Background: Data management related to progress and professional competency examinations in medical education is of paramount importance due to its pivotal role in ensuring educational quality and driving instructional decision-making. However, the data lifecycle of these examinations—including design, execution, psychometric analysis, and reporting—operates in a fragmented and siloed manner within Iranian institutions, such as the Medical Education Assessment Center. This fragmentation leads to challenges like data dispersion, lack of standardization, and critical security vulnerabilities. This study aimed to design and validate a comprehensive data management model to enhance the current situation.
Methods: This research employed an exploratory-descriptive mixed-methods approach. The qualitative phase utilized meta-synthesis and interviews with 16 experts to extract challenges and formulate the initial constructs of the model. In the quantitative phase, the model's relationships were validated using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique, based on a survey instrument administered to a sample of 142 specialists and administrators.
Findings: The proposed model organizes the DAMA-DMBOK framework by contextually reducing and adapting it into four core, localized dimensions relevant to the medical examination domain: 1) Data Governance and Security, 2) Data Quality, 3) Reference and Master Data Management, and 4) Data Architecture and Infrastructure. The PLS analysis results, demonstrating a good model fit (R2 for dependent variables and positive Q2), indicated that Data Governance is the strongest driving factor in improving Data Quality and Master Data Management within these institutions.
Conclusion: The implementation of this contingency model is expected to successfully upgrade examination data management by increasing data accuracy, enhancing security, and facilitating strategic educational decision-making. The findings contribute theoretically to the contextualization of international data management frameworks (such as DAMA) in academic environments and provide structured, practical solutions for Iranian medical education institutions to transition from fragmented systems to a secure and integrated data system.