Abstract
Background/Aims Quality Assurance is a broad term with widely varying expectations about the nature of QA activities. The HMORN Virtual Data Warehouse (VDW) has an expanding set of quality assurance data checks. These checks improve the reliability and consistency of the data across sites. By reviewing several real-world examples, we will step through and evaluate several of the ‘FYings’ of quality assurance work. Q1: Can we justiFY QA? Q2: Can we codiFY QA? Q3: Can we quantiFY QA? Q4: Can we demystiFY QA? And finally Q5: Can we commodiFY QA?
Methods Masking site information, we will review specific examples of current quality assurance work, asking each question for each example. We will then describe each set of QA activities and include tables, graphs, comments, dissemination information, actions (or inactions) that happen after the QA review.
Results Quality assurance is definitely a hot topic, although perhaps misunderstood. We often think there are electriFYing moments when we discover and save a project from disaster. We think it will indemniFY our projects from failure. Investigators ediFY it. But have we convinced funders to commodiFY QA?
Discussion We will clariFY whether quality assurance is a commodity.
