Propensity, Susceptibility, Infectiousness, and Proximity: Predicting Organizational Diffusion of Electronic Medical Records

Abstract:     
Electronic medical record systems (EMRs) could alleviate many problems confronting the health care industry. However, due to their inherent complexity and the difficulties in gaining commitment to their adoption by numerous stakeholders, adoption by hospitals has been slow. In this paper we use a heterogeneous diffusion model to identify predictors of the likelihood of EMR adoption by hospitals. We theorize that this likelihood is driven by static organizational characteristics as well as temporal and spatial factors. Static organizational factors describe the propensity of a hospital to adopt EMR, based on its past adoption of other related information technologies. Temporal factors reflect the fact that the adoption of EMR spreads through the community of hospitals overt time and that an individual hospital's likelihood of adoption is shaped by susceptibility and infectiousness factors. Susceptibility refers to the fact that a particular non-adopter hospital is likely to adopt EMR because it is vulnerable, by virtue of its age and size, to the adoption actions of other hospitals. At the same time, infectiousness suggests that a particular non-adopter hospital might also adopt EMR because of exposure to actions of an adopter firm that has "celebrity" status. In addition, spatial proximity (i.e., physical distance to other adopters) and social proximity (i.e., membership in a health system with other adopters) are also expected to influence the probability of EMR adoption by a hospital. We use a discrete event survival model fitted to data from a sample drawn from a multi-year survey, spanning 1970 to 2005, of almost 4,000 hospitals across the USA to test the hypotheses. Results provide support for the proposed relationships between propensity, susceptibility, infectiousness, and proximity and the likelihood of EMR adoption. Theoretical and practical implications are discussed.

Keywords: electronic medical record, diffusion, propensity, susceptibility, infectiousness, spatial proximity

working papers series