Primary care
potassium results show large seasonal variation due to problems with specimen
stabilisation. This may mask other underlying reasons for variation. If we plot
the distribution of potassium results from ED and primary care side by side we
can see what appears to be a systematic difference between the two populations
(Figure 6)
In North
Devon, two practices (Black Torrington and Lynton) have centrifuged all
specimens on site since 2014. This has resulted in much more stable potassium
results. We can see the same shift in mean potassium result in these practices
that occurred when the analyser was changed in 2018. However, we also see a
large systematic shift in the result between the primary care and ED
populations (Figure
7).
Figure 7 Mean
monthly potassium in ED compared with 2 practices that stabilise all specimens
at point of care by centrifugation. Note that in this analysis we only looked
at “first time tests” by removing any test that was repeated on a specific
patient within 3 months
Impact of demographic differences on potassium
result
One
explanation for this result is that the people tested in ED are very different
to those tested in primary care. The following population pyramid shows the
differences in the demographic groups that are tested in ED compared with Lynton
and Black Torrington (Figure 8).
Figure 8 Population
pyramids showing demographic differences in people having a potassium test in
the ED compared with Black Torrington / Lynton GP practices.
To examine whether
these demographic differences could account for the systematic difference in
potassium results, we looked at the results of first time testing (i.e.
ignoring repeats within 3 months) in specific demographic groups. For
simplicity, we looked at just the potassium results before the analyser change,
as this gave us the largest dataset. We can see that the difference in mean
potassium exists across all demographic groups (Table 4).
Impact of disease severity on
potassium result
Patients in
the ED who have a test are more likely to be acutely unwell than patients in
general practice. In an attempt to determine whether the difference in
potassium might be accounted for by differences in clinical reason for the
test, we repeated our analysis looking at different groups that we could
identify either through the clinical details on the request form, or from their
testing history. The comparator group might be expected to contain patients who
were more likely to be acutely unwell (Table 5). We can see no significant difference between the
patient groups and their comparators, and conclude that disease severity is
unlikely to be a reason for the systematic difference in potassium between the
ED and primary care.
Table 5 Difference in mean potassium between
patients in different clinical groups, as identified from clinical details on
request form.
Location of patient group
|
Patient group
|
Comparator
|
No of patients in group
|
Number of patients in comparator
|
Mean
K in group
|
Mean
K in comparator
|
Difference
|
GP
|
Blood
requested for chronic disease monitoring (asterisk in clinical details)
|
Not
requested for chronic disease monitoring
|
667
|
3978
|
4.68
|
4.59
|
-0.09
|
GP
|
Patient
has no repeat test within next week
|
Patient
has repeat test in hospital within next week
|
162161
|
1381
|
4.46
|
4.51
|
0.05
|
ED
|
Patient
has no repeat test within next week
|
Patient
has repeat test within hospital within the next week
|
13996
|
1017
|
4.21
|
4.24
|
0.03
|
ED
|
Patient
has no repeat test within next week
|
Patient
has repeat test on ICU within the next week
|
13996
|
241
|
4.21
|
4.22
|
0.01
|
What does this mean for patients?
We cannot
account for this systematic difference in potassium results between the ED and
primary care. It does not appear to be due to demographic or disease
differences. It would seem to be unlikely to be due to specimen stability as we
see the effect in locations where specimens are stabilised at the point of draw
and where results appear stable across the year. Both ED and primary care use
the same equipment manufacturers and specimens are run on the same analysers.
Nonetheless,
we can estimate the impact of this difference on the rate of abnormal results. The
following table shows the proportions of patients who fall into different
potassium result groups (Table 6).
Table 6 Proportion of potassium tests in different
result categories comparing ED and the two practices that stabilise all
specimens by centrifugation
From this
analysis, we can work out the number of patients in primary care who would be
placed in different categories if all practices stabilised specimens and if
analyser performance was the same as that seen for ED specimens (Table 7).
Table 7 Predicted annual number of patients who fall
into different result categories using actual primary care mean compared with theoretical
mean derived from ED results (based on 124,000 tests per year in primary care).
Conclusions
We will talk
in a subsequent blog about the impact of specimen stability on potassium
results. This blog looks only at the clinical impact of a systematic shift in
result depending on the location of where the blood has been taken.. We can
estimate that about 1 in 12 potassium results taken in primary care would be in
a different result category if the test was done in a different location. We do
not understand the reasons for this but clearly it is important to study this
further, and to understand whether this is a phenomenon seen in other regions.
With the aim to provide a reliable link to patients journey of well-being, ABHA pathology laboratory was incepted in 2001. Understanding the liability of a pathologist in the diagnosis for patients, we have always adopted a modern concept and made our laboratory a well defined, high-tech laboratory. We have five different departments for specific diagnosis.
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