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Explore practical questions from the laboratory, with worked examples and sources to help you apply what you read.
Featured guide · EQA
One EQA result, two targets
See why the same result can agree with one target and differ from another.
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40 guides across 8 topics
Measurement uncertainty
5 guides
What does measurement uncertainty mean for a laboratory result?
Start with the quantity measured, the intended use and the scope of the estimate.
Which routine laboratory data can I use to estimate measurement uncertainty?
Check what your control data represent and what else contributes to the estimate.
When should I use a top-down or bottom-up approach to measurement uncertainty?
Compare evaluation approaches and the evidence each needs.
How do uncertainties in the inputs affect uncertainty in the final result?
Follow the link between model inputs and uncertainty in the result.
What should I include in a measurement uncertainty record?
Explain the estimate, the evidence it uses and when to review it.
Verification and method comparison
5 guides
Does high correlation mean two laboratory methods agree?
Use differences across the measuring range to assess agreement.
What can a laboratory method verification study tell me?
Separate verification from validation and define the scope of the study.
How do I assess agreement when results are categories?
Choose an evaluation that fits a category or classification.
Why does the concentration range matter in a method comparison?
See how a study can span a wide range and still miss the concentration where a decision is made.
What can a dilution check tell me about the reportable range?
Follow one specimen through two dilutions and see what recovery says about extending the measuring interval.
External quality assessment
5 guides
What is my EQA result being compared with?
Read the target, peer group and assessment rule behind the score.
What does an EQA z-score actually tell me?
See how the same difference can receive a different score when the assessment scale changes.
Why can an EQA sample behave differently from a patient sample?
Compare paired patient and EQA results to see why specimen behaviour matters.
What can I learn from a small EQA peer group?
See how one result can move a peer mean and what to check about the comparison group.
What can a pattern across several EQA rounds tell me?
Compare an isolated high score with a recurring difference in the same direction.
Internal quality control
5 guides
Why has my IQC chart signalled when every result is within limits?
See how a shift can emerge across several runs and what to check when it does.
Why run controls at more than one concentration?
See how a problem can show up at one control concentration while another stays near target.
What does a QC shift after a reagent lot change tell me?
Follow a shift on the QC chart and see how paired patient results can help assess its significance.
What does a repeat QC result within limits tell me?
Use the first result and the repeat together to decide what the repeat adds to the review.
When should I review my IQC mean and control limits?
See how a control-material lot change can affect the mean and what happens when you pool the results.
Analytical performance specifications
5 guides
What makes an analytical performance specification fit for purpose?
Connect an analytical performance specification to the decision the result supports.
How can clinical outcomes inform an analytical performance specification?
See how imprecision can change a decision classification and what evidence would connect that change to clinical outcomes.
How is biological variation used to set analytical performance specifications?
Use a worked example to derive an imprecision target from within-person variation and compare it with an observed CV.
When is current achievable performance a sensible basis for a specification?
Use comparable laboratory data to evaluate a candidate performance benchmark.
Why are allowable bias and imprecision separate requirements?
Compare two fictional methods to see why bias and imprecision need separate requirements.
Calibration and traceability
5 guides
What does a calibrator certificate tell me about traceability and uncertainty?
Follow the calibration chain and see where bias and uncertainty enter the assessment.
How is a laboratory result linked to a higher-order reference?
Follow a laboratory result through the calibrators and procedures that link it to its reference.
Why can two methods traceable to the same reference give different results?
Compare results from two methods with the same stated reference and see where they differ in practice.
What makes a reference material suitable for transferring a calibration?
Compare two materials with the same assigned value and see how each affects patient results.
What is the difference between a calibrator and a control?
See why calibration can complete successfully while a separate control is outside its limits.
Statistics and interpreting results
5 guides
When should I use SD, CV, standard error or a confidence interval?
Choose a statistic for the question you need to answer.
What can a histogram tell me about my laboratory data?
See what a histogram reveals about turnaround times from two laboratory workflows.
How can one unusual result change a summary of laboratory data?
See how one unusual observation changes the mean, median and standard deviation.
When should I use a paired analysis for laboratory results?
Compare results from the same specimens to see what a paired analysis tells you.
What does a p-value tell me about a laboratory comparison?
See why two studies with the same estimated difference can have different p-values.
Laboratory risk and service review
5 guides
How could a laboratory error lead to patient harm?
Connect a possible failure to harm, safeguards and evidence that they work.
How can I tell whether a laboratory safeguard is working?
Follow a barcode alert to see what evidence shows whether a safeguard did its job.
What can a near miss tell me about laboratory risk?
Trace a wrong-record entry caught before release and see what the near miss reveals.
Why can a laboratory meet its turnaround-time target and still leave patients waiting?
Compare the laboratory’s turnaround clock with the time from collection to first clinical review.
Which laboratory risks should I review first?
Compare routine rework with a failed urgent handover to see why one risk needs an earlier review.
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