ArticlePloS one2017
Network analysis of surgical innovation: Measuring value and the virality of diffusion in robotic surgery.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Induced Bias Due to Crossover Within Randomized Controlled Trials in Surgical Oncology: A Meta-regression Analysis of Minimally Invasive versus Open Surgery for the Treatment of Gastrointestinal Cancer.Annals of surgical oncology · 2018Pooled it
- Knowledge translation in surgery: a scoping review of implementation strategies, effectiveness and contextual barriers and enablers.BMC health services research · 2025Article
- Review
- Novel Strategies for Managing Retropharyngeal Lymph Node Metastases in Head and Neck and Thyroid Cancer with Transoral Robotic Surgery (TORS).Annals of surgical oncology · 2022Review
- Shared Learning Utilizing Digital Methods in Surgery to Enhance Transparency in Surgical Innovation: Protocol for a Scoping Review.JMIR research protocols · 2022Article
- Innovation in Orthopaedics: Part 2-How to Translate Ideas and Research into Clinical Practice.Current reviews in musculoskeletal medicine · 2022Review
- Quo Vadis Anesthesiologist? The Value Proposition of Future Anesthesiologists Lies in Preserving or Restoring Presurgical Health after Surgical Insult.Journal of clinical medicine · 2022Article
- How Warmth Appeal Affects Persuasion: The Moderating Role of Brand Concepts.Frontiers in psychology · 2022Article
- FibVID: Comprehensive fake news diffusion dataset during the COVID-19 period.Telematics and informatics · 2021Article
- Analysis of relative bacterial activity and lactate dehydrogenase gene expression of caries-associated bacteria in a site-specific natural biofilm: an ex vivo study.Clinical oral investigations · 2021Article
- Robotic-assisted interval cytoreductive surgery in ovarian cancer: a feasibility study.Obstetrics & gynecology science · 2020Article
- Evaluating the implications of Brexit for research collaboration and policy: a network analysis and simulation study.BMJ open · 2019Article
- Extracervical Approaches to Thyroid Surgery: Evolution and Review.Minimally invasive surgery · 2019Review
- Robotics in cardiac surgery.Annals of the Royal College of Surgeons of England · 2018Review
- Robotics in otorhinolaryngology - head and neck surgery.Annals of the Royal College of Surgeons of England · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundExisting 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
methodsNetwork 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®).
resultsRankings 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).
conclusionNetwork 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.