[Establishment of a German ICCR dataset : Translation and integration of SNOMED CT using the example of TUR-B].

Abstract

Background: The structured recording of data from histopathological findings and their interoperability is critical for quality assurance in pathology.

Materials and methods: To harmonize the content of the reports, the International Collaboration on Cancer Reporting (ICCR) has defined standardized datasets. These datasets are not yet available in German nationwide. This gap is addressed here using the transurethral bladder resection (TUR-B) dataset as a use case.

Results: We describe the process of establishing the datasets by carrying out translation, mapping on SNOMED CT codes, and using SNOMED CTs hierarchy to fill dropdown menus. Furthermore, we identified rules for checking for self-consistency of reports by using the example of the TUR bladder.

Discussion: With this article, we have created an example of a German version of the ICCR TUR‑B dataset including mapping to the SNOMED CT terminology. Further activities should include the definition of overarching cancer disease models to further exploit the potential of SNOMED CT.