Physical examination, clinical tests and electrophysiological methods are used in the diagnosis of carpal tunnel syndrome (CTS). However, in practice there are no standard clinical and electrophysiological tests for clinics and laboratories. Therefore, data fragmentation or incompatibilities may occur in Electronic Health Record (EHR) systems. Furthermore, secondary use and different biomedical research targets are not considered in these EHR systems. During routine documentation, incomplete, incorrect, inconsistent data entry and incorrect coding can be done. This study aimed to develop an EHR system that could be used in different clinics and centers in diagnosis of CTS, thus creating a standardized, high quality, predictive, preventive, personalized and real-time participatory CTS biomedical data warehouse. The CTS-based EHR system was developed using Microsoft Visual Studio C # programming language. Also during a new patient record, the system was supported by a clinical decision support system (CDS S) based on the data mining methods using WEKA program for pre-diagnosis of the CTS. This EHR system also allows clinical and electrophysiological test results as well as genetic and environmental variants to be integrated into a single database within the framework of precision medicine approachment. In addition, this system can provide a large scale accurate and complete data warehouse for secondary use purposes.