The Consensus Effect on Shared Treatment Experience in Online Healthcare Communities

40 Pages Posted: 7 May 2015 Last revised: 4 Mar 2018

See all articles by Lu (Lucy) Yan

Lu (Lucy) Yan

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies

Yong Tan

University of Washington - Michael G. Foster School of Business

Date Written: October 1, 2016

Abstract

Online healthcare communities have become increasingly popular among patients, enabling them to connect to a large population of patients who suffer from similar health problems and to access massive amounts of health-related information. We are interested in investigating how other patients’ consensus on treatment experience affects patients’ perceived treatment effectiveness. In this regard, we use the cue diagnosticity framework to examine patients’ shared treatment reviews. By controlling individual heterogeneity and the inhomogeneous weighting function of social influence on patients, we find that consensus has a positive impact on patients’ perceived treatment effectiveness. This positive effect, however, is negatively moderated by the characteristics of the shared information, including volume and the patients’ pre-commitment and social connectedness. Overall, we find that perceived treatment effectiveness is closely related to patients’ perceptions about treatment. We provide a discussion of the implications of our findings for pharmaceutical marketing and public policies.

Keywords: health information sharing, perceived treatment effectiveness, user-generated content, social network, latent variable model, random coefficient model

Suggested Citation

Yan, Lu (Lucy) and Tan, Yong, The Consensus Effect on Shared Treatment Experience in Online Healthcare Communities (October 1, 2016). Journal of Management Information Systems 34(1) 11-39.. Available at SSRN: https://ssrn.com/abstract=2603042 or http://dx.doi.org/10.2139/ssrn.2603042

Lu (Lucy) Yan (Contact Author)

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies ( email )

Department of Operations and Decision Technologies
1309 E. Tenth Street
Bloomington, IN 47401
United States

Yong Tan

University of Washington - Michael G. Foster School of Business ( email )

Box 353226
Seattle, WA 98195-3226
United States

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