A large number of healthcare organizations now utilize some method of storing electronic health record (EHR) data. This has simplified the storage of medical records but because of differences in the EHR systems and their databases has greatly increased the difficulty in exchanging electronic clinical data. There are a fair share of methods and applications available for conducting comparative effectiveness research (CER). But there has not been a consensus on developing a standard for conducting CER. Semantic interoperability has been identified as a major obstacle in exchanging electronic health information in CER studies. In order to better understand this issue, we utilized qualitative methods to measure data retrieval, information loss, and evaluate the semantic interoperability amongst Common Data Models (CDM). We compared several existing models from a sample of representative clinical research organizations: Observational Medical Outcomes Partnership (OMOP), Biomedical Research Integrated Domain Group (BRIDG), the Clinical Data Interchange Standards Consortium (CDISC), and the US Food and Drug Administration (FDA). We mapped data from a single institution-based clinical data warehouse for research (CDWR) to each CDM. The results of the data mapping were then tested by using two case study scenarios to assess the CER functionality. We found that the CDM from OMOP was the most complementary to the needs of conducting CER studies and had the most functionality amongst the data models. However, there was a need for modifications to each of the data models to meet the needs of the use cases and to interoperate with the CDWR.