Creating Synthetic Patients to Address Interoperability Issues: A Case Study with the Management of Breast Cancer Patients.

Interoperability issues are common in biomedical informatics. Reusing data generated from a system in another system, or integrating an existing clinical decision support system (CDSS) in a new organization is a complex task due to recurrent problems of concept mapping and alignment. The GL-DSS of the DESIREE project is a guideline-based CDSS to support the management of breast cancer patients. The knowledge base is formalized as an ontology and decision rules. OncoDoc is another CDSS applied to breast cancer management. The knowledge base is structured as a decision tree. OncoDoc has been routinely used by the multidisciplinary tumor board physicians of the Tenon Hospital (Paris, France) for three years leading to the resolution of 1,861 exploitable decisions. Because we were lacking patient data to assess the DESIREE GL-DSS, we investigated the option of reusing OncoDoc patient data. Taking into account that we have two CDSSs with two formalisms to represent clinical practice guidelines and two knowledge representation models, we had to face semantic and structural interoperability issues. This paper reports how we created 10,681 synthetic patients to solve these issues and make OncoDoc data re-usable by the GL-DSS of DESIREE.