Limits and Limitations Limits and Limitations

Statistical quality control has a long history in healthcare laboratories, being first introduced in the 1950s by Levey and Jennings [1]. They adapted Shewhart's industrial QC approach that utilized mean and range charts [2] for use with duplicate measurements on patient pools. Henry and Segalove [3] did much to make QC practical and actually were responsible for the “single-value ” type of QC chart that is now known as the Levey-Jenning's chart. As automated analytic systems became common in the 1960s, QC took on new importance and was widely applied. As multichannel automated analyzers were introduced in the 70s, difficulties with QC became apparent due to the high frequency of false rejections [4]. Westgard multi-rule QC [5] was developed to minimize the false rejections due to 2 SD control limits and improve the low error detection when 3 SD control limits were employed. High-stability high-precision analyzers became common by the 1990s, leading to “cost-effective ” design of QC procedures to minimize cost (false rejection, number of control measurements) and at the same time maximize quality (error detection) [6]. Today's 5th and 6th generation automated analyzers can often be effectively managed with minimum QC, assuming the selection of appropriate control rules and number of control measurements [7] and assuming that the control limits are properly established [8]