How we avoid patient shortage with an integrated analysis of learning objectives and clinical data during development of undergraduate medical curricula.
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| Title: | How we avoid patient shortage with an integrated analysis of learning objectives and clinical data during development of undergraduate medical curricula. |
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| Authors: | Balzer, Felix1 (AUTHOR), Bietenbeck, Andreas1 (AUTHOR), Spies, Claudia1 (AUTHOR), Dittmar, Martin1 (AUTHOR), Lehmann, Lars1 (AUTHOR), Sugiharto, Firman1 (AUTHOR), Ahlers, Olaf1 (AUTHOR) olaf.ahlers@charite.de |
| Source: | Medical Teacher. Jun2015, Vol. 37 Issue 6, p533-537. 5p. |
| Subject Terms: | *Curriculum planning, *Teaching aids, *Behavioral objectives (Education), *Undergraduates, Health care rationing, Study & teaching of medicine, Nosology |
| 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. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
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| 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. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 0142159X |
| DOI: | 10.3109/0142159X.2014.955844 |
