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Six Sigma

Quality on the Sigma Scale at Aga Khan Laboratory

A recent study from the Scandinavian Journal of Clinical and Laboratory Investigation details the quality indicator performance of the Aga Khan University Hospital in Karachi, Pakistan. Quality Indicators were measured across the total testing process: pre-analytical, analytical, and post-analytical. Can you guess where the biggest problems occurred? The results might not be what you expect...

Six Sigma across the Total Testing Spectrum

A recent paper accomplished a trifecta of sorts: measuring quality indicators not only in the PRE-analytical and POST-analytical phases of testing, but also in the analytical phase of testing. We convert the analytical Sigma-metrics to match the short-term Sigma results to compare the error rates of all the different processes in the testing spectrum.

Six-Sigma - Medical Cutoffs as Tolerance Limits

See how quality-planning can deliver World Class Quality for a POC device. This QC application makes use of medical cutoffs as tolerance limits for a cardiac marker POC device. Using Six Sigma techniques, Dr. Westgard shows how QC can be easy for difficult methods. (Preview)

Six Sigma - Quality Design and Control Applications

Forget the theory and the hype about Six Sigma: What can do "in action"? It can help you to objectively assess the state of your current QC, determine the desirable CV and bias for your tests, specify the necessary QC procedures and/or needed improvements, compare all kinds of quality requirements to each other, and more. Combined with our Quality-Planning tools, Six Sigma can offer a "one-two" punch to any QC situation. (Preview)

Six Sigma - Patient Data for Assessing Process Performance and Stability

Patient Data and Six Sigma together? Yes, the two most advanced QC techniques can work together. In fact, the two make a powerful combination. This application illustrates the use of both Sigma-metrics and Patient Data QC (also known as Average of Normals, AoN, Average of Patients). Patient Data QC uses patient test results to assess the performance of a laboratory testing process and to identify changes in process stability. This application strategy fits together with the strategy of multistage quality control, which employs multiple QC designs to accomplish specific objectives. (Preview)