| Summary: | Malcolm Masso, Cristina Thompson Centre for Health Service Development, Australian Health Services Research Institute, University of Wollongong, Wollongong, NSW, Australia Abstract: The context for the paper was the evaluation of a national program in Australia to investigate extended scopes of practice for health professionals (paramedics, physiotherapists, and nurses). The design of the evaluation involved a mixed-methods approach with multiple data sources. Four multidisciplinary models of extended scope of practice were tested over an 18-month period, involving 26 organizations, 224 health professionals, and 36 implementation sites. The evaluation focused on what could be learned to inform scaling up the extended scopes of practice on a national scale. The evaluation findings were used to develop a conceptual framework for use by clinicians, managers, and policy makers to determine appropriate strategies for scaling up effective innovations. Development of the framework was informed by the literature on the diffusion of innovations, particularly an understanding that certain attributes of innovations influence adoption. The framework recognizes the role played by three groups of stakeholders: evidence producers, evidence influencers, and evidence adopters. The use of the framework is illustrated with four case studies from the evaluation. The findings demonstrate how the scaling up of innovations can be influenced by three quite distinct approaches – letting adoption take place in an uncontrolled, unplanned, way; actively helping the process of adoption; or taking deliberate steps to ensure that adoption takes place. Development of the conceptual framework resulted in two sets of questions to guide decisions about scalability, one for those considering whether to adopt the innovation (evidence adopters), and the other for those trying to decide on the optimal strategy for dissemination (evidence influencers). Keywords: diffusion of innovations, extended scope practice, evaluation, multidisciplinary models of care, scalability
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