Background: Common data model (CDM) is a standardized data structure defined to efficiently use different sources in hospitals. A study using the CDM is scarce for orthopedic outcome researches due to the complexity of variables. We aimed to test the feasibility of applying CDM in the orthopedic field and analyzed risk factors for periprosthetic joint infection (PJI) after total joint arthroplasty (TJA) using CDM.Methods: We undertook a retrospective cohort study of all primary and revision hip and knee TJAs at our institution from January 2003 to October 2017. We identified potential risk factors for PJI after TJAs in the literatures, which included preoperative demographic/social factors, previous medical history, intraoperative factors, laboratory results and others. The data sourced from EMR was extracted, transformed, and loaded into CDM.Results: Variables such as demographic/social factors, medical history and laboratory results could be converted into CDM, but the other known risk factors could not. In total, 12,320 primary hip and knee TJAs and 120 revision arthroplasties were identified. Among them, 34 revisions were done because of PJI. Risk factors of PJI were hypertension and urinary tract infection after total hip arthroplasty, and age (70-79 years), male sex, anemia, steroid use, and urinary tract infection after total knee arthroplasty. Conclusions: This study demonstrates that orthopedic outcome researches using CDM is feasible although data converting to CDM was possible for limited factors. Further data transforming technologies need to be developed to analyze more factors relevant to orthopedic area, such as intraoperative factors and imaging findings.