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

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          Abstract

          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.

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          Most cited references23

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          Epidemic Spreading in Scale-Free Networks

          The Internet has a very complex connectivity recently modeled by the class of scale-free networks. This feature, which appears to be very efficient for a communications network, favors at the same time the spreading of computer viruses. We analyze real data from computer virus infections and find the average lifetime and persistence of viral strains on the Internet. We define a dynamical model for the spreading of infections on scale-free networks, finding the absence of an epidemic threshold and its associated critical behavior. This new epidemiological framework rationalizes data of computer viruses and could help in the understanding of other spreading phenomena on communication and social networks.
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            The Selfish Gene

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              Prediction Policy Problems.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                25 August 2017
                2017
                : 12
                : 8
                : e0183332
                Affiliations
                [1 ] Surgical Innovation Center, Department of Surgery and Cancer, Imperial College London, St. Mary’s Hospital, London, United Kingdom
                [2 ] Department of Surgical Research and Innovation, The Royal College of Surgeons of England, London, United Kingdom
                [3 ] Big Data and Analytical Unit, Imperial College London, St. Mary’s Hospital, London, United Kingdom
                [4 ] School of Business and Management, Queen Mary University of London, London, United Kingdom
                Dalian University of Technology, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-7468-3287
                Article
                PONE-D-17-17908
                10.1371/journal.pone.0183332
                5571947
                28841648
                16ca945f-c755-497a-8d81-d2240c24e3a6
                © 2017 Garas et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 10 May 2017
                : 2 August 2017
                Page count
                Figures: 6, Tables: 0, Pages: 14
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000297, Royal College of Surgeons of England;
                Award ID: GG 1037600/2017-2018
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100005302, Alexander S. Onassis Public Benefit Foundation;
                Award ID: F ZM 014-1/2016-2017
                Award Recipient :
                Dr. George Garas, MD, FRCS holds a Royal College of Surgeons of England Doctoral Research Fellowship (Grant number GG 1037600/2017-2018) and is also supported by Imperial College London (Grant number CID 337755/2015-2018) and the Alexander S. Onassis Public Benefit Foundation (Grant number F ZM 014-1/2016-2017). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Engineering and Technology
                Mechanical Engineering
                Robotics
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Medicine and Health Sciences
                Health Care
                Health Care Policy
                Computer and Information Sciences
                Network Analysis
                Medicine and Health Sciences
                Health Care
                Health Care Providers
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Cardiovascular Procedures
                Cardiac Surgery
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Endocrine System Procedures
                Thyroidectomy
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Reproductive System Procedures
                Prostatectomy
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Surgical Excision
                Prostatectomy
                Custom metadata
                All relevant data are available on figshare (URL: http://dx.doi.org/10.6084/m9.figshare.95635) and can be accessed through DOI: 10.6084/m9.figshare.5209048.

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                Uncategorized

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