Quality Management
The issue of bias in analytical measurements generates a lot of debate. Existential debates (does bias exist? should it?) are often mixed with more practical debates (what's the best way to calculate bias?). Here's a description of the different kinds of bias that (might?) exist in the laboratory.
A description of the variables, equations and all the mathematical details behind the Quality Planning models.
How many runs does it take before your instrument will detect a medically important error? This is a basic question that other industries take great pains to determine - so why is it healthcare laboratories generally don't know the answer? Dr. Westgard explains how this number can be calculated - and how new technologies in the lab are creating a new way to describe the performance of QC procedures
This is a lesson on how to determine the performance of a QC procedure using a table of areas under a normal curve. At the intersection QC Design, Six Sigma, statistics, and QC - you can establish your capability to detect an important medical error
QC Selection Grids are quick planning guides for your single rule or multirule selection. If you know how often you have problems with a method (and you do know, don't you?) and can calculate the method's critical-error (we give you an online calculator to do it for you), then you can find out the best rule for your method.