Initial Communication Media and Patient Revisit: Evidence from an Online Mental Healthcare Platform
56 Pages Posted: 10 May 2023
Date Written: March 20, 2023
Abstract
Online mental healthcare platforms have flourished during the COVID-19 pandemic, but the media choice in online physician-patient interactions has still been a conundrum for all stakeholders. As an essential service design element, communication media could affect patient revisit, which in turn helps manage chronic diseases. Yet this media effect is little understood in research and practice. Using data from a leading online mental healthcare platform in China, we classify service media into synchronous (audio, video) and asynchronous (text) types and study their relative effects. First, we observe disproportionately more patient revisits after initial healthcare services via synchronous media. The effect is consistent across different empirical methods, such as matching and regression discontinuity design. Second, synchronous media improve both the health conditions of patients and the revenue of physicians and the platform. Third, we explore the underlying mechanisms and present evidence suggesting that the cue multiplicity (more likely than feedback immediacy) of synchronous media communication explains its positive effect. Finally, we examine the effect heterogeneity across overt and covert patient attributes and find that: (i) The media effect is significant for most mental conditions but not schizophrenia, suggesting that synchronous media are effective when online consultation matters in therapy; and (ii) the effect is more pronounced for patients at a higher risk of health deterioration, as predicted and ranked using machine learning techniques. We discuss the implications of these findings for understanding the interplay between communication media and telehealth service engagement and designing sustainable online platforms for all healthcare stakeholders.
Note:
Funding Information: None
Conflict of Interests: None
Ethical Approval: This study was approved by the Research Ethics Committee at the School of Management, Harbin Institute of Technology.
Keywords: Digital Platform, Online Healthcare Service, Patient Revisit, Communication Media, Mental Health, Regression Discontinuity Design, Machine Learning
JEL Classification: D83, I12, L86, M15
Suggested Citation: Suggested Citation