The effect of interactive factors on online health consultation review deviation: An empirical investigation. (July 2022)

• Record Type: Journal Article
• Authors: He, Yifan; Guo, Xitong; Wu, Tianshi; Vogel, Doug
• Is Part Of: International journal of medical informatics. Volume 163(2022)
• Publication Date: 2022-07
• Subjects: Online doctor reviews -- Usefulness of online reviews -- One-to-one online health consultation -- Online doctor review deviation -- Machine learning -- Multinomial logistic regression; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2022.104781
• Languages: English
• ISSNs: 1386-5056

Abstract

Highlights: Using online doctor reviews with third-party supervision as the evaluation method. Identifying three types of interactive factors in one-to-one online health consultations. Higher response speed and lower response-question ratio can reduce review deviation. Single interaction modalities and medical information can reduce review deviation. Voice messages can better reduce review deviation in surgery than internal medicine. Abstract: Background: One-to-one online consultation is a common type of online health consultation. In choosing doctors for these consultations, patients rely on online reviews. Yet the deviation between online doctor reviews and the true quality of doctor-provided online services calls the usefulness of online doctor reviews into question, and the methods for reducing this deviation via doctor-patient communication remain unclear. Objectives: The purpose of this study is to test the effects of interactive factors on online doctor review deviation and to further explore deviation across doctor specialties in the context of one-to-one online health consultations. Methods: We collect our data from a well-known Chinese online health consultation platform. The dataset includes 60, 693 one-to-one online health consultation communication flows and corresponding online doctor reviews. We construct an online doctor review deviation matrix and use logistic regression and multinomial logistic regression models to examine the effects of interactive factors on online doctor review deviation. Results: Our findings indicate that, in the context of a one-to-one online health consultation, a quicker response time and a lower response-question ratio could reduce deviation in online doctor reviews. Single modalities, such as the use of voice messages and uploading of photos, could reduce online doctor review deviation, especially in terms of patient overestimation. Medical information, including structural medical history and prescription information, could decrease online doctor review deviation. Moreover, the use of voice messages in surgery patient treatment can reduce online doctor review deviation more than in internal medicine. Conclusion: Interaction frequency, message delivery methods, and medical information can influence the deviation of online doctor reviews. Furthermore, the effects of voice messages vary across doctor specialties. This study offers theoretical and practical implications for the design of online health consultation platforms and the usage of online doctor reviews.