Currently submitted to: JMIR Human Factors
Date Submitted: May 5, 2025
Open Peer Review Period: May 12, 2025 - Jul 7, 2025
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Bridging Perceptual Gaps Between Clinicians and Developers in Smart Healthcare Systems: An Empirical Study Using the Information System Success Model
ABSTRACT
Background:
Smart healthcare systems are increasingly integrated into clinical practice to enhance efficiency and care quality. However, differences in perspectives between clinical users and system developers often result in perception gaps that hinder successful implementation. These misalignments can reduce user satisfaction, limit system reliance, and compromise overall adoption. A deeper understanding of these perceptual differences is crucial to improving health IT design and sustainability.
Objective:
This study aims to explore perception gaps between clinical users and system developers regarding key system success constructs in smart healthcare environments. Specifically, it investigates how these differences affect user satisfaction and dependence, and examines whether perceived risk moderates the relationship between information quality and system dependence.
Methods:
A cross-sectional survey was conducted in a regional hospital in Taiwan, with 289 valid responses collected—266 from clinical users and 23 from system developers. The survey instrument measured constructs from the Information System Success Model (ISSM), including system functionality, information quality, facilitating conditions, social influence, user dependence, user satisfaction, and perceived risk. Multiple regression and moderation analyses were employed to examine relationships among variables.
Results:
Significant perceptual differences were identified between clinical users and developers in terms of system functionality, information quality, user satisfaction, and perceived risk. Regression analyses revealed that system functionality, information quality, facilitating conditions, and user dependence were significant predictors of user satisfaction. Additionally, information quality and social influence positively influenced user dependence. Perceived risk was found to moderate the relationship between information quality and user dependence.
Conclusions:
The findings support the extended ISSM framework in the context of smart healthcare and underscore the importance of participatory system design, transparent communication regarding system risks, and institutional support. Addressing perceptual gaps between key stakeholders is essential for fostering trust, enhancing user engagement, and promoting the sustainable adoption of health IT systems in clinical settings.
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Copyright
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