Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Business Administration

First Advisor's Name

Weidong Xia

First Advisor's Committee Title

Committee Co-Chair

Second Advisor's Name

Monica Chiarini Tremblay

Second Advisor's Committee Title

Committee Co-Chair

Third Advisor's Name

Min Chen

Third Advisor's Committee Title

Committee member

Fourth Advisor's Name

Mido Chang

Fourth Advisor's Committee Title

Committee member

Keywords

Health Information Exchange, HIE, Social Exchange Theory, Technology Adoption, Implementation, Diffusion of Innovation Theory

Date of Defense

7-2017

Abstract

The healthcare system in the US faces substantial challenges related to cost, access and quality. Health Information Exchange (HIE) has been widely viewed as a viable solution for dealing with those challenges. Despite the potential contributions to the healthcare system that HIE promises, adoption and use of HIE have always been difficult, and the past two decades have witnessed significant HIE implementation failures.

The limited understanding of HIE is a major obstacle for HIE success. Only recently in-depth research about HIE starts to appear in top IS journals. In addition, the uniqueness of healthcare industry adds to the complexity to HIE. Our study attempts to address this research gap by systematically examining multiple factors that influence HIE adoption and use. Using social exchange theory (SET) and diffusion of innovations theory, a research model was developed to empirically test major factors that impact healthcare providers’ relative advantages and risks perceptions for adopting and using HIE. It is further proposed that relative advantages and risks in turn impact organizations’ intentions for adopting and continuously using HIE. As such, we posit that organizations’ assessments of relative advantages and risks associated with HIE mediate the impacts of organizational and technological factors on organizations’ adoption and use intentions.

This study uses questionnaire surveys for data collection. Out of a total of 163 responses, 117 surveys were completed and were analyzed using Partial Least Square software SmartPLS 3. Data analysis finds that most of the relationships were in the hypothesized directions with some of the relationships being significant. Specifically, top management support, absorptive capacity, trust, and HIE innovation characteristics positively affect relative advantages and negatively affect risk. Furthermore, relative advantages positively affect adoption/continuance intentions, whereas risk negatively affects adoption/continuance intentions.

This study contributes to the literature and offers important practical implications. It is one of the early empirical attempts to understand the key factors that affect HIE’s adoptions and use. The research can also serve as a starting point for more in-depth studies in the future. Moreover, practitioners can use the several newly-developed scales to empirically examine healthcare providers’ adoption and use intentions.

Identifier

FIDC004029

Available for download on Friday, December 06, 2019

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