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

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.