This dissertation examines the adoption of health IT by addressing the barriers to adoption from the perspective of multiple stakeholders. I examine three different phenomena using alternative methodologies and theoretical lenses.

Essay 1: The Impact of Firm Characteristics and Spatial Proximity on the Diffusion of Electronic Medical Records: A Hazard Modeling Analysis.

This study, positioned at the inter-organizational level, draws upon adoption and diffusion literature to predict the likelihood of EMR adoption by hospitals. I theorize that adoption is driven by factors such as the concentration and experience with complementary HIT and an environmental factor, spatial proximity. Using a hazard model fitted to data from a sample drawn from almost 4,000 hospitals, I find support for a positive relationship between IT concentration and likelihood of adoption. I also find that spatial proximity explains variance in adoption and that its effect diminishes as distance increases.

Essay 2: Isolating the Effects of IT on Performance: An Empirical Test of Complementarities and Learning.

An issue at the organizational level is whether benefits result from investment in HIT. I apply a knowledge-based lens to the examination of IT adoption and process-level value, incorporating the effects of learning occurring through complementary IT adoption. I test hypotheses using data from almost 400 nationally-representative hospitals matched with quality and financial performance data and find that learning associated with more experience with IT leads to superior performance.

Essay 3: Adoption of Electronic Medical Records in the Presence of Privacy Concerns: The Elaboration Likelihood Model and Individual Persuasion.

At the individual level, privacy concerns can inhibit the adoption of EMRs. I draw from literature on attitude change to develop hypotheses that individuals can be persuaded to support the use, and ultimately opt-in to EMRs, even in the presence of significant privacy concerns if compelling arguments about the value of EMRs are presented. Using a quasi-experimental methodology, I find that privacy concerns interact with argument framing and issue involvement to affect attitudes toward the use of EMRs. In addition, results suggest that attitude towards EMR use and CFIP directly impact the likelihood of adoption of EMR technology.