Technology Acceptance in Health Information Systems
Summary
Technology acceptance in health information systems examines the factors that shape users’ willingness to adopt and use digital tools for clinical practice, patient management and health education. This field integrates psychological, organisational and technical perspectives to understand how perceived usefulness and ease of use, social influences and environmental enablers determine behavioural intention and actual system use. Recent advances have explored the role of artificial intelligence, telemedicine platforms and patient-facing portals in settings ranging from tertiary hospitals to community clinics. By elucidating barriers such as technological anxiety and facilitators such as reliable training and support, this research informs the design and implementation of systems that improve efficiency, care continuity and health outcomes across diverse populations.
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Technology Acceptance in Health Information Systems publication trend
The graph below shows the total number of articles in technology acceptance in health information systems across all publications each year (not limited to Nature Index journals).
Technical terms
Technology Acceptance Model (TAM): A theoretical framework positing that perceived usefulness and perceived ease of use determine users’ adoption of information systems.
Unified Theory of Acceptance and Use of Technology (UTAUT): An integrative model that explains user intentions through constructs such as performance expectancy, effort expectancy, social influence and facilitating conditions.
Perceived usefulness: The degree to which a user believes that using a particular system will enhance job performance or health-care outcomes.
Perceived ease of use: The extent to which a user expects that interacting with a system will be free of effort.
Behavioural intention: A measure of an individual’s readiness or willingness to perform a specific behaviour, such as adopting a health information technology.
References
- Why do healthcare workers adopt digital health technologies - A cross-sectional study integrating the TAM and UTAUT model in a developing economy. International Journal of Information Management Data Insights (2023).
- Utilization of, Perceptions on, and Intention to Use AI Chatbots Among Medical Students in China: National Cross-Sectional Study. JMIR Medical Education (2024).
- Attitudes towards digital health technology for the care of people with chronic kidney disease: A technology acceptance model exploration. PLOS Digital Health (2024).
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