Statistical Quality Control is paramount for accurate medical testing in the clinical laboratory.  In the healthcare environment, analyte assays have come under the regulatory spotlight, and have also made the news, as an area of significant deficiency.  The cause of deficiency in these cases resulted from the absense of, or insufficient application of, proper QC protocols.  This type of statistical QC deficiency can be seen not only in many clinical testing laboratories but also in the operations of diagnostic test kit manufacturers.   Simultaneously, as CLIA and other regulatory agencies tighten up the quality requirements, the population of laboratorians are, of necessity, playing catch-up in what is often, to many, a little known subject area.  Today, this education effort is generally carried out in the midst of an environment of higher caseload volumes and greater demands on turnaround time. Choices surrounding quality control processes in the laboratory are handled as each institution sees best fit.  On the other hand, all the decisions surrounding the process of accepting or rejecting a given run of tests must follow clearly defined rules.  The applied set of rules for a given test usually arises as some combination of minimally meeting compliance directives, and the institution’s own guidelines for providing the best results to patients, based, in part, upon the unique nature of each specific test under consideration.  Putting this initiative into place, including research, training and ongoing deployment, is a major investment of time and money. Factored strongly in choosing specific quality control processes are also the practical considerations of long and short-term costs involved.  The minimization of potential litigation is one very important consideration for this reason, in addition to the desire for best serving patients and preserving reputation.  Good statistical QC in itself, without the ability to easily create accurate documentation, is, therefore, a pitfall to be avoided.  Having a sensitive testing methodology which can minimize the number of costly re-runs would also be important.   Evaluating whether or not a given test has satisfactorily passed the set of rules in place can be a tedious and time-consuming manual process requiring additional personnel.                                                                        Why QCflex?