Effective Dissemination Of Healthcare Information And Its Behavioral Impacts
Dr Sharon Tan Swee Lin, Associate Professor, School of Computing
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Abstract:
Effective dissemination of healthcare information aims to promote public health and improve professional healthcare services. However, healthcare information per se does not necessarily lead to behavioral change unless it is effectively conveyed to and absorbed by its target audience. Motivated by the questions of both real-world relevance and theoretical significance, this dissertation is composed of two empirical essays on the behavioral impacts of the effective dissemination of healthcare information in the contexts of e-commerce and healthcare.
The first study attempts to investigate the effects of health-hazard information (HHI) on online and offline consumer behavior. Timely HHI such as air pollution information aims to instruct individuals to minimize specific outdoor or indoor activities to protect themselves from harmful hazards or noxious pollutants. While offline demand typically decreases with fewer outdoor activities, this study addresses the following questions: 1) What are the impacts of health-hazard information on offline and online purchase activities? 2) What is the mechanism of the above effects? 3) What is the relative effectiveness of pushed and pulled health-hazard information? Leveraging a unique data set of HHI for air pollution from both pushed and pulled channels and online/offline purchase behavior in 165 stores and over 4,000 consumers in China, we perform panel linear regressions of consumer behaviors against the intensity of pushed and pulled HHI. Our results suggest that HHI affects online product search and purchase through two different mechanisms. Pushed and pulled HHI influences consumer behavior via the "avoidance" mechanism and the "bad mood inertia" mechanism, respectively. Additionally, the intensity of pushed HHI has larger elasticities of consumer demand than the intensity of pulled HHI. A 1% increase in pushed HHI is associated with an 8.5%-8.8% growth in online product search behaviors. On the contrary, the elasticity of pulled HHI on consumer behavior is only around 1-1.8%. This essay contributes to the literature on HHI and multichannel retailing. First, it distinguishes between two types of mechanisms through which HHI can affect consumer behaviors. Second, it contributes to the multichannel retailing literature by documenting that both complementarity and substitution exist between online and offline channels. Finally, it examines both pushed and pulled HHI and compare their relative effectiveness, which can help bridge the research gaps while informing important policy decisions of crafting and emphasizing pushed or pulled HHI.
The second empirical study is regarding the disclosure of performance information to clinicians and its subsequent performance improvement. In recent years, to improve the quality of care per dollar spent, governments have been transforming healthcare payment models from volume-based to value-based care. To facilitate this transformation, healthcare practitioners have initiated data-intensive value-driven care (VDC) projects to regularly and retrospectively monitor clinical performance and cost at a fine-grained level. This paper attempts to extend the literature on value-based care and data analytics by addressing the following questions: 1) Whether VDC projects improve clinicians' performances? 2) What is the underlying mechanism of such improvement, if any? 3) What is the heterogeneity of effects across different departments? Leveraging the phase-in feature of VDC projects across hospitals and departments, this paper establishes a rigorous causal inference of the effects of VDC projects on clinical performance in a quasi-experimental setting using Difference-in-Differences models. Our results suggest that VDC projects improve the quality of care, cost-effectiveness, and patient satisfaction. Specifically, the cost has dropped 4,757-5,873 SGD per episode on average for some conditions. Additionally, utilizing a fine-grained timeline of these projects, we are able to identify the effects of data analytics apart from other non-IT effects (i.e., goal congruence). Third, our results also suggest heterogeneity among surgical and non-surgical departments. This study contributes to the literature on value-based care by providing the first rigorous empirical evidence of VDC projects. It also contributes to the literature on the value of data analytics by disentangling the effects of data analytics from goal congruence.