Exploring the impact of free live-streamed medical consultation on patient engagement and patient satisfaction in the multistage online consultation process: A quasi-experimental design

IF 6.7 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Decision Support Systems Pub Date : 2025-02-12 DOI:10.1016/j.dss.2025.114422

Haochen Song , Xitong Guo , Tianshi Wu

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引用次数: 0

Abstract

In recent years, many online healthcare communities (OHCs) in China introduced the feature of free live-streamed medical consultations (FLSMC), which allows patients to communicate with physicians and have an interactive consultation for free through live streaming. Despite the rapid growth of FLSMC, little is known about whether FLSMC can bring benefits to patients when they have online consultation needs in the future. Drawing on signaling theory, this study examines the impact of FLSMC on patient engagement and patient satisfaction in the multistage online consultation process. We further explore the moderating effects of physician's owned and earned signals in the pre-consultation stage by integrating social capital theory with signaling theory. We collect a panel data set of 16,151 physicians from a leading OHC in China. Based on the DID method, a quasi-experimental design, and the instrumental variable method, we demonstrate that FLSMC has a positive effect on patient choice, patient messaging, and patient satisfaction. In addition, we find that the physician's title and online rating can positively moderate the effects of FLSMC on patient choice. This study not only sheds light on the literature on online healthcare by identifying the role of signals in the context of FLSMC, but also provides decision support for patients, physicians, and OHC managers.

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来源期刊

Decision Support Systems 工程技术-计算机：人工智能

CiteScore

14.70

自引率

6.70%

发文量

119

审稿时长

13 months

期刊介绍： The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).