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In times of converging and diversifying audiovisual (AV) industries, digitising health sector and the increasing phenomenon of cross-sectoral innovation, the question arises about the state of affairs between the health and AV sectors. The chapter aims to explore what the main modes of cross-sectoral cooperation between the health and AV sectors are and what supports and hinders the emergence of a related cross-innovation system. The chapter introduces two case studies carried out in Estonia and the wider Aarhus region (Midtjylland) in Denmark. At each site representatives of the main stakeholders of both sectors were interviewed – policy makers, entrepreneurs, educators and professionals. The results demonstrate the crucial role of path-dependencies – in terms of both hindering and enabling cross-sectoral dialogues – and also the importance of effective coordination in supporting cross-innovation.

Diffusion of innovations, defined as the adoption and implementation of new ideas, processes, products, or services in health care, is both particularly important and especially challenging. One known problem with adoption and implementation of new technologies is that, while organizations often make innovations immediately available, organizational actors are more wary about adopting new technologies because these may impact not only patients and practices but also reimbursement. As a result, innovations may remain underutilized, and organizations may miss opportunities to improve and advance. As innovation adoption is vital to achieving success and remaining competitive, it is important to measure and understand factors that impact innovation diffusion. Building on a survey of a national sample of 654 clinicians, our study measures the extent of diffusion of value-enhancing care delivery innovations (i.e., technologies that not only improve quality of care but has potential to reduce care cost by diminishing waste, Faems et al., 2010) for 13 clinical specialties and identifies healthcare-specific individual characteristics such as: professional purview, supervisory responsibility, financial incentive, and clinical tenure associated with innovation diffusion. We also examine the association of innovation diffusion with perceived value of one type of care delivery innovation – artificial intelligence (AI) – for assisting clinicians in their clinical work. Responses indicate that less than two-thirds of clinicians were knowledgeable about and aware of relevant value-enhancing care delivery innovations. Clinicians with broader professional purview, more supervisory responsibility, and stronger financial incentives had higher innovation diffusion scores, indicating greater knowledge and awareness of value-enhancing, care delivery innovations. Higher levels of knowledge of the innovations and awareness of their implementation were associated with higher perceptions of the value of AI-based technology. Our study contributes to our knowledge of diffusion of innovation in healthcare delivery and highlights potential mechanisms for speeding innovation diffusion.

This chapter establishes the conceptual and analytic framework for the book. It relates not only to much of the existing work in evolutionary and institutional economics, but also to work in cultural science and cultural semiotics domains as well as in media convergence and transmedia studies. The central concept it first deploys is ‘innovation systems’ as applied in national, regional, international and sectoral contexts. It then builds on the general theory of economic evolution by Kurt Dopfer and Jason Potts and reviews the tools this theory provides to carry out a meso-level analysis of industries co-innovating and converging. It then proposes a new concept – ‘cross-innovation’ – to refer to the emergence of new structures and ‘rules’ at the boundaries of existing industries.