We have shown that our approach yields promising results, which can be used for local and cross-institutional DQ assessments. The developed frameworks provide useful methods for interoperable and privacy-preserving assessments of DQ that meet the specified requirements. This study has demonstrated that our methodology is capable of detecting DQ issues such as ambiguity or implausibility of coded diagnoses. It can be used for DQ benchmarking to improve the quality of RD documentation and to support clinical research on distributed data.