Better interaction performance attracts more chronic patients? Evidence from an online health platform

杠杆(统计) 背景(考古学) 心理学 医学 家庭医学 计算机科学 生物 机器学习 古生物学
作者
Huan Liu,Yao Zhang,Yuelin Li,Kendra Albright
出处
期刊:Information Processing and Management [Elsevier]
卷期号:60 (4): 103413-103413 被引量:2
标识
DOI:10.1016/j.ipm.2023.103413
摘要

Online health consultation (OHC) serves as an important approach for patients to take an initial impression of a physician's interaction with their patients. However, little study has paid attention to how physicians leverage their interaction performance to attract patients. Drawing on signaling theory and externality effect, this study investigates how a physician's OHC performance influences patients’ choice of consulting the physician in a chronic disease context on an online health platform. By decomposing a physician's interaction performance into three dimensions, i.e., interaction breadth, interaction length, and interaction depth, this paper provides a novel method to evaluate the physician's performance. Information of 4434 physicians from six departments of chronic diseases at 185 general hospitals in the Tier Three Class A segment across China was collected, including individual information and the OHC records of the physicians. Regression analyses were applied to test the hypotheses. The results indicate that better performance in the interaction breadth and length helps physicians attract more patients while higher interaction depth reduces patients’ choice of physician. A physician's general health knowledge sharing behavior and expertise level intensify the negative effect of interaction depth on patient choice of physician. This study contributes to the literature on online health behavior, chronic disease management, and signaling theory, and offers implications for practice.
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