Abstract

Quality control (QC) validation is used to determine: 1) whether statistical QC procedures are appropriate for detecting medically important errors; and 2) the equality of performance required by different laboratory tests. QC validation is well documented in the medical literature, but we are unaware of studies addressing its application, problems or unique differences in veterinary laboratories. We applied QC validation to automated hematology and biochemistry analyses in our laboratories, with goals of >/= 90% probability of error detection and </= 5% probability of false rejection. Analytical quality requirements in the form of total allowable error were defined using regulatory criteria for human proficiency testing; these were later modified based on clinician and pathologist feedback. Initial QC goals were not met for 14 of 49 (28.6%) analyte-control combinations. Subsequent modifications in methodology, analytical quality requirements and technician training achieved QC goals for all but one analyte. For this analyte (platelet count, low control), nonstatistical QC procedures were emphasized. QC validation was beneficial for clarifying statistical QC performance, and for assessing the need and justification for changes in methods and personnel training. The validation exercise allowed simplification of QC rules, enabled machine flagging of abnormal results, and decreased time and expense associated with QC recording, analysis, problem-solving and reruns. QC validation is recommended for all veterinary laboratories as a useful tool in total quality management.

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