How we avoid patient shortage with an integrated analysis of learning objectives and clinical data during development of undergraduate medical curricula

Abstract

Access to patients is a crucial factor for student-centred medical education. However, increasing numbers of students, teacher shortage, a patient spectrum consisting of rarer diseases, and quicker discharges limit this necessary access, and therefore pose a challenge for curriculum designers. The herein presented algorithm improves access to patients in four steps by using routinely available electronic patient data already during curriculum development. Step I: Learning objectives are mapped to appropriate ICD-10 (International Statistical Classification of Diseases) codes. Step II: It is determined which learning opportunities need to be considered first for patient allocation in order to maximise overall benefit. Step III: Hospital’s departments with the highest expertise on respective learning objectives are assessed and selected for teaching. Step IV: Patients of the chosen department that present the best match for a given learning opportunity are assigned to participation. This integrated analysis of learning objectives and existing clinical data during curriculum development is a well-structured method to maximise access to patients. Furthermore, this algorithm identifies learning objectives of a curriculum that do not correspond well to the spectrum of patients of the respective teaching hospital and which should therefore be taught in learning formats without patient contact.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article.