Modeling the longitudinality of user acceptance of technology with an evidence-adaptive clinical decision support system

Modeling the longitudinality of user acceptance of technology with an evidence-adaptive clinical decision support system

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Article ID: iaor20141858
Volume: 57
Start Page Number: 444
End Page Number: 453
Publication Date: Jan 2014
Journal: Decision Support Systems
Authors: , ,
Keywords: computers: information, decision, behaviour
Abstract:

This paper presents multiple innovations associated with an electronic health record system developed to support evidence‐based medicine practice, and highlights a new construct, based on the technology acceptance model, to explain end users' acceptance of this technology through a lens of continuous behavioral adaptation and change. We show that this new conceptualization of technology acceptance reveals a richer level of detail of the developmental course whereby individuals adjust their behavior gradually to assimilate technology use. We also show that traditional models such as technology acceptance model (TAM) are not capable of delineating this longitudinal behavioral development process. Our TAM‐derived analysis provides a lens through which we summarize the significance of this project to research and practice. We show that our application is an excellent exemplar of the ‘end‐to‐end’ IS design realization process; it has drawn upon multiple disciplines to formulate and solve challenges in medical knowledge engineering, just‐in‐time provisioning of computerized decision‐support advice, diffusion of innovation and individual users' technology acceptance, usability of human‐machine interfaces in healthcare, and sociotechnical issues associated with integrating IT applications into a patient care delivery environment.

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