Data Evaluation, Result Reporting, and Reference Intervals
Core concepts
Data evaluation covers descriptive statistics, outlier assessment, and the delta check. Candidates must know reference interval concepts: central 95% interval, parametric vs nonparametric derivation, and the effect of partitioning by age and sex. Understand sensitivity, specificity, predictive values, and how prevalence affects predictive value.
Reporting
Know critical value reporting, turnaround time, amended reports, and the requirement to document notification. Understand that reference intervals must be verified locally and that results should be reported with units and method context.
Traps in questions
- Assuming a result outside the reference interval is always abnormal.
- Confusing sensitivity with predictive value.
- Forgetting that predictive value depends on prevalence.
- Reporting critical values without documented notification.
Worked rule of thumb
A reference interval contains the central 95% of a healthy population, so 5% of healthy people fall outside it by definition. Interpret a result in clinical context, not by the interval alone. When a delta check flags a large change, verify specimen identity before reporting.
Study guidance
Practice interpreting 2x2 tables and computing predictive values. Most items test whether you can distinguish the statistic being asked from the one you assume.