Network analysis of surgical innovation: Measuring value and the virality of diffusion in robotic surgery

BACKGROUND: Existing surgical innovation frameworks suffer from a unifying limitation, their qualitative nature. A rigorous approach to measuring surgical innovation is needed that extends beyond detecting simply publication, citation, and patent counts and instead uncovers an implementation-based value from the structure of the entire adoption cascades produced over time by diffusion processes. Based on the principles of evidence-based medicine and existing surgical regulatory frameworks, the surgical innovation funnel is described. This illustrates the different stages through which innovation in surgery typically progresses. The aim is to propose a novel and quantitative network-based framework that will permit modeling and visualizing innovation diffusion cascades in surgery and measuring virality and value of innovations. MATERIALS AND METHODS: Network analysis of constructed citation networks of all articles concerned with robotic surgery (n = 13,240, Scopus®) was performed (1974-2014). The virality of each cascade was measured as was innovation value (measured by the innovation index) derived from the evidence-based stage occupied by the corresponding seed article in the surgical innovation funnel. The network-based surgical innovation metrics were also validated against real world big data (National Inpatient Sample-NIS®). RESULTS: Rankings of surgical innovation across specialties by cascade size and structural virality (structural depth and width) were found to correlate closely with the ranking by innovation value (Spearman's rank correlation coefficient = 0.758 (p = 0.01), 0.782 (p = 0.008), 0.624 (p = 0.05), respectively) which in turn matches the ranking based on real world big data from the NIS® (Spearman's coefficient = 0.673;p = 0.033). CONCLUSION: Network analysis offers unique new opportunities for understanding, modeling and measuring surgical innovation, and ultimately for assessing and comparing generative value between different specialties. The novel surgical innovation metrics developed may prove valuable especially in guiding policy makers, funding bodies, surgeons, and healthcare providers in the current climate of competing national priorities for investment

Development blocks in innovation networks : The Swedish manufacturing industry, 1970–2007

The notion of development blocks (Dahmén, 1950, 1991) suggests the co-evolution of technologies and industries through complementarities and the overcoming of imbalances. This study proposes and applies a methodology to analyse development blocks empirically. To assess the extent and character of innovational interdependencies between industries the study combines analysis of innovation biographies and statistical network analysis. This is made possible by using data from a newly constructed innovation output database for Sweden. The study finds ten communities of closely related industries in which innovation activity has been prompted by the emergence of technological imbalances or by the exploitation of new technological opportunities. The communities found in the Swedish network of innovation are shown to be stable over time and often characterized by strong user-supplier interdependencies. These findings serve to stress how historical imbalances and opportunities are key to understanding the dynamics of the long-run development of industries and new technologies