A Practical and Efficient Approach to Database Quality Audit in Clinical Trials

Abstract

In clinical trials, data quality is one of the key factors in determining the success or failure of a drug development program. Data audit is an important step in assessing and ensuring the quality of clinical databases. However, despite the availability of many sophisticated statistical methodologies in analyzing clinical data, there are few data audit methods that are both efficient and statistically sound. A frequent method is auditing data for a fixed percentage of the subjects in a clinical study. Such a method either wastes too many resources or lacks statistical rigor in determining the quality status of a database. In this article, we give a short review of some recent developments and provide an example of database audit strategy. The methodology was developed for, and applied to, a real clinical study. Such a method is both statistically sound and efficient in saving resources needed for the conduct of the audit.