10 Common Mistakes When Interpreting Blood Tests

The short answer

The most common mistakes when interpreting blood tests are ignoring how the sample was collected, reading one marker in isolation, treating a reference range as a line between healthy and unhealthy, and over-reading small changes between tests.

Most are errors of process, and a short checklist prevents them.

Ten mistakes and how to avoid each

Each mistake below has a simple fix.

Mistake	Why it matters	The fix
1. Ignoring collection conditions	Most errors in laboratory testing arise before the sample is analysed: 46 to 68% of total errors (Plebani, 2006).	Record fasting status, time, illness, exercise and supplements with every result.
2. Missing biotin	Taking 10 mg of biotin daily for a week interfered with 9 of 23 biotin-based assays in one study, including thyroid tests and ferritin (Li et al., 2017).	Ask about hair, skin and nail supplements before any test.
3. Reading one marker alone	Ferritin rises with inflammation and can hide low iron stores.	Read markers in groups, with CRP.
4. Treating the range as healthy versus unhealthy	A reference interval covers the central 95% of a reference population, so 5% of healthy people fall outside it.	Read position within range, the pattern and the person.
5. Over-reading small changes	Every marker varies from day to day, so small shifts are often noise (Fraser, 2011).	Look for change that is large, sustained and matched by related markers.
6. Mixing units	Ranges published in US units do not apply to Australian SI results.	Confirm units before comparing with any range.
7. Comparing across laboratories	Methods and intervals can differ between laboratories.	Use the same laboratory where possible.
8. Treating a functional flag as a diagnosis	Functional ranges prompt questions. They do not name conditions.	Phrase findings as patterns to investigate.
9. Forgetting medications and supplements	Many change results, including thyroid hormone, corticosteroids, iron and iodine.	Keep a current list and read results against it.
10. Delaying referral	An out-of-range result is a medical question first.	Set referral lines in advance and follow them.

Why a full panel almost always has a flag

The more markers you test, the more likely a healthy person has at least one result outside its range by chance alone.

If each reference interval covers 95% of healthy people, and 20 independent markers are tested, the chance that all 20 fall inside their ranges is 0.95 multiplied by itself 20 times, or about 36%. That leaves about a 64% chance of at least one flag in a healthy person.

Real markers are not fully independent, so the true figure differs. The point holds: one isolated, mildly abnormal result on a large panel is often chance. Retest before building a story around it.

Thinking errors

Some mistakes are in the reasoning, not the reading. Research on diagnostic error has catalogued the biases involved and identifies reflection on your own thinking as the main defence (Croskerry, 2003).

Three are especially relevant to pathology.

Anchoring. Fixing on the first abnormal result and reading everything else through it.
Premature closure. Stopping once one explanation fits, before checking for others.
Confirmation bias. Noticing the markers that support what you expected from the case history and passing over those that do not.

The defence is the same for all three: before you conclude, name one other explanation and look for evidence against your first one.

A pre-interpretation checklist

Run this before reading any result. It takes about a minute.

Do I know the fasting status, time of collection and laboratory?
Was the client well, rested and not recently training hard?
Do I have a current list of medications and supplements, including biotin?
Are the units the ones my ranges use?
Is anything outside the laboratory's interval? If so, it is referred before anything else.
Have I got the previous results to compare?
Am I reading markers in groups, not one at a time?
Have I named one alternative explanation for my main finding?

Where a platform helps. Several of these mistakes are mechanical, and software handles mechanical work well. Beyond Normal reads results in Australian SI units, shows the conventional and the functional interval side by side, groups markers into 21 clinical clusters, and takes fasting status, medications and supplements into account in its interpretation. It also charts each marker across visits, which makes real trends easier to tell from noise. To compare tools, see the best online platforms for practitioners to interpret blood tests.

Frequently asked questions

What is the most common mistake when reading blood tests?

Ignoring how and when the sample was collected. Most errors in laboratory testing occur before analysis, and fasting status, illness, exercise and supplements all change results.

Can a blood test be abnormal in a healthy person?

Yes. Reference intervals cover the central 95% of a reference population, so healthy people fall outside them. On a panel of 20 independent markers, at least one flag is more likely than not.

Can supplements affect blood test results?

Yes. Biotin can interfere with some immunoassays, including thyroid tests. Iron, iodine and other supplements change the markers they relate to. Record everything the client takes.

Why did my client's result change when nothing else changed?

Every marker has normal day-to-day biological variation, and every laboratory method has some imprecision. Small changes are often noise.

Is a result outside a functional range a problem?

Not necessarily. It is a prompt to read related markers, check collection conditions and compare with earlier tests.

Sources

Citations were checked against PubMed on 4 October 2026.

Plebani M. Errors in clinical laboratories or errors in laboratory medicine? Clin Chem Lab Med. 2006;44(6):750-759. doi:10.1515/CCLM.2006.123
Li D, Radulescu A, Shrestha RT, et al. Association of biotin ingestion with performance of hormone and nonhormone assays in healthy adults. JAMA. 2017;318(12):1150-1160. doi:10.1001/jama.2017.13705
Jones G, Barker A. Reference intervals. Clin Biochem Rev. 2008;29 Suppl 1:S93-S97. PMC2556592
Fraser CG. Reference change values. Clin Chem Lab Med. 2011;50(5):807-812. doi:10.1515/CCLM.2011.733
Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them. Acad Med. 2003;78(8):775-780. doi:10.1097/00001888-200308000-00003