Analyte stability in whole blood using experimental and datamining approaches.

The analytical stability of laboratory tests relies mostly on internal and external quality control procedures. Summarized patient data has in several studies been shown to be a good supplement for monitoring analytical stability. In our present investigation, we evaluate a datamining method for retrospective evaluation and assessment of analyte stability in whole blood. Results from the laboratory information system were used as the basis for the datamining approach. Blood tests were requested by the general practitioners and drawing of the blood sample was either at the general practitioner's or at the hospital outpatient clinics. We were able to split data into groups based on sample collection place and time to analysis. The datamining approach was compared to experiments where samples were incubated at a single temperature as well as an experiment where the temperatures were changed during incubation. To demonstrate the method, we selected three laboratory tests considered representative: potassium, phosphate, and lactate dehydrogenase. The datamining approach showed results similar to the reference experiment. Furthermore, our results show that the analytes phosphate and potassium were not stable after short storage at a lower temperature.