We all accept errors do occur in our laboratories. But we may not be aware that an approach to error-classification and correction has been widely accepted. Error in the laboratory is defined as deviation or variance from the truth or from an accepted, expected, true or reference value.
Sources of Variance
SOURCES of Variance that are recognised include:
- Differences between individual patients (inter-individual)
- Variation within an individual patient (intra-individual)
Inter-individual variance is associated with sex, age, race, and lifestyle. Usually each laboratory takes this type of variance into account during the establishment of the normal reference intervals.
Intra-individual variance is due to differences in the preparation of the patient, prior to collection of the specimen for analysis.
Pre-analytical variance reflects what happens to the specimen between collection and analysis such as transport storage, centrifugation, time, etc.
Analytical variance in the laboratory belongs to one of two types:
- Systematic Error… error that occurs repeatedly over time and is often due to a problem with the instrument or reagents
- Random Error… error that occurs without any pattern and is usually not due to an inherent property of the instrument or reagents but to human error.
Systematic Error occurs when all measurements or observations, using a given method, deviate to the same degree from the true value. Therefore, it occurs regularly and with constant magnitude. You can measure it when recognised, and it can be eliminated.
This type of error is:
- Also known as bias of the method
- Known as positive bias when the observed value is greater then the true one
- Known as negative bias when the observed value is less than the true one
- Not unusual
- Recognised through quality control
Investigated by trouble-shooting
*More discussion on ‘troubleshooting when errors or other problems occur’ is presented in MODULE #4 Quantitative Quality Control