Optimal Online Health Information Market: An Empirically-Based Market Design Approach

  • Fatemeh Ameri

Student thesis: Phd


Advances in information technology have made a significant influence on healthcare. Among technological breakthroughs, Internet has revolutionized the way people have access to health information. People increasingly use the Internet to search for, exchange and post health information on various types of websites. Internet offers invaluable benefits to its users; nevertheless, this very freedom to post information and the resulting enormous body of information is also one of the major sources of concerns. There have been misgivings about the quality of online health information since the Internet has been introduced. The 'top-down' approaches to control the quality of online health information proved to be neither practical nor desirable. The advent of web 2.0 (read and write version of web) enables user-driven approaches to improve the quality of information through 'bottom-up' approaches. The critical question is what type of bottom-up approach is suitable to provide online users with high quality health information.Drawing on the market design literature, this research proposes a framework to understand and address (improve) the problem of quality of online health information. The research aims to identify the conditions under which a market for exchange of online health information works efficiently and then study the mechanisms to achieve the efficiency conditions and maximise quality. It also highlights the literature gaps for designing an online market that ensure the quality of exchanged health information.The research collected data from question and answer platforms to carry the empirical analysis. One hundred actual question and answers from nine platforms (900 in total) were collected. The quality of health information was determined by medical expert assessors and related design features were collected form Internet. Statistical algorithmic modelling was adopted for data analysis. Supervised learning methods and mainly regression tree method was used to investigate the relationship between design and quality of health information. The study uncovers the mechanisms and design features that are associated with the quality of health information. It reveals the interaction between design features that lead to high quality health information. The results particularly highlight the importance of experts' participation in the platform for increasing health information quality. It also shed light on the importance of financial incentives in enhancing health information quality. Building on the empirical findings, the research proposes four design scenarios of an online health information market and their respective outcome in terms of quality.The research opens a new perspective for researchers on how to tackle the problem of quality of online health information by framing this problem as a 'market design' issue. It provides important design lessons for managers and designers on how to enhance the quality of online health information in their platforms. It gives policy makers empirically supported guidance for recognising and promoting online procedures that lead to production of high quality online health information.
Date of Award1 Aug 2016
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorKathy Keeling (Supervisor) & Mohammad Salehnejad (Supervisor)


  • Market design
  • Online health information
  • Information quality

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