Andy (and the Mailbase),
Regarding the Empower program previously mentioned - I suspect you have accessed the wrong "Flyer" on their website.
http://www.stt-consulting.com/news.php?rubriek=8
I apologise for being insufficiently specific.
The "Master Comparison Flyer" refers to a project where 20 single donor samples are made available to labs for between lab comparisons for 8 analytes, including reference method value assignment for enzymes.
I had meant to refer to the "Percentile Monitoring Flyer" where labs send in daily means of their outpatient measurements for 20 analytes. In our lab this can be up to 200 measurements per analyte, and some labs will have very many more.
I have had some attempts to define mathematically control limits without great success and these would depend on CVa, CVg, n, and an effect of the "Unwellness" of the group (a sicker population may have a wider CVg). Some relationships have shown between the average age on each day (older on Mondays and younger on Saturdays); the sex mix on each day and the average value.
By definition this is QA (assessment of quality) rather than QC (the data comes too late, eg end of day at earliest for Control of quality). There is further development needed but the comparison of different populations and analysers allows a different way of looking at quality.
As an aside I have further expanded this internally to collect data on over 60 analytes at weekly, monthly or 6 monthly intervals (depending on our workloads) as a QA exercise. Where possible I am using the population reference intervals as a guide to see whether the midpoint of the distribution is near the middle of the reference interval (where this might be expected) and assess any bias against this interval. I suspect that many laboratories are making similar calculations.
Also glad to see you are making the most of your lunchbreak with a few interesting calculations!
Best wishes,
Graham
________________________________________
From: Clinical biochemistry discussion list <[log in to unmask]> on behalf of Andy Minett <[log in to unmask]>
Sent: Monday, 11 August 2014 10:26 PM
To: [log in to unmask]
Subject: Re: Using Patient Means as a QC measure
>While grouping 20 patient samples may be sufficient in some circumstances (overkill, even, for some tests),
>I would be tempted to work the alogrithm backwards to see just how much systematic error is *actually* being
>detected by this scheme for tests with a high patient:analyser variance ratio. I expect though, that you'd need
>to see huge systematic errors in the magnitude of +/-15 to 20 SD before AoN flagged up error for ALP with
>groups of 20 patient results.
Just out of interest, I've spent my lunch hour working backwards to find out how much error is actually being detected in this ALP example.
For a probability of error detection of 50%, grouping 20 patient samples for AoN will allow the detection of +/-6.2 SD... so the 15-20SD I suggested earlier is a little exaggerated! (see attached screenshot).
Still, as an example, this would mean reporting true ALP results of 150 (IU/L) coming off the analyser as 174 before the patient mean QC suggested there might be a problem. Compare this with using groups of 200 patient samples which, at the same p rate, would flag 'out of control' with a genuine systematic error of as little as 6 IU/L.
Best regards,
Andy Minett
Specialist Biomedical Scientist
Biochemistry
Pathology
Hull Royal Infirmary
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