Overview
Every result that leaves a laboratory becomes part of a medical decision, so laboratories must prove — every single day — that their results can be trusted. Laboratory Quality Management is the organised system of goals, resources, processes and checks that keeps analytical results accurate, precise and reproducible.
This lesson introduces quality control (QC), the difference between accuracy and precision, the quality management cycle, and the three broad categories of laboratory error — pre-analytical, analytical and post-analytical — along with the Levey-Jennings chart and Westgard rules used to detect them.
Learning Objectives
After this lesson you will be able to…- Define quality control, accuracy and precision
- Explain the goal and structure of laboratory quality management
- Differentiate clearly between precision and accuracy using worked examples
- Classify laboratory errors as pre-analytical, analytical or post-analytical
- Describe the Levey-Jennings chart and Westgard multirule procedure used for QC
Clinical Story
Why This MattersA morning-shift technologist notices the internal QC value for glucose has drifted just above the mean for four consecutive runs — each one within +1SD, but never below the mean. Applying the Westgard 4:1s rule, she flags a systematic error, holds patient reporting, and traces it to a newly opened reagent lot calibrated slightly high — catching the problem before a single incorrect patient report goes out.
Core Concepts
Quality control (QC) is a measure of precision — how often a measurement system produces the same result again and again, over time and under different operating conditions. Accuracy is different: it is how often the system produces the correct result compared with a known standard value.
Worked example: a QC material has a known creatinine value of 2 mg/dL. Instrument A repeatedly gives 4.1, 4.2, 4.1, 4.0, 4.1, 4.1 — tightly clustered but far from 2. Instrument A is precise but not accurate. Instrument B gives 4, 0.9, 2.1, 2, 1.9, 2 — mostly close to 2 but scattered. Instrument B is accurate but not precise. A reliable laboratory test needs both.
Quality management in a laboratory works as a continuous cycle:
- Set the goals and objectives the management wants for laboratory quality
- Provide initial requirements — instruments, calibration materials, trained staff, a competent lab manager
- Set the quality control processes
- Perform quality assessment at required intervals and identify error
- Take steps for quality improvement — eliminate the error and raise the standard
The cycle then repeats, continuously refining laboratory performance.
All errors associated with analysis and reporting of a patient's sample fall into three categories:
- Pre-analytical error — everything before the sample reaches the lab (wrong test ordered, illegible handwriting, wrong patient ID, wrong tube, delayed transport). This accounts for roughly 75% of all laboratory errors.
- Analytical error — faulty calibration, interfering substances, sample mix-up during actual testing.
- Post-analytical error — wrong patient identification at reporting, transcription errors, delayed reporting, previous values unavailable for comparison.
Laboratory personnel are directly responsible for analytical error, but must never ignore pre-analytical error — a rejected bad sample protects the patient far more than a perfectly analyzed wrong sample.
Laboratory Principle
Quality control material is compared against known target values using statistics or control charts. The most widely used tool is the Levey-Jennings chart (named after Levey and Jennings, 1950; later improved by Henry and Segalove). Days are plotted on the X-axis and observed QC values on the Y-axis, with the mean and ±1SD, ±2SD, ±3SD lines drawn parallel to it. Any value that falls outside the accepted mean ±2SD range signals that laboratory testing must stop until the error is found and corrected. The Westgard multirule procedure (e.g. 1:3s, 2:2s, 4:1s) is then applied to the pattern of QC points to distinguish random error (a one-off chance event) from systematic error (an error that affects every subsequent test equally, such as a faulty pipette).
Equipment Required
Reagents & Materials
| Reagent / Material | Concentration / Grade | Purpose | Storage |
|---|---|---|---|
| Internal QC Material — Level 1 (Normal) | Analyte at low-normal physiological range | Detects error at normal analyte levels | 2–8°C (or −20°C per manufacturer) until reconstitution |
| Internal QC Material — Level 2 (Abnormal) | Analyte at pathological/high range | Detects error at clinically abnormal levels | 2–8°C (or −20°C per manufacturer) until reconstitution |
| External QC / Proficiency Testing Sample | Blinded, assigned target concentration | Inter-laboratory comparison (EQAS) | As specified by the supplying external quality assessment agency |
Step-by-Step Procedure
Run the chosen internal QC material once (or once per shift) for 20 consecutive working days to build a baseline data set for that lot.
Calculate the mean and standard deviation (SD) of the 20 baseline values — these become the laboratory's own target values for that QC lot.
Plot the days on the X-axis and the control values on the Y-axis. Draw the mean as a horizontal line, then draw ±1SD, ±2SD and ±3SD lines parallel to it.
Analyze the QC material at the start of every shift (morning and evening), after instrument servicing, whenever a new reagent lot is opened, and whenever patient results look inappropriate.
Compare each new QC point against Westgard multirule criteria (1:3s, 2:2s, 4:1s and similar) to decide whether to accept the run or investigate and correct an error before releasing any patient reports.
