Theses and Dissertations - UTB/UTPA
Understanding User Resistance to Information Technology: Toward A Comprehensive Model in Health Information Technology
Date of Award
Doctor of Philosophy (PhD)
Computer Information Systems
Dr. Vishal Midha
Dr. Punit Ahluwalia
Dr. Jun Sun
The successful implementation of health information systems is expected to increase legibility, reduce medical errors, boost the quality of healthcare and shrink costs. Yet, evidence points to the fact that healthcare professionals resist the full use of these systems. Physicians and nurses have been reported to resist the system. Even though resistance to technology has always been identified as key issue in the successful implementation of information technology, the subject remains largely under-theorized and deficient of empirical testing. Only two proposed model have been tested so far. Hence, though user resistance is clearly identified and defined in literature, not very much is known about its antecedents; and about how and why it comes about.
This study seeks therefore, to fill this gap. If organizational change managers must go past the hurdle of under-utilized systems, low productivity and the high implementation costs associated with them, a clear understanding of the very nature of resistance is important. The following questions are investigated: (1) why do healthcare personnel resist health information technology? (2) What are the antecedents of perceived threats to health information technology? And, (3) does user resistance vary across healthcare professions?
The study utilizes the theory of psychological reactance, the cognitive dissonance theory, the extended technology acceptance model and other relevant theories to build on the Lapointe and Rivard (2005) resistance framework. The resulting theoretical model is further tested empirically using primary data. Partial Least Squares technique will be used to analyze data and findings would be discussed. This work is expected to contribute to both our understanding of the resistance theory—through the extension of current theory—as well as provide useful tools for change practitioners to mitigate the phenomenon and improve electronic health records implementation outcomes.
University of Texas-Pan American
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