# Secure Delivery Scheme of Common Data Model for Decentralized Cloud Platforms
## Materials and Methods
### Materials
#### 2.1.4 Common Data Model (CDM)  
In medical and pharmacy research, the management of sensitive medical information such as patient information and safety issues are emerging domestically and abroad, and the medical community is paying attention to the possibility of utilizing a highly objective and safe research through the use of a CDM. Therefore, the introduction of CDM is increasing in domestic and overseas hospitals. The analysis of a lot of real data utilizes the CDM system. For example, it facilitates analysis across data sources by standardizing terms for drug use, medical events and procedures, data structure, and data interpretation [25].  
Electronic Health Records (EHR), which are widely used in hospitals, are rapidly ubiquitous in the medical field, but their use in biomedical and clinical research is limited due to interoperability issues and technical requirements. Therefore, software that directly interacts with previously constructed EHR data utilizing the extracted CDM data can make the data more accessible to users with limited computing expertise or domain knowledge, or EHR-based users, and accelerate related research. Moreover, we introduce PatientExploreR, a scalable application built on the R/Shiny framework that interfaces with a relational database of EHR data in Observational Medical Outcomes Partnership CDM (OMOP-CDM) format, which generates patient-level interactive dynamic reports and provides clinical data without programming [26].  
Based on the EHR system, CDM has been expanded and built to enable the analysis and comparison of Adverse Drug Reactions (ADRs), whose data structures are integrated with other external organizations. It provides a basis for collaborative research, analysis, and comparison between institutions in which the same type of CDM has been built, and provides an environment in which the same research can be conducted simultaneously on a variety of data sources [27].  
The use of standard Health Information Exchange (HIE) data is increasing due to operability. However, the integration of HIE data into the EHR system has not yet been studied. To ascertain the quality of these data, referral documents from the Health Level 7 (HL7) Clinical Document Architecture (CDA) are converted to a CDM, to facilitate HIE data availability for longitudinal data analysis and to identify data quality levels. The CDA document was used to define the mapping rules for CDA-CDM conversion, confirming that CDM conversion was possible [28]. In addition, it has succeeded in transforming EHR into a common data model for Observational Health Data Science and Informatics (OHDSI), and this method can provide various opportunities for researchers and data holders [29]. Data integration is an important task in healthcare information and has a huge impact on what you get from existing health information data. Research using the OMOP-CDM, a common data model used to unify the data structure of each institution, is continuously being conducted in several countries. In France, a feasibility assessment was conducted for the implementation of the national electronic health record, which standardizes data and facilitates data exchange, sharing, and storage, using a CDM. This is especially the case when data are collected through different heterogeneous systems. CDM also provides tools for data-quality assessment, model integration, visualization, and analysis. An extract-transform-load process was implemented to feed data from the French healthcare system to the OMOP-CDM, and, as a result, 17 vocabularies corresponding to the French context were added to the concept of the OMOP-CDM [30].