Development and evaluation of a graduate surgical skills curriculum: How to make medical simulation data Findable, Accessible, Interoperable and Reusable

Introduction
Increasingly more simulation studies are published under the Open Access publishing model making them freely accessible online to everyone. Often, the only aspect that is not yet open are the underlying datasets from these publications. Publishing datasets improves reproducibility and reliability of research, it increases visibility of research, and accelerates innovation. Furthermore, unique and highly valuable data from i.e. simulation-based training or surgical techniques is not available to everyone.

Our aim is to present a best practice for publishing medical simulation data. A study on development and evaluation of a proficiency-based and simulation-based surgical skills training for technical medicine students is used as an example.

MethodsA four-station procedural assessment was developed of basic surgical tasks that included scrubbing and donning, local anaesthesia, incision/excision, and suturing. Performance indicators were determined by an expert panel consisting of four professors in surgery and two technical physicians in surgery. A rubric was developed for scrubbing and donning and procedure-specific rating scales were developed for local anaesthesia, incision/excision, and suturing. The surgical skills training was evaluated after at least one clinical rotation with an online survey.

Data are published according to the FAIR principles: Findable, Accessible, Interoperable and Reusable. To be ‘Findable’, a unique digital object identifier (DOI) was assigned to the dataset, and metadata described the content, contact information, location, items and definitions. The data repository is indexed by search engines, i.e. Google Scholar. The data is ‘Accessible’ for everyone under Open Access. To be ‘Interoperable’, MeSH standards were used. Finally, to be ’Reusable’, the data were made readable by translating and describing the assessment scoring rubrics, addition of documentation, and a license permitting data reuse was assigned.

Results & DiscussionData for 116 master students from two academic years were refined, and student and assessor data anonymised. Age information was grouped by age intervals, so it can be openly published in an external repository. The dataset was made publicly available in the 4TU.ResearchData repository for reuse in i.e. SESAM community. Researchers should be attributed when data is reused under a CC-BY-SA licence.

For medical simulation studies, it is feasible to publish data alongside Open Access peer-reviewed journal articles. The FAIR principles for data management should be incorporated in the design and implementation of future simulation studies._{Clinical speciality keyword
Surgery
References/Acknowledgements}The authors gratefully acknowledge the Noun Project for the Figure icons: "find" by Adrien Coquet, "context" by Nithinan Tatah, "padlock" by Fahmihorizon, "Recycle" by sripfoto.Underlying study: Halfwerk, F., Groot Jebbink, E., & Groenier, M. (2020). Development and Evaluation of a Proficiency-based and Simulation-based Surgical Skills Training for Technical Medicine Students. MedEdPublish, 9(1), [3523], https://tinyurl.com/Halfwerk2020