Quality Requirements and Standards
An extended version of an essay originally prepared for the September 2013 issue of Clinical Laboratory News. It discusses how "total" our "total error" should be. Back when Total Analytic Error was introduced, it was clear that it concentrated on the analytical step. Over the years, "mission creep" has tempted others to keep expanding the types of errors to be considered.
A recent advisory report on the NHS, chaired by Dr. Don Berwick, has valuable lessons for all healthcare systems: Sometimes we can hit a goal, but miss the point. But while the report acknowledges this truth, it also says the opposite can be true as well: sometimes we can set a goal we'll never be able to hit, and that, too, can be harmful to our healthcare system. So we bring the issue to laboratory quality requirements: do we have goals that are too hard (or too easy) to hit?
The use of Quality Indicators (QI) is an important indicator that a laboratory has embraced and implemented a Quality Management System (QMS). But which Quality Indicators should a laboratory choose? And what does a particular QI tell us? As it turns out, some QIs are more important than others.
Here's a recent example proving the importance of the choice of quality requirement. A laboratory was reviewing the performance of a cholesterol method. By one local standard, the performance was not acceptable. By another standard (CLIA), it was. So is the method good or not? Which quality requirements are right? This case study looks at a number of quality requirements and compares them.
Molecular diagnostics is a field exploding with growth. Next Generation Sequencing (NGS), RNA and DNA microarrays, mass spectrophotometry are poised to enter the clinical laboratory. Special challenges arise when we try to apply "traditional" quality control and quality assurance models to these new testing technologies. Not only will we need to adapt current quality thinking to the practical realities of the new tests - we will definitely need to avoid repeating the mistakes we made in our traditional QC approaches.