A guest post by Nils Person, PhD, FACB

I recently read the essay "The QC We Really Do" with great interest and found the information very useful.  However, there was one topic that I was concerned about. It had to do with re-calibration in response to QC rule failure. The essay indicated that re-calibration is a common response to QC rule failure.... and I am not sure that is a good strategy. .

Posted by Sten Westgard, MS

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"?

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?

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.

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)

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...

Posted by Sten Westgard, MS

Posted by Sten Westgard, MS

In the iconic western film, The Magnificent Seven, there is a famous scene about marksmanship. [Quick set up: The Magnificent Seven are - you guessed it, seven - gunmen hired to protect a peasant village from a much larger group of bandits] Early in the film, the heroic gunmen detect three bandit scouts and want to capture them. In an abrupt exchange of gunfire, two bandits are killed, but the third bandit mounts his horse and attempts to escape. As the bandit flees, one of the gunmen, Britt, steadies his pistol and takes aim. The escaping bandit gallops farther and farther away. But just as he is about to disappear behind a hill, Britt shoots, hitting the bandit square in the back, killing him. The youngest of the gunmen, Chico, shouts:

    Chico: (in awe) That was the greatest shot I've ever seen!

    Britt: (sternly) The worst! I was aiming at the horse.

This scene reminds us that even when what one person thinks is great performance may not be acceptable by another person's standards. Indeed, what appears like an accomplishment may actually be an error.

And what, you may ask, does this have to do with Six Sigma?

Sten Westgard, MS

[Posted by Sten Westgard, MS, from the AACC Press Release]

Posted by Sten Westgard, MS

As we write, the National Basketball Playoffs are underway. The home team for Westgard QC, the Milwaukee Bucks, just went down to defeat in the final game of a 7-game series.

Those who follow basketball know that in a series like this, the teams basically alternate home court advantage. The Bucks went to Atlanta to play the Hawks for two game,s then the Hawks came to Milwaukee to play the Bucks for two games, etc. But while there is a home court advantage in the audience (which didn't work: both teams won away games), the courts in every stadium are the same. The basketball hoop in Atlanta is the same as the basketball hoop in Milwaukee. Why is that?

Because the rules specify a consistent goal. The NBA has a rule book which states the precise size of the court, equipment and basket size. A basket, for example, "shall consist of a pressure-release NBA approved metal safety ring 18" in inside diameter with a white cord net 15" to 18" in length." Every stadium must comply with this rule. 

Likewise, there is a single standard for the basketball: "The National Basketball Association (NBA) allows only one official ball: The ball must be the official NBA game ball manufactured by Spalding. The ball is orange in color, 29.5 inches in circumference and weighs 22 ounces (size 7). It must also be inflated to between 7.5 and 8.5 pounds per square inch."

Sorry for the long prologue. But wouldn't it be nice if labs were the same?

Posted by Sten Westgard, MS

Alan Greenspan gave some instantly notorious testimony to the US Congress recently:

“I was right 70 percent of the time, but I was wrong 30 percent of the time,” 

I'm not sure what was more concerning; the fact that he admitted that almost a third of the time he was wrong, or that he clearly believes that being right only 70% of the time was acceptable. Clearly, for a man once called "The Oracle" and Maestro, he was lowering the bar on the standards for judging him.

Testimony like that raises some instant questions:

• If Alan Greenspan was responsible for setting the direction of the world's greatest economy, is a 30% error rate acceptable?
• If Alan Greenspan was an airline, would you fly him?
• If Alan Greenspan was a core laboratory test, would you buy the instrument?
• If Alan Greenspan was a glucose meter, would you buy the device?

Posted by Sten Westgard, MS

“There is increasing recognition of a need to improve the precision of HbA1c assays, in view of the low biological variability of Hb A1c. The NGSP plans to reduce the
acceptability specification for level 1 laboratories to 0.70% and for manufacturers of all Hb A1c methods to <0.75% in 2010 (http://www.ngsp.org/ ngsp/prog/News/manuf09.html; accessed October 28, 2009). The College of American Pathologists (CAP) also has recognized the need to tighten total error criteria for Hb A1c and is in the process of
revising the criteria used in grading proficiency tests (http://www.
ngsp.org/ngsp/prog/News/manuf09.html; accessed October 28, 2009). In 2007,
the limit specified by the CAP for acceptability on HbA1c proficiency testing was +/- 15% of the target value. This limit was lowered to +/-12% in 2008 and to +/-10% in 2009, and it will be lowered to +/-8% in 2010 and to +/-6% in 2011. “

As these quality requirements tighten, how are we going to respond?

Posted by Sten Westgard, MS

Posted by Sten Westgard, MS

Posted by Sten Westgard, MS

In June of this year, Zoe Brooks presented an AACC-sponsored webinar with the title, Laboratory QC: Bridging the Gap Between Theory and Practice. During this webinar, Zoe presented a poll and more than 100 participants responded. The results are very interesting...