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Healthcare systems have undergone significant changes in recent decades in order to reduce the large costs associated with all services and to improve the quality of healthcare delivery (Hedberg & Morosi, 2015). Factors such as an aging population and increasing cost of new medical treatments have complicated the fulfillment of this purpose, as these factors cause an increase in healthcare spending (Plageras et al., 2017). To solve the current problems of healthcare sustainability, information technology (IT) has been introduced into healthcare, which has given rise to a new term called eHealth (Eysenbach, 2001). The COVID-19 crisis has made it clear that technology can be an important pillar for the survival and improvement of services in many sectors, especially in healthcare, bringing business-related advantages and dynamic and efficient processes (Taques et al., 2021).
In a relatively short period of time, general health practices have evolved towards digitization and hospital technology platforms have improved, from passive applications with only practical information to read to active applications where professionals and patients can interact, to data analysis systems that can help find trends that facilitate the creation of new vaccines and fight diseases, and even the use of learning techniques in the detection of falsification of medical images (Ghoneim et al., 2018). Numerous eHealth innovation projects are being carried out to address healthcare issues with IT. These types of projects, which constitute systems capable of satisfying medical and economic needs, are designed and developed with the aim of responding to the problems faced by health. However, a common concern in the innovation ecosystem involved is that most of these projects remain in a permanent pilot state (Urueña et al., 2016).
Figure 1 shows the life cycle of a technological project and the exact location of our research. The project life cycle is divided into two main environments: the pilot environment, where the first complete but non-final iteration of a technology is developed to consider the possibilities for further development; and the real environment, where technology developed can run in the normal operating and common use. This research focuses on the transition from the pilot environment to the real environment, since this is where the phenomenon of interest is found.
Figure 1.
Technological project life cycle
Most studies that have focused on the acceptance of technology by end users are quantitative and based on questionnaires using different analysis models (Venkatesh et al., 2003). In this framework, there are not only different factors related to technological resistance, but also financial, legal, political, organizational and end-user behavior factors which could have an impact on the implementation of IT in the healthcare sector. Scholars have identified the need to discover mechanisms to help achieving successful implementation of these projects. A very small percentage of eHealth innovation projects are commercialized and widely used in healthcare services in the real environment. For this reason, some literature references have suggested using the term pilot plague, which implies that projects are set up to run as non-permanent test projects rather than becoming a normal practice in common use (Andreassen et al., 2015). The fact that a pilot project does not reach the commercialization stage implies great financial, time and effort losses for the institutions and people involved. However, no qualitative studies have focused on technology acceptance by end-users, and none of the compared studies have implemented and non-implemented projects.