OBJECTIVES: Healthcare resource utilization and costs are often measured by retrospective claims analyses. Using a common data model (CDM) with standardized variables has the ability to enhance robustness and generalizability of data and improve the timeliness of these studies. Given the rapidly changing treatment landscape for HCV, it is a prime candidate for research based on a CDM. The purpose of this study was to analyze healthcare resource use and costs by comorbidity status in patients with chronic HCV using a virtual database based on a CDM.    METHODS: A virtual database was created with 3 large commercially available datasources using specifications developed by Observational Medical Outcomes Partnership (OMOP) CDM v4 format (www.omop.org/CDM). By employing a massively parallel processing (MPP) database platform we created this database with 30+ standardized variables as needed for this study. Utilizing this virtual database allowed for comparison of demographic, clinical, and healthcare utilization variables analyzed simultaneously across the large databases for patients with HCV.  RESULTS: Results from two of the databases (1 commercial/Medicare, 1 commercial only) representing more than 212,000,000 covered lives yielded information for 97,935 patients with chronic HCV (n=46,384 for database 1; n=