Data management and quality assurance

Abstract

Clinical data management is a vital vehicle in clinical trials to ensure the integrity and quality of data being transferred from trial subjects to a database system. Poor management of data is a pitfall to statisticians, study investigators, sponsors, and most importantly, patients. Efforts in quality assurance in clinical data management have been increasing, as reflected in the increase of related publications in MEDLINE during the past 10 years. Despite the success of harmonization of Good Clinical Practice (GCP) in Europe, Japan, and the United States, no harmonized guideline on good clinical data management is available yet. We attempt to examine the current regulatory requirements on clinical data management and to discuss specific issues in data acquisition and data validation consistent with good clinical data management. In summary, good clinical data management currently means compliance with International Conference on Harmonization (ICH) GCP and Food and Drug Administration (FDA) guidelines. The three most important concepts for good clinical data management are implementation of quality control procedures, an audit trail, and quality quantification of the final database. They should all be dictated in standard operating procedures that are continually updated to the current best practice.