There are an increasing number of new technological innovations emerging and being fielded in the market, especially medical technologies. Studies of these new technologies should consider trajectories of change and adaptation as new systems and capabilities are introduced and mature. Within the literature is a variety of technology adoption, evolution and radical change models; one widely cited view of technology adoption is Rogers diffusion of innovation, which has been used to empirically examine attempts to inject new technologies into various domains.
Rogers diffusion of innovation accounts for success stories of technology adoption; however, it is limited for technologies that are rejected by intended users, require significant tailoring, or are used for unexpected functions. The proposed dissertation research takes a cognitive systems engineering perspective to reinvigorate the study of the impact of new technology in complex, socio-technical settings, by focusing on the intersections of the domain, artifacts (e.g. tools and technologies), and practitioners. A case study of a specific new technology was conducted using a triangulation of ethnographic methods including: observations, interviews, and log analysis. The emerging telemedicine example studied in this research is the electronic intensive care unit (e-ICU). The e-ICU was implemented in a single hospital in 2000; it was not subsequently expanded to other hospital systems until years later and since then has seen increased usage around hospital systems. The study summarizes the current e-ICU functions into three groups: access to expertise, anomaly response, and sensemaking. Additionally, intervention logs where the e-ICU nurses write down every time a discourse occurs between the e-ICU and ICU were examined. The intervention log analysis lends support to the hypothesis that these functions and additional functions of the e-ICU are changing over time. Finally, the interviews provide a survey of additional functions that other e-ICUs across the country.
Previous research utilizes these methods to identify patterns in how expert practitioners interact with computerized support to achieve domain-specific objectives, making no projections about potential trajectories of adaptation through use that may occur over the longer term. This research is novel in that the findings form the foundation of a proposed, expanded, theoretical framework of trajectories and indicators of technology change.
This research is anticipated to have theoretical as well as applied contributions. First, an enhanced theoretical framework should better enable companies to predict the impacts of new technologies in emerging markets by providing possible trajectories and associated indicators. Thus, these projections may be further explored in future research as to how technology may be steered into more productive trajectories, and how to mitigate the negative side effects associated with particular trajectories. The research suggests that the ability to project possible trajectories in order to aid in selecting among alternatives and managing post-conditions of change can be done based on the pattern base built up through cognitive systems engineering and the proposed theoretical framework.