Although diffusion of new IT in healthcare does not seem to level of, successes are reported frequently. Many of these successful cases experience enthusiastic use of the innovation by a limited group of physicians or other users. This paper explains stranded diffusion by differentiating the match between user and IT s' to adopter categories (the User-IT-match or USIT-model). This match is described by the (sub)- dimensions of affection/resistance, relevance, requirements and resources. Once the sub-dimensions are determined for all adopter groups, it might become clear that different sub-dimensions play a role for every adopter group, and thus in every successive stage of the diffusion process. The diffusion process strands if there is no match with the sub-dimensions that play a role for the adopter category that was to adopt the innovation in that stage. A total of 56-case-studies on the diffusion of an Electronic Prescription System (EPS) for general practitioners in the Netherlands was used to test the explanatory power of these factors. We conclude that USIT is of high value to determine adopter-category specific diffusion problems, and thus to understand stranding diffusion. The relevance-factor has the biggest impact within USIT. The paper includes discussion of the limits of the model and suggestions for elaboration. The paper discusses diffusion problems that are specific for this EPS.
|Number of pages||16|
|Journal||International journal of healthcare technology and management|
|Publication status||Published - 2001|