title: Assessing or predicting adoption of telehealth using the diffusion of innovations theory: a practical example from a rural program in New Mexico.
abstract: In New Mexico, a large rural state, it was anticipated that telehealth would bring significant value to health care delivery, improve local capacity for patient care, decrease the need for patient travel, diminish professional isolation, provide an avenue for enhanced professional education and information sharing, increase access to care, and ultimately improve health status. During the course of an evaluation of the University of New Mexico Center for Telehealth's rural telemedicine program, we used a grounded theory approach to assess barriers to the adoption of telemedicine and components of successful adoption. We then turned to the diffusion of innovations theory to better understand the dynamic interactions between the characteristics of telehealth and the social system in which it is applied. In doing so, we learned that the type of innovation decision involved in the adoption of telehealth appears to be particularly important in determining adoption. In this article we demonstrate that diffusion theory can be a useful framework for evaluating telehealth programs. We also suggest that the development of a predictive tool for prospective assessment would be useful, and could be applied when new telehealth programs are being planned.
authors.affiliation: Office of Evaluation, University of New Mexico School of Medicine, Albuquerque, New Mexico 87131, USA. helitzer@unm.edu
authors.forename: Deborah
authors.initials: D
authors.lastname: Helitzer
authors.forename: Debra
authors.initials: D
authors.lastname: Heath
authors.forename: Kristine
authors.initials: K
authors.lastname: Maltrud
authors.forename: Eileen
authors.initials: E
authors.lastname: Sullivan
authors.forename: Dale
authors.initials: D
authors.lastname: Alverson
mesh_terms: D003695:Delivery of Health Care / Q000639:trends*; D006801:Humans; D009516:New Mexico; D012423:Rural Health; D017216:Telemedicine / Q000639:trends*; D019112:Teleradiology / Q000706:statistics & numerical data