A clinical laboratory's Levey-Jennings chart shows QC sample results drifting steadily toward the upper control limit over five consecutive runs, though the values are still within the control limits. What is the correct response?
AReport all patient results normally; QC values are still within the control limits
BInvestigate and correct the source of drift before releasing any patient results from the affected runs
CRerun only the QC sample after recalibration to confirm correction, then release results
DAverage the drifting QC results and apply a mathematical correction factor to patient values
A consistent trend (even within control limits) violates Westgard trend rules and signals systematic drift — the method may already be affecting patient results. The point of QC is to catch problems before they reach patients, not to confirm errors after the fact. Option 0 is the dangerous misconception: staying within limits is not sufficient if a trend indicates the method is no longer stable. Option 2 addresses only the QC without finding the root cause.
Question 2 Multiple Choice
A clinical method for serum potassium has excellent accuracy on QC samples but high imprecision (large CV). What is the primary patient safety concern?
ACalibration may be off, causing all results to be shifted systematically high or low
BRandom scatter could push a truly normal patient's result outside the reference range, triggering unnecessary treatment or masking a true abnormality
CThe method will fail to detect any abnormal potassium values at all
DHigh CV is only a concern in research labs; clinical diagnostics tolerates wider variation
Reference ranges define the normal window for healthy patients. If a method has wide random scatter, a patient with a true potassium of 4.0 mmol/L might be measured as 3.4 or 4.6 — one potentially triggering a cardiac intervention, the other missing a real abnormality. Good accuracy (option 0) is separately important but addresses systematic error, not random scatter. Precision determines whether the method reliably places each patient's result in the correct zone relative to the reference range.
Question 3 True / False
The same spectrophotometric technique can be used in both an industrial QC lab and a clinical diagnostic lab, but clinical labs layer additional QC requirements on top of the standard method.
TTrue
FFalse
Answer: True
The underlying analytical chemistry — Beer's law, calibration curves, detection limits — is identical. What distinguishes clinical analytical chemistry is not different chemistry but different consequence: a 10% error in an industrial batch triggers a retest, while the same error in a clinical lab can cause misdiagnosis or harmful treatment. Clinical labs respond with mandatory QC samples every batch, Levey-Jennings charting, Westgard rules, and reference ranges — layers of safeguards not required in most industrial contexts.
Question 4 True / False
A patient result that falls outside the laboratory's reference range definitively indicates disease and requires immediate clinical intervention.
TTrue
FFalse
Answer: False
Reference ranges are typically defined as the central 95% of values in a healthy reference population — meaning 5% of healthy individuals will have results outside the range by statistical definition. An out-of-range result is a flag for clinical consideration, not a diagnosis. Physicians must interpret the result in the context of the patient's symptoms, history, and other findings. Additionally, reference ranges vary by age, sex, and laboratory method, so a result flagged as abnormal at one lab might be normal at another.
Question 5 Short Answer
Why do clinical labs run quality control samples with every patient batch rather than only when a problem is suspected?
Think about your answer, then reveal below.
Model answer: Because analytical errors are invisible without a known reference point. Patient samples have unknown true values, so drift or shifts in method performance cannot be detected from patient results alone. QC samples with known concentrations reveal whether the method is performing correctly before results reach clinicians. Running QC every batch also creates a documented performance record, allows early detection of gradual drift (before it crosses a critical threshold), and satisfies regulatory requirements that patient safety depends on continuous, not reactive, verification.
The key insight is that you cannot know a method has drifted by looking at patient results — there is no truth to compare against. QC provides that external truth. This is why QC is not optional or reserved for suspected problems: by the time a problem is suspected, patients may already have received results from a compromised method. Proactive QC is the only way to catch failures before they have consequences.