Learning Objectives Matrix in DIM.RUHR: A Didactic Concept for the Interprofessional Teaching of Data Literacy in Outpatient Health Care.

Abstract

(1) Background: Each year, significant volumes of healthcare data are generated through both research and care. Since fundamental digital processes cannot function effectively without essential data competencies, the challenge lies in enhancing the quality of data management by establishing data literacy among professionals in outpatient healthcare and research. (2) Methods: Within the DIM.RUHR project (Data Competence Center for Interprofessional Use of Health Data in the Ruhr Metropolis), a didactic concept for interprofessional data literacy education is developed, structured as a learning objectives matrix. Initially conceived through a literature review, this concept has been continually developed through collaboration with interprofessional project partners. The study was conducted between February 2023 and June 2024. (3) Results: The foundational structure and content of the didactic concept are based on various scientific studies related to general data literacy and the outcomes of an interactive workshop with project partners. Eight distinct subject areas have been developed to encompass the data literacy required in healthcare professions: (1) Fundamentals and general concepts, (2) ethical, legal, and social considerations, (3) establishing a data culture, (4) acquiring data, (5) managing data, (6) analyzing data, (7) interpreting data, and (8) deriving actions. Within these, learners' data literacy is assessed across the four competency areas: basic, intermediate, advanced, and highly specialized. (4) Conclusions: The learning objectives matrix is anticipated to serve as a solid foundation for the development of teaching and learning modules aimed at enhancing data literacy across healthcare professions, enabling them to effectively manage data processes while addressing the challenges associated with digital transformation.