Troubleshooting / Common Issues
More than 10% of results fall outside the reference interval (verification fails)
Possible causes
- –Population demographic mismatch — your patient population may differ from the original study population in age, sex, ethnicity, or health criteria
- –Preexamination differences — specimen type, collection technique, or handling conditions differ from the original study
- –Analytical differences — the test method's calibration or bias differs from the method used to establish the original interval
- –Incorrect reference individual selection — some enrolled individuals may not meet the 'healthy' criteria
Recommended action
First, review the Distribution of Data table to identify which results are outside the interval and whether they represent true population variability or data quality issues. Check for data entry errors and documented sample handling problems. If results appear valid, consider whether demographic partitioning is needed. If the interval consistently fails, consult your laboratory director regarding establishing a laboratory-specific reference interval per CLSI C28-A3c.
3–4 results fall outside (borderline result)
Possible causes
- –Small sample size increases the probability of borderline outcomes by chance
- –Mild population or preexamination differences that do not invalidate the interval
Recommended action
CLSI EP28 recommends enrolling an additional 20 reference individuals and repeating the study. If ≤ 2 of the new 20 fall outside, the interval is verified. If 3 or more of the new set are outside, the interval is not verified. Document the repeat study and its outcome in the verification record.
Histogram shows a bimodal or highly skewed distribution
Possible causes
- –The enrolled population contains two or more distinct subgroups (e.g., mixed sex, wide age range)
- –The analyte is known to have sex- or age-dependent reference intervals
- –One or more individuals with underlying conditions were inadvertently enrolled
Recommended action
Review the reference individual selection criteria and health documentation for all enrolled subjects. If the analyte's reference interval is normally partitioned by sex, age, or another variable, repeat the study with separate cohorts of ≥ 20 individuals per partition. Apply the 10% rule independently to each subgroup.
Result appears to be an outlier — one extreme value far outside the interval
Possible causes
- –Data entry error — incorrect raw value recorded
- –Sample handling issue — wrong sample, mislabeled aliquot, or compromised specimen
- –Reference individual was incorrectly classified as healthy
- –Instrument malfunction or interference during that measurement
Recommended action
Investigate the specific sample before excluding it. Results may only be excluded if a valid, documented non-performance reason exists (e.g., instrument error flag, documented sample handling problem, or proof that the individual did not meet the healthy criteria). Statistical aberrance alone is not sufficient justification for exclusion. Document the reason for any exclusion in the verification record.