Developing Country-Specific Charlson Comorbidity Index Mappings for Use with German Administrative Data: Methodological Comparative Study.

BACKGROUND: The Charlson Comorbidity Index (CCI) is widely used to quantify comorbidity burden in observational research. Applying it to real-world data requires accurate ICD-based mappings. The commonly used mapping by Quan et al. (2005) does not reflect current German coding standards. OBJECTIVE: To develop year-specific mappings (2004 to 2026) based on the German Modification of ICD-10 for the CCI with an open-source implementation and compare them with the mapping by Quan et al. METHODS: For each year, mappings were curated via independent dual review with consensus. In 515,827 inpatient cases from a German tertiary center (2010-2024), year-appropriate mappings and Quan's mapping were applied and the results pooled into two respective datasets that were subsequently compared. Agreement was assessed using the Intraclass Correlation Coefficient (ICC) (two-way mixed-effects model for absolute agreement based on single measurement), and the significance of the discordances was measured using McNemar's test. RESULTS: Agreement was very high; 3.13% of cases differed. A single code was present in 49% of the discordant cases and was intentionally excluded in the new mappings as not diagnostic for the category it was assigned to. Discordant results were found in 9 out of 17 categories with the leading categories "peripheral vascular disease", "mild liver disease" and "severe liver disease" being present in respectively 52%, 17% and 16% of the discordant cases. After filtering the dataset to only include observations with any diagnosis of a malignant disease, 6.86% of cases differed, and 79% of those differences were caused by the category "peripheral vascular disease", suggesting significant discrepancies for specific research questions. CONCLUSIONS: We provide transparent, year-specific ICD-10-GM (2004-2026) mappings and an open-source tool for CCI calculation. The mappings align with current German coding practice and enable reproducible, year-appropriate comorbidity adjustment using administrative data.