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DIM.RUHR: Interprofessional teaching of data competencies in outpatient care Background Methods Discussion •Handling the increasing amount of data in healthcare research and care requires specialist knowledge and experience on the part of healthcare professionals •The varying and often inadequate data competencies across different settings can affect the quality of data creation, storage, processing, and use DIM.RUHR (Data competence center for the interprofessional use of health data in the Ruhr metropolis) addresses this by creating high-quality teaching and learning modules for specific target groups in the healthcare domain. By focusing on improving data competencies, the DIM.RUHR project aims to enhance the overall quality of RWD handling, contributing to better healthcare outcomes through more efficient and effective use of data. (johnstocker_vector/vecteezy.com) Results How can the quality of handling RWD be improved by establishing comprehensive data literacy among professionals in outpatient care and research? Scan QR code and take a look at our LOM in detail MODULES TOPICS Fundamentals and overarching concepts Basic understanding of data General principles and concepts of RDM Research data policies Data management plans FAIR principles Open data/source/science/… Ethics , legal, and social considerations General legal aspects Data protection and personal data Special considerations for health/patient data Critical thinking Establishing a data culture Identifying data applications Specifying data applications Coordinating data application Acquire data Modeling data applications Data collection and curation Data evaluation and ensuring data quality Manage data Data structure Data manipulation Data preparation Meta data and meta data standards Data protection and data maintenance Data storage and restoriation Publication paths for data; repositories Analyze data Data tools Evaluate data Interpret data Data comprehension Present data Derive actions Identify opportunities for action Evaluate impact LOM • Learning objectives matrix as a basis for the development of teaching and learning modules • Structure based on Petersen et al. (2022), initial content based on literature research and adaption for target group through workshops OER search • Identification of suitable material for reuse • Use of a self-constructed evaluation catalog for the quality assessment of existing OER (open educational resources) materials • Identification of gaps in content in existing material Guideline • Development of a guideline for the creation of high quality OER • Based on existing recommendations and established didactic concepts OER creation • Creation of own material (in particular filling content gaps and addressing the target groups through case studies) Visit our website! LOM contents OER search: Evaluation catalog and result example SEARCH RESULT example Module „acquire data“ Initial results: N = 8 798 End results: n = 113 Conclusion of entire search: Most of the material is not healthrelated, much of it is aimed at an academic audience and specifically related to RDM •Audio •Video •Text •Form and design • Media format Production quality • Structure •References • Social aspects Formal criteria • Motivation • Learning objectives •content Content quality Guideline topics Pros and cons of different formats Fundamentals of OER Quality criteria Implementation recommendations *Exclusion and no further consideration if OER does not meet minimum requirements * * * * * * How-to OER 1. Define topic and learning objectives 2. Determine target group 3. Select the appropriate format 4. Use open licenses correctly and observe legal requirements 5. Structure content and prepare it for teaching purposes 6. Plan technical implementation 7. Create and test material 8. Perform quality assurance 9. Publish and make available
