Institute for Medical Informatics, University of Lübeck, Lübeck, Germany.
Clinic for Hematology and Oncology, UKSH, Lübeck, Germany.
Stud Health Technol Inform. 2022 May 25;294:307-311. doi: 10.3233/SHTI220464.
Around 500,000 oncological diseases are diagnosed in Germany every year which are documented using the International Classification of Diseases for Oncology (ICD-O). Apart from this, another classification for oncology, OncoTree, is often used for the integration of new research findings in oncology. For this purpose, a semi-automatic mapping of ICD-O tuples to OncoTree codes was developed. The implementation uses a FHIR terminology server, pre-coordinated or post-coordinated SNOMED CT expressions, and subsumption testing. Various validations have been applied. The results were compared with reference data of scientific papers and manually evaluated by a senior pathologist, confirming the applicability of SNOMED CT in general and its post-coordinated expressions in particular as a viable intermediate mapping step. Resulting in an agreement of 84,00 % between the newly developed approach and the manual mapping, it becomes obvious that the present approach has the potential to be used in everyday medical practice.
每年德国诊断出约 50 万例肿瘤疾病,这些疾病使用国际肿瘤疾病分类(ICD-O)进行记录。除此之外,肿瘤学中还经常使用另一种分类系统 OncoTree 来整合肿瘤学的新研究成果。为此,开发了一种将 ICD-O 元组半自动映射到 OncoTree 代码的方法。该实现使用了 FHIR 术语服务器、预协调或后协调 SNOMED CT 表达式和子集测试。已经应用了各种验证。结果与科学论文的参考数据进行了比较,并由一位资深病理学家进行了手动评估,证实了 SNOMED CT 通常以及其后协调表达式作为可行的中间映射步骤的适用性。新开发的方法与手动映射之间的一致性达到 84.00%,这表明该方法有可能在日常医疗实践中使用。