Tools, Technologies and Training for Healthcare Laboratories

Journal Watch: The Quality of Estradiol Assays

Posted by Sten Westgard, MS

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Managing quality vs. measuring uncertainty

Posted by Sten Westgard, MS

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What about Bias? (in enzyme assays)

Posted by Sten Westgard, MS

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Labs: Lean to the bone?

Posted by Sten Westgard, MS

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Lab 2010: Are we aiming for the same goals?

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?

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Quality Requirements: Aiming at the Right Target?

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?

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Accuracy-Based Surveys: An idea whose time should already have come

(Or, if only some surveys are based on accuracy, then what are the other surveys based on?)

Posted by Sten Westgard, MS

There's an article that appeared in the October 2010 issue of  CAP Today that probably didn't get enough attention. It covers a subject that's been gnawing at us for a while:

Accuracy-based Surveys carve higher QA Profile, by Anne Paxton

For those of you who thought all proficiency testing was "accuracy-based", this article may give you a bit of a shock. In fact, most PT surveys - indeed most EQA programs and even peer-group programs - are not based in accuracy. Instead, those surveys are only based on "consensus."

What's the difference,  What does it mean - and how did it come to be this way?

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What's the Q of D? 2012 update

Posted by Sten Westgard, MS

In the recent issue of Clinical Chemistry, an editorial reviews the current state of Vitamin D testing: "There is common agreement that 25-OHD is a 'difficult' analyte."

25-Hydroxyvitamin D: A Difficult Analyte, Graham D. Carter, Clin Chem 58:3; 486-488 (2012).

At the same time, the editorial notes that marked process is being made:

"Nevertheless, results submitted to the international Vitamin D External Quality Assessment (DEQAS) have shown a gradual reduction in interlaboratory imprecision (CV) in recent years - from >30% in 1995 to 15% in 2011."

The question is, is that reduction in imprecision good enough? Or is the quality required by Vitamin D still too "difficult"?

More after the jump...

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More Error Rates at POC

Posted by Sten Westgard, MS

In the December 2011 issue of Point of Care journal, an interesting study was published:

Preanalytical Errors in Point-of-Care Testing: Auditing Error of Patient Identification in the Use of Blood Gas Analyzers, Natalie A Smith, David G Housley, Danielle B. Freedman, Point of Care, Volume 10: Number 4, December 2011.

The study looked at patient identification errors on a blood gas analyzer in various departments in a hospital. Bearing in mind that this is just one type of pre-analytical error, what do you think the rate was? Given around 100,000 tests, what would you guess as the number of defects?

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Think QC Again - in Japanese!

Posted by Sten Westgard, MS

Recently, the journal In Vitro Diagnostics Global News a publication of CGI KK and in association with CAP Today, has begun publishing a series of translations of Westgard articles into Japanese:

ThinkQCAgain
The title of the series is Think QC Again, an important message regardless of language or country.

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Failures Fuel the US Healthcare System

Posted by Sten Westgard, MS

A lot of interesting studies coming out this month, unfortunately none of them with encouraging news about the US healthcare system.

The latest, from Sunil Eappen, MD, Atul Gawande, MD et al, Relationship Between Occurence of Surgical Complications and Hospital Finances, JAMA, April 17, 2013, Vol. 309, No. 15 1599-1606

Take a guess: do US hospitals make more money when things go wrong, or less?

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Pop Quiz: How many people are US hospitals killing?

Posted by Sten Westgard, MS

It's almost mandatory that any presentation or report discussing patient safety references the landmark IOM report of 2000: To Err is Human - Building a Safer Health System. The takeaway quote from this report is that US hospitals were causing 44,000 to 98,000 deaths that were otherwise preventable. That is, hospitals were causing tens of thousands of avoidable deaths.

A recent paper has attempted to revise that estimate, focusing on Preventable Adverse Events (PAEs) that contributed to the death of patients. Can you guess how lethal US hospitals are now?

  1. 4,000 to 10,000 PAEs per year
  2. 44,000 to 98,0000 PAEs per year
  3. 100,000 to 200,000 PAEs per year
  4. 210,000 to 440,000 PAEs per year

The answer, after the jump...

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Total Analytic Error discussed in Clin Lab News

Posted by Sten Westgard, MS

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Could your laboratory catch this error? A Coda

Posted by Sten Westgard, MS

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Pop Quiz: If labs want to reach quality, do they need MAPS?

Posted by Sten Westgard, MS

In a recent issue of CCLM, an interesting opinion paper reported on a pilot study of the quality of UK laboratories.

Given 5,812 QC data points on 5 different platforms in 9 different laboratories measured over 6 months, and a quality goal of 7.0%  how many of those laboratories do you think achieved 5-Sigma quality?

  • 100%
  • 75%
  • 50%
  • 25%
  • less than 25%

The answer, after the jump...

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Pop Quiz: How good (bad) are US hospitals at inflicting adverse harm?

Posted by Sten Westgard, MS

We've all heard the infamous quote now over a decade and a half old: that US hospitals kill between roughly 40,000 and 90,000 patients each year. This was an estimate courtesy of the Institute of Medicine report "To Err Is Human" which made the dire performance of hospitals knowledge that even the general public could understand.

But more recently, studies have been tracking the adverse event rates much more closely. A recent NEJM paper followed four conditions from 2005 to 2011.

Of these four conditions, which do you think has the best Sigma performance when it comes to the occurrence of adverse events?

A. Acute Myocardial Infarction (AMI)

B. Congestive Heart Failure

C. Pneumonia

D. (other) Conditions Requiring Surgery

The answer, after the jump...

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In case you missed it: Above Average QC

Posted by Sten Westgard, MS

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Quality Indicators can be dangerous to your health

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Pop Quiz: What does healthcare think of Risk Analysis?

Posted by Sten Westgard, MS

So we all know that Risk Analysis is coming to laboratories in the US. (click here if this is news to you). But Risk Analysis, particularly the FMEA technique (Failure Mode and Effects Analysis), is not new to healthcare. Outside the laboratory, plenty of healthcare practitioners have been performing FMEA.

So what do they think about this technique? Try and guess which one of these responses is from a someone in healthcare:

  • "The jury's still out on the FMEA process because... has anybody evaluated FMEA as a tool for analysing risk? And it turns out there isn't... well why are we doing this process?... When all it is doing is bringing a few things to the surface, which is no bad thing, but it's not a validated process."
  • "...Forget FMEA. It doesn't really work effectively, I don't think, and the scores are a hindrance rather than anything else, year... We wasted a lot of time on FMEA before we realized, this isn't actually working. Yeah, because I think you can get caught up on just the score, that's the thing."
  • "The scoring in the FMEA teams need to be the same people, if you change half way through because of the highly subjective interpretation things change dramatically."
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What Traceability and Sigma-metrics share in common: A Need for Good Data

Posted by Sten Westgard, MS

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