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DETERMINANTS OF THE INTENTION TO USE TELEMEDICINE: EVIDENCE FROM PRIMARY CARE PHYSICIANS

Published online by Cambridge University Press:  29 July 2016

Francesc Saigi-Rubió ,
Ana Jiménez-Zarco  and
Joan Torrent-Sellens
Francesc Saigi-Rubió
Affiliation:
Open University of Cataloniafsaigi@uoc.edu
Ana Jiménez-Zarco
Affiliation:
Open University of Catalonia
Joan Torrent-Sellens
Affiliation:
Open University of Catalonia
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Abstract

Objectives: While most studies have focused on analyzing the results of telemedicine use, it is crucial to consider the determinants of its use to fully understand the issue. This article aims to provide evidence on the determinants of telemedicine use in clinical practice.

Methods: The survey targeted a total population of 398 medical professionals from a healthcare institution in Spain. The study sample was formed by the ninety-three primary care physicians who responded. Using an extended Technology Acceptance Model and microdata for the ninety-six physicians, binary logistic regression analysis was carried out.

Results: The analysis performed confirmed the model's goodness-of-fit, which allowed 48.1 percent of the dependent variable's variance to be explained. The outcomes revealed that the physicians at the healthcare institution placed greater importance on telemedicine's potential to reduce costs, and on its usefulness to the medical profession. The perception of medical information security and confidentiality and the patients’ predisposition toward telemedicine were the second explanatory factors in order of importance. A third set of moderating effects would appear to corroborate the importance of the physicians’ own opinions.

Conclusions: These results have revealed the need for a dynamic approach to the design of telemedicine use, especially when it targets a variety of end-users. Hence, the importance of conducting studies before using telemedicine, and attempting to identify which of the above-mentioned predictors exert an influence and how.

Keywords

Telemedicine adoptionTechnology driversPerceived attitudesIntention to useProbabilistic models of causationTechnology acceptance model (TAM)
Type
Assessments
Information
International Journal of Technology Assessment in Health Care , Volume 32 , Issue 1-2 , 2016 , pp. 29 - 36
Copyright
Copyright © Cambridge University Press 2016 

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