The controls that I am using currently stopped giving values (& ranges) for Sodium & Potassium. What is the correct way to arrive at values for these analytes. I am unsure of exactly how to get a range. I ran 20 of each & arrived at a mean & set a pretty tight range. I also use the known standards used in testing to make sure that I can recover the values & do recover them well.Thanks for your help. Middleboro, MA
Realize that the purpose of the values listed on the product insert for assayed QC materials is really only for guidance, since these values generally are determined from several instruments across several laboratories. Laboratories use these values to assess the values obtained in their settings. Quality control materials that do not include expected mean and ranges of values for particular analytes are termed unassayed QC products.
Establishing the means and SDs for sodium and potassium using unassayed materials is no different than for what is done with assayed materials. However you must know that the method is generating correct (accurate) patient results. Accuracy assessment determines if a method yields the “right” answers and is evaluated by at least one of the following: (a) assaying materials with assigned or known values, (b) comparing patient specimen results with a method in long standing use and known to be accurate, (c) verifying results from interlaboratory (voluntary or regulatory) survey data, or (d) splitting specimens with another laboratory. CLIA and all professional accreditation organizations require test sites to evaluate accuracy prior to implementing a method for routine use as part of the performance specification evaluation for nonwaived test methods.
Analyzing 20 QC samples over a period of time to include variations in analyts, instrument maintenance, reagent, and calibrator changes, etc. is the recommended practice. The mean and SD are then used to establish performance limits. In selecting QC rules, the laboratory director is expected to understand the implications of rule selection in terms of medical significance and probabilities for error detection and false rejections. For example, in selecting a + n SD rule, remember that with two controls per run, the false rejection rate for the + 2.0 SD rule is approximately 10% and for the + 3.0 SD rule about 1%. The false rejection increases when the number of controls increases. The false rejection rate for + 1.0 SD rule is approximately 32% when only one QC is analyzed. Therefore, pick rules carefully to maximize error detection and minimize false rejection, since all out of control situations need to be investigated. The best approach to selecting QC rules is to base the decision on an identified quality goal and the method’s (in)accuracy and (im)precision.
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