APS TO VERIFICATION · FREE INTRODUCTION
Analytical performance specifications: what quality is needed?
An analytical performance specification (APS) describes the measurement quality needed for a particular use.
1 · Understand APS → 2 · Understand verification
Understand what an APS means, where it comes from and why it belongs before a verification decision.
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What does “good enough” mean?
A short introduction to measurement-quality requirements, precision, bias and the different meanings of an acceptable result. Clear explanations, familiar examples and occasional reflections.
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By Stephen MacDonald · Updated 2 October 2026
Start with the use of the result
A test may help make a decision near a threshold or monitor change over time. The analytical performance needed for those uses may differ. “The analyser performs well” is therefore incomplete: well enough for which purpose, and at which concentrations?
An APS connects that purpose to a requirement, such as a limit for imprecision or bias. It provides a basis for judging performance; the performance you happen to observe does not, by itself, define what is acceptable.
Five terms that answer different questions
| Term | The question it answers |
|---|---|
| Performance specification | What analytical quality is needed? |
| Manufacturer’s claim | What performance does the manufacturer state? |
| Local study result | What did our study observe? |
| IQC control limit | When should routine control results trigger a response? |
| EQA assessment limit | How does this scheme judge a submitted result? |
These quantities can inform one another, but they are not interchangeable. A total-error allowance is not automatically a limit for CV, bias or measurement uncertainty. Compare the same characteristic, units and conditions.
Where do specifications come from?
The EFLM Milan consensus describes three models. [1]
- Clinical outcomes: how analytical performance affects clinical decisions and patient outcomes.
- Biological variation: analytical variation considered in relation to variation within and between people.
- State of the art: performance that is technically achievable or achieved by a defined group of laboratories.
The appropriate model depends on the test’s use and the quality and relevance of the evidence. A published number is not automatically suitable for every population or concentration. Achievable performance is not necessarily sufficient for a clinical need.
One example: the right question, wrong concentration
Fictional example. A laboratory introduces an assay used near a low decision threshold. It has convincing precision results at a much higher concentration.
Those results describe the condition studied. They do not establish the quality needed, or the performance achieved, near the threshold. The laboratory first needs to identify the relevant requirement there, then obtain evidence that addresses it.
The lesson: “good precision” only becomes useful evidence when it is connected to the intended use. The verification guide continues this example.
How APS connects to verification
APS asks what is needed. Verification asks whether specified requirements are met. A manufacturer’s claim and a requirement for your intended use may not be the same.
Before judging a study, be clear which requirement it addresses and why that requirement is appropriate. Choose the criterion before seeing the results. If it is not met, investigate the evidence and the proposed use; do not select a more convenient limit simply to obtain a pass.
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Sources and boundaries
- [1] Sandberg et al. EFLM Milan consensus statement (2015). The three models and their application.
- [2] CLSI C24: Statistical Quality Control for Quantitative Measurement Procedures. Public scope of routine QC.
- [3] JCGM VIM: verification. The meaning of specified requirements.
This is a conceptual introduction, not an assay-specific specification or a study protocol. The example is original and fictional. Follow applicable guidance and local governance when applying the ideas.
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