The Future of Education

Every year, a large amount of real-world data (RWD) is generated through research and care in the healthcare sector. Handling this data requires professional knowledge and experience among healthcare professionals, including in outpatient care. The varying and often inadequate data competencies across different settings can affect the quality of data creation, storage, processing, and use [1]. Essential digital processes cannot run adequately without fundamental data skills [2], raising the question of how to improve quality in handling RWD by establishing comprehensive data skills among professionals in outpatient care and research. The DIM.RUHR project (Data competence center for the interprofessional use of health data in the Ruhr metropolis, funded by the German Federal Ministry of Education and Research) addresses this by developing a didactic concept for interprofessional teaching of RWD skills through a learning objectives matrix (LOM).The content is based on scientific papers on teaching general data literacy and results from an interactive workshop with project partners. The LOM will be continuously refined through evaluation with interprofessional project partners. It guides the design of learning modules tailored to the needs of various professions in outpatient healthcare and research. The LOM maps data competencies across different disciplines and categorizes required knowledge, skills/abilities, and (value) attitudes into four competence areas. It is expected to provide an adequate foundation for developing teaching and learning modules to promote RWD competencies. This will enable professionals in outpatient healthcare and research to expand their skills and knowledge effectively for the proficient management of all data processes. 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.