Verification of Data Completeness and Accuracy

Abstract

Complete and accurate data is the backbone of any database. Rigorous, objective, and transparent verifi cation processes are vital to establishing and maintaining high quality data. In the absence of such processes, a database cannot be relied upon to properly inform database participants and users. Data about outcomes occupy an increasingly pivotal role in decisions that impact quality of care, professional reputation, reimbursement, and health care policy, to name a few. These developments underscore the importance of robust data verifi cation processes. Data verifi cation may be accomplished using several means, including on site visits and remote source document verifi cation. The emergence of central statistical verifi cation techniques using adaptive or triggered monitoring in real time is an important development. This approach to data verifi cation has the potential of signifi cantly improving both the volume and quality of verifi ed data as well as limiting the resource utilization impact on databases and their participants.Florence Nightingale is widely credited with being the fi rst person to advocate for the collection, analysis, and public reporting of surgical outcome data [ 1 ]. Complete and accurate data are fundamental to database quality and associated outcomes analysis. In the absence of complete and accurate data, the power of a database as an instrument of outcomes measurement and a platform for quality improvement is severely diminished.