26th International Association for Management of Technology Conference - IAMOT 2017

System Dynamics models have previously been used to describe the adoption of new technology in Healthcare. JB Homer and later KL Knoll developed such models based on case studies involving implantable devices and antibiotic pharmaceutical product. In both cases the technologies studied were of a therapeutic nature and the use-event was linked to an individual patient (single use). The process involved in the adoption of new technology which is diagnostic in nature and where the same device is used in many patient use-events, is significantly different. In such cases, the initial decision to acquire the technology is normally dependent on the availability of substantial capital but once the device is installed, the subsequent use requires little or no additional funds. The differences brought about by the application; namely diagnostic versus therapeutic, introduces a further variance form the aforementioned scenarios, resulting in unique dynamic characteristics. The model, discussed in this paper was developed to simulate the multi-use diagnostic device adoption process and is structurally based on the five-stage Adoption Decision process described by Rogers. The well-known process describes the propagation of potential adopters through the stages of adoption or rejection of a new idea. Stocks and flows which constitutes the key elements of a System Dynamics model is utilised to represent the population of adopters (stocks) and how they move(flows) through the stages of the Adoption Decision process. In developing the model, a specific case of adoption of a novel full body x-ray scanner is used. Data for development and verification of the model was collected from the adoption of the innovation in two distinct applications, namely Trauma and Forensic Medicine. The two applications were further studied in two different geographic areas; South Africa and the United States of America. This lead to the simulation of the adoption process of the same innovation in four distinct cases. The paper will present the initial results from the simulation.