Posted by Sten Westgard, MS
Earlier, we posted an article on the website with a darkly humorous take on the passing of the CLSI EP22 guideline, which voted itself out of existence in late 2010. Other websites have also noted its passing.
But it's worthwhile to take a moment to discuss, in all seriousness, where we are with Risk Information, Risk Management, "Equivalent QC", and the CLIA Final Rules. How did we get here? What drove us to this state? Where are we going next?
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Here's a question from a website visitor regarding assigning a mean value for a new QC material with the following assumptions:
"1. The analyte reports out as a whole number.
2. The results of calculations on 20 replicate samples are;
A. Mean = 10.5
B. SD = 0.5
C. 2 SD Range = 9.5 - 11.5
D. 95% Confidence Interval = 10.3 - 10.7
E. CV% = 4.9
The question is "what to set the mean at?" One camp contends that the mean of 10.5 should be used, even though no result will ever "hit" the mean. The other camp states that the mean should be set to 10 or 11 regardless of whether or not a LJ shows bias, or even 10x failure. "
Answer after the fold.
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We see the Bail Outs of the bankers and wall street. We see the cutbacks and austerity of governments in Greece and Ireland as their governments struggle to make good on the debts run up by their out-of-control banks.Private risks made into Public losses.
But is the laboratory immune from the problem of "Too Big to Fail"?
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Posted by Sten Westgard, MS
The National Oil Spill Commission released a preliminary chapter of its report today. This is the commission charged with finding out what went wrong with the Deepwater Horizon / Macondo oil rig in the Gulf of Mexico that blew up in 2010 and spilled 4 million barrels of oil and killed 11 workers.
Whenever there are big stories in the media, we like to take a look at them to see if we can learn anything, find any connection between the disaster and our own situation in the medical laboratory community. But from a distance, it's hard to see any similarities between oil rigs and labs, right?
Right?
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Posted by Sten Westgard, MS
Posted by Sten Westgard, MS
This question comes to us from a CLS student in Texas:
"I was hoping that someone might be able to answer a question that is causing me and some of my
classmates some confusion. There is some confusion when you are plotting your QC chart and all your values are a whole number. Would you keep you SD as a whole number or make it to one decimal place? And if you did make it to one decimal place, would you be making your SD more accurate that your original value?"
Answer after the jump...
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Posted by Sten Westgard, MS
We want your control chart data!
We've always had an "open door" policy on the website, welcoming your questions and your data. At times, we may not be so explicit in inviting you to contact us with your observations, comments, inquiries, and frustrations, but we do want to hear from you.
Now, we're asking for a more specific set of data from you - for your problem methods, show us a few months of QC data, ideally with notations such as new control lot, new reagent, recalibration, etc.
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Posted by Sten Westgard, MS
Earlier this month I had the pleasure of speaking at the Abbott Diagonstics Turning Science into Caring symposium in Belgium [full disclosure: I was compensated to speak at this event].
I was fortunate to partner with Dr. Jeremie Gras, who shared the same topic. He lectured first on Six Sigma concepts and experiences in Belgium, and I followed him with some additional data, observations, implications, and recommended best practices. It was a "one-two punch" for Sigma-metrics.
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Posted by Sten Westgard, MS
From Dr. Carmen Ricos, on behalf o the SEQC-Analytical Quality Commission:
Sten Westgard, MS
Is it time for a tighter quality requirement for glucose meters?
Fresh on the heels of Dr. George Klee's review of setting performance specifications, as well as the recent FDA public meeting on glucose meter quality, Dr. Klee and Dr. Brad Karon of the Mayo Clinic and Dr. James C. Boyd of the University of Virginia recently published a study that used simulation modeling to determine performance criteria for glucose meters:
"Glucose Meter Performance Criteria for Tight Glycemic Control Estimated by Simulation Modeling", Brad S Karon, James C. Boy, and George G. Klee, Clinical Chemistry 56:7; 1091-1097 (2010)
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Posted by Sten Westgard, MS
Attending the AACC/ASCLS convention predictably results in one frustration. Walking through the poster sections, you find that many of the method validation abstracts are only performing within-run precision studies.
What's so bad about that?
Repeat after me: it's not about the repeatability...
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Posted by Sten Westgard, MS