Concept mapping for supporting the differential diagnostic generation of hypotheses in the case-based online learning system CASUS: Qualitative improvement of dagnostic performance through ICD-10 coding

Kernt, Marcus; Holzer, Matthias; Bauer, Daniel; Fischer, Martin R (2008). Concept mapping for supporting the differential diagnostic generation of hypotheses in the case-based online learning system CASUS: Qualitative improvement of dagnostic performance through ICD-10 coding. GMS Zeitschrift für medizinische Ausbildung, 25(3), Doc91. German Medical Science

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Introduction: Concept mapping tools have long been established in medical education as an aid for visualizing learning processes in computer-based programs. The case-based learning system CASUS with its mapping tool for visualizing the differential diagnostic reasoning process is an example. It was shown that such tools are well accepted by users and lead to an increased number of diagnostic hypotheses being visualized as maps. However, there is scarce evidence on the quality of user-generated diagnostic hypotheses. This study examines the quality of diagnostic hypotheses obtained with CASUS and whether the quality can be improved through ICD-10 coding as compared with an expert’s solution.

Methods: We randomized 192 third-year medical students at the University of Munich into two groups. The students worked in groups of two on one computer.

Group A was asked to code their diagnostic hypotheses with an ICD-10 coding browser before entering them into the mapping tool.

Group B generated their hypotheses without prior ICD-10 coding. The differential diagnostic reasoning visualizations were analyzed quantitatively and qualitatively. An expert solution was used as reference.

Results: Eighty-seven differential diagnoses were evaluated. Group A, using ICD-10 coding, made the correct and precise diagnosis of malaria tropica significantly more often than Group B (p < 0.05). For additional alternative diagnostic hypotheses, no quantitative or qualitative differences were detected.

Conclusions: ICD-10 coding in connection with a mapping tool supporting the diagnostic reasoning process improved the accuracy of diagnostic performance in third-year medical students in the case of malaria tropica.

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