政治学
统计
考古
组合数学
法学
操作系统
数学
作者
Donglei Yu,Yaolin Hu,Jian Wang,Stephen Nicholas,Elizabeth Maitland
标识
DOI:10.1177/20552076231182789
摘要
Objective Online medical consultation (OMC) is increasingly used in China, but there have been few in-depth studies of consultation arrangements and fee structures of online doctors in China. This research assessed the consultation arrangements and fee structure of OMC in China by undertaking a case study of obesity doctors from four representative OMC platforms. Methods Detailed information, including fees, waiting time and doctor information, was collected from four obesity OMC platforms and analyzed using descriptive statistical analysis. Results The obesity OMC platforms in China shared similarities in the use of big data and artificial intelligence (AI) but differed across service access, specific consultation arrangements and fees. Big data search and AI response technologies were used by most platforms to match users with doctors and reduce doctors’ pressure. The descriptive statistical analysis showed that the higher the rank of the online doctor, the higher the online fee and the longer the wait time. Through a comparison with offline hospitals, we found online doctors’ fees exceeded offline hospital doctors’ fees by up to 90%. Conclusions OMC platforms can gain competitive advantages over offline medical institutions through the following measures: make fuller use of big data and AI technologies to provide users with longer duration, lower cost and more efficient consultation services; provide better user experience than offline medical institutions; use big data and fee advantages to screen doctors to match users’ consultation needs instead of screening by the rank of doctors only; and cooperate with commercial insurance providers to provide innovative health care packages.
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