Abstract Introduction Community learning is a key component for the progression of surgical innovation, which is itself crucial to advancing surgical practice. Assessment of learning curve’s (LCs) allow rigorous evaluation of new surgical procedures/devices and their introduction into clinical practice. The Idea–Development–Exploration–Assessment–Long-term (IDEAL) framework provides recommendations for the evaluation of new surgical procedures and devices throughout the stages of innovation. This study aimed to identify the current reporting practice of LCs in IDEAL studies. Method A systematic review was conducted to identify author-reported IDEAL/IDEAL-D studies of any IDEAL stage and surgical specialty. LC outcomes were extracted including information relating to surgeons’ experience and training, and methods for measuring and assessing the LC. Results Searches yielded 1411 publications, of which 59 studies met the eligibility criteria. Of these, 31 (53%) reported information on the LC, with only 3 (5%) studies measuring or reporting on LC in detail. 21 (36%) studies reported training for surgeons and 16 (27%) reported support or performance monitoring. Conclusions Despite IDEAL recommendations, reporting the LC was found to be rare in the included studies. Reporting of the LC in future studies is recommended to facilitate robust evaluation of new surgical procedures and devices.

Abstract Systemic risk (SR) is considered as the risk of collapse of an entire system, which has played a significant role in explaining the recent financial turmoils from the insurance and financial industries. We consider the asymptotic behavior of the SR for portfolio losses in the model allowing for heavy-tailed primary losses, which are equipped with a wide type of dependence structure. This risk model provides an ideal framework for addressing both heavy-tailedness and dependence. As some extensions, several simulation experiments are conducted, where an insurance application of the asymptotic characterization to the determination and approximation of related SR capital has been proposed, based on the SR measure.

Abstract Background Innovation in surgery is growing. The rigour of reporting of innovation must therefore be examined to ensure evaluations are thorough and transparent. The Idea, Development, Exploration, Assessmemt, Long-term follow-up (IDEAL) framework was developed in 2009 to help researchers evaluate innovative procedures. However, it is not known whether the IDEAL principles have been adopted into the reporting of robotic surgery. The aim of this study is to identify and summarise published literature for robotically assisted anti-reflux surgery, to understand whether evaluations are being performed in a robust way. Methods Systematic literature searches were undertaken to identify studies relating to robotic anti-reflux surgery. All primary research studies pertaining to robotically-assisted surgery for adults with symptomatic gastro-oesophageal reflux disease were included. Studies examining multiple interventions, where the outcomes could not be separated, were excluded. Data will be doubly extracted using tailored online forms. Data extraction themes include: study characteristics, technique description and evolution, governance/ethical factors and outcome reporting. Data will be synthesised into tables and summarised in a narrative synthesis. A meta-analysis will not be performed as we aim to examine reporting, rather than the efficacy of robotically-assisted anti-reflux surgery. Results 824 abstracts were identified, of which 80 were included for full text review. Summarised data will be used to propose a standard of reporting which will inform future work in the field. Conclusion The findings will feed in to the other six arms of RoboSurg to examine reporting in robotic upper gastrointestinal surgery more generally.

Abstract Introduction There is an increasing trend in novel robotic-assisted oesophagectomy in place of standard techniques, potentially due to its perceived technical benefits and improved post-operative outcomes. However, safety and efficacy remain uncertain and little is known about surgeons’ expertise in this complex procedure. This review aims to summarise the reporting of surgeons’ expertise in studies evaluating robotic oesophagectomy. Method Systematic searches of OvidSP, MEDLINE and Cochrane Library were conducted using key words for robotic surgery and oesophageal cancer. Searches were limited to human studies published up to February 2020. Studies reporting any type of outcome for robotic oesophagectomy were included. Data on quality assurance measures (e.g. type of centre, surgeons’ experience, study entry criteria) and learning curve assessments were recorded. Results Of 954 abstracts screened, 226 full texts were reviewed and 103 included. Two studies were clinical trials. There were 85 (82.5%) single and 6 (5.8%) multi-centred institutions. Forty-four (43%) stated the type centre(s) involved: general (n = 1), specialist (n = 41) or mixed (n = 2). Thirteen (13%) reported centres’ caseload of robotic and non-robotic oesophagectomies within a defined period. Seven described surgeons’ prior experience in robotic oesophagectomy, and 5 described experience in open/laparoscopic surgery. Two stipulated entry criteria for surgeons (training qualification and number of robotic oesophagectomies performed). Eighteen (17%) assessed the learning curve through changes in operating time, complications and conversion rates. Discussion There is currently inadequate reporting on surgeons’ expertise in robotic oesophagectomy, making comparisons with standard techniques challenging. This highlights the need for better transparency when reporting surgical innovation, as outlined by the IDEAL framework.

Abstract Introduction The IDEAL framework describes a series of stages through which surgical innovations typically pass. For each stage, the framework makes recommendations with the intention of improving the quality of research in surgery. Its adoption has been slow despite publication of practical guidance. It has been recognized that determining the stage of innovation of an invasive procedure or device can be problematic, and this issue may be hindering adoption of the framework. The aim of this study is to develop a practical algorithm for determining the stage of innovation of any invasive procedure or device. Methods Multiple data sources will be used: published literature, intra-operative video recording, interviews with stakeholders, healthcare datasets, and clinical policies and guidelines. Systematic reviews will be conducted to identify guidance relating to surgical innovation, and evaluations or critiques of guidance. Case studies of surgical innovations will be undertaken, to gain an understanding of problems encountered in determining stage of innovation. An algorithm will be developed through an iterative process of testing and refinement, triangulating data from the literature reviews and case studies. Results The findings of the initial systematic reviews will be presented. This will include guidance relating to surgical innovation, and evaluations or critiques of it. Recognized problems in determining stage of innovation will be summarized, including proposed solutions and suggestions for further development. Conclusion This study will use multiple data sources to develop a practical algorithm for determining the stage of innovation of any invasive procedure or device.

ABSTRACT Disability history is everyone's history. However, existing archival literature on disability focuses almost exclusively on issues of accessibility. Relatively little has been written on the challenges and opportunities present in strengthening disability history representation in archives. The author uses their experience as a contractor for a regional nonprofit to explore the nature of working with community members to strengthen disability history representation in archives and proposes documentation strategy as an ideal framework for such collaborations.

IntroductionApproximately £1130 billion was invested in research worldwide in 2016, and 9.6% of this was on biomedical research. However, about 85% of biomedical research investment is wasted. The Lancet published a series to identify five categories relating to research waste and in 2014. Some categories of research waste in surgery are avoidable by complying with the Idea, Development, Exploration, Assessment, Long-term follow-up (IDEAL) framework for it enables researchers to design, conduct and report surgical studies robustly and transparently. This review aims to examine the extent to which surgical studies adhered to the IDEAL framework and estimate the amount of overall research waste that could be avoided if compliance was improved.MethodsWe will search for potential studies published in English and between 1 January 2018 and 31 December 2018 via PubMed. Teams of paired reviewers will screen titles, abstracts and full texts independently. Two researchers will extract data from each paper. Data will be collected about general information and specialised information in each stage, and our IDEAL Compliance Appraisal tool will be used to analyse included studies. Descriptive statistics and χ2 or Fisher’s exact tests for comparisons will be presented.DiscussionOur study will provide important information about whether compliance with the specific IDEAL Recommendations has reduced research waste in surgical and therapeutic device studies. And we will identify particular key aspects that are worse and need to focus on improving those in future education.