Modeling the Acceptance of Hospital Information Systems among Nurses: An Extended Technology Acceptance Model

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Article Type:
Research/Original Article (بدون رتبه معتبر)
Abstract:
Introduction
The perceived usefulness and perceived ease of use have been considered as the main factors affecting the acceptance of the new technologies since last few decades. However, it appears that these only two factors cannot describe the users’ behavior in the environments like the Hospital Information System. From the technology acceptance standpoint at the individual acceptance level, the present paper tends to develop a Technology Acceptance Model with introducing some external factors.
Material and Methods
This study was conducted in 2017. The research population was included 185 nurses who works in Health Information Management (HIM) departments of Tehran University of Medical Sciences. A questionnaire was developed in order to gather the required data. The validity was obtained by panel of experts and the reliability was examined and then confirmed in a 50 person sample using the Cronbach’s Alpha (α=0.93). The Likert’s five item scale was applied. The data were analyzed using descriptive statistics, exploratory factor analysis, and path analysis.
Results
The behavioral intention was affected significantly and positively by the factors of perceived usefulness, perceived ease of use, self-efficacy, end user support, social norm, trust, job relevance, and training, with trust having the highest level of effects. Also perceived ease of use had a significant effect on perceived usefulness along with an indirect effect on behavioral intention through perceived usefulness. The factors of anxiety, voluntariness, and facilitating conditions showed no significant effects on behavioral intention.
Conclusion
The factors of trust, perceived usefulness, social norm, end user support, and self-efficacy have an impact on the behavioral intention of the users utilizing the Hospital Information System in the concerning hospitals. These factors could explain 72% of the changes of behavioral intention. Concentrating on them would lead to the improvement of the acceptance and Hospital Information System efficiency.
Language:
English
Published:
Frontiers in Health Informatics, Volume:7 Issue: 1, 2018
Pages:
1 to 6
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