Pi-Jung Hsieh

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PURPOSE Electronic medical records (EMRs) exchange improves clinical quality and reduces medical costs. However, few studies address the antecedent factors of physicians' intentions to use EMR exchange. Based on institutional trust and perceived risk integrated with the decomposed theory of planned behavior (TPB) model, we propose a theoretical model to(More)
PURPOSE Cloud computing technology has recently been seen as an important milestone in medical informatics development. Despite its great potential, there are gaps in our understanding of how users evaluate change in relation to the health cloud and how they decide to resist it. Integrating technology acceptance and status quo bias perspectives, this study(More)
Virtual communities have become increasingly popular in recent years. Despite significant growth in the number of virtual communities, few communities have been successful retaining members and motivating members to continue sharing knowledge. This study focuses on how knowledge-contributor characteristics impact the relationship between individuals’(More)
In this study, we examined physician acceptance behavior of the electronic medical record (EMR) exchange. Although several prior studies have focused on factors that affect the adoption or use of EMRs, empirical study that captures the success factors that encourage physicians to adopt the EMR exchange is limited. Therefore, drawing on institutional trust(More)
Nursing is critical in health care systems and comprises the planning, execution, and documentation of nursing care. To better manage health care information during patient care, the use of a mobile nursing information system (MNIS) provides more time to care for inpatients by reducing time-consuming and redundant paperwork. The purpose of this study was to(More)
The latest technological trends such as health cloud provide a strong infrastructure and offer a true enabler for healthcare services over the Internet. Despite its great potential, there are gaps in our understanding of how users evaluate change related to the health cloud and decide to resist it. According to the technology acceptance and status quo bias(More)