Flow Diagram
Quality Control
QC material is run at the start of each shift (morning and evening), after instrument servicing, whenever a new reagent lot is opened, and whenever patient results look inappropriate. Results are plotted on a Levey-Jennings chart and evaluated using Westgard rules; any run outside the accepted mean ±2SD range is held and investigated before reports are released.
Laboratories periodically analyze blinded samples supplied by an External Quality Assessment Scheme (EQAS) and compare their results with peer laboratories using the same method or instrument, verifying long-term accuracy against a value assigned by a reference or definitive method.
Reference Values
Normal Ranges⚠️ Reference ranges may vary between laboratories. Always apply your laboratory's established reference intervals.
Clinical Interpretation
| Finding | Possible Significance | Action / Follow-up |
|---|---|---|
| One QC value exceeds ±1SD (1:2s) | Warning only | Inspect the trend; usually accept the run and continue monitoring |
| 2 consecutive values exceed ±2SD, or 4 consecutive exceed ±1SD (2:2s / 4:1s) | Systematic error | Reject the run, investigate calibration or reagent lot, correct before releasing reports |
| One value exceeds ±3SD, or one exceeds +2SD while another exceeds −2SD (1:3s / R:4s) | Random error | Reject the run immediately, withhold patient reports, troubleshoot the instrument |
Common Errors & How to Avoid Them
Cause: Illegible handwriting (e.g. FBS misread as RBS), wrong patient ID, wrong collection tube, hemolyzed or delayed sample
Prevention: Verify patient identity and requisition details before collection; reject visibly hemolyzed or clotted samples; transport within 10–15 minutes
Cause: Uncorrected calibration error, aging reagent, worn pipette or glassware
Prevention: Run QC material every shift, follow the manufacturer's calibration schedule, and act immediately on Westgard rule violations
Cause: Wrong patient identification when entering or reporting results, unclear handwriting, delayed reporting
Prevention: Double-check patient ID before release; use electronic/LIS reporting where available; compare with previous values
Laboratory Tips from the Bench
Always run your QC material before the first patient sample of the shift — never after. Catching a problem before patient samples are run saves you from repeating an entire batch.
Keep QC material in small aliquots at −20°C rather than repeatedly freeze-thawing one bottle; repeated freeze-thaw cycles change analyte concentration and will falsely widen your SD.
Remember the order P-A-P for the three error types, following the sample's journey: Pre-analytical → Analytical → Post-analytical. About 75% of all lab errors happen before the sample even reaches the analyzer — Pre-analytical.
Important Notes
The mean ±2SD control limit describes how tightly your instrument reproduces a known QC value — it has nothing to do with the normal reference range of the analyte in patients. Do not confuse the two.
A random error (e.g. a sudden power fluctuation) affects only the run at that moment. A systematic error (e.g. a faulty pipette) affects every subsequent test equally until corrected — this distinction determines how you troubleshoot.
Interactive Quiz
Test Your KnowledgeFlashcards
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Clinical Case Study
Apply Your KnowledgeMrs. Rao's fasting blood sample was sent for glucose and creatinine as part of a routine diabetes follow-up, with her report due within 2 hours per hospital turnaround policy.
The Level-2 glucose QC value fell beyond +3SD immediately after a new reagent lot was opened, triggering a Westgard 1:3s violation. Following protocol, the technologist withheld Mrs. Rao's glucose report, re-calibrated with the new lot, re-ran the QC, and confirmed it returned to the accepted range before releasing a corrected — and now trustworthy — report.
- →Always run QC immediately after opening a new reagent lot, not just at the start of the shift
- →A single point beyond ±3SD (1:3s) is treated as a random or systematic error and must halt reporting
- →Correcting an error before reporting protects patient safety even if it delays turnaround time
Frequently Asked Questions
Quality control (QC) is the day-to-day statistical checking of results against control material. Laboratory quality management is the broader system — goals, resources, QC processes, assessment and improvement — within which QC operates.
Because it accounts for roughly 75% of all laboratory errors. Even though clinicians and phlebotomists are often responsible for ordering and collection, laboratory personnel who detect a pre-analytical problem must reject the sample rather than process it, since a bad sample can never give a reliable result.
At the beginning of every shift, ideally morning and evening, plus after instrument servicing, after opening a new reagent lot, and whenever patient results look clinically inappropriate.
Quick Revision
10-Minute ReviewKey Takeaways
- Quality control (QC) is a measure of precision; accuracy is a measure of closeness to the true value — a system can be one without the other.
- Laboratory quality management follows a continuous cycle: set goals → provide resources → set QC processes → assess quality → improve.
- About 75% of laboratory errors are pre-analytical, making sample and order verification critical.
- Analytical errors (calibration, interference, sample mix-up) are reduced through routine QC material analysis.
- The Levey-Jennings chart with Westgard multirules is the standard tool for detecting random and systematic error.
- No patient report should be released while a QC run sits outside its accepted control limits.
Competency Checklist
Track Your MasteryReferences
- National Institute of Open Schooling (NIOS). Biochemistry — Module: Laboratory Quality Management (Lesson 26).
- Westgard JO. Basic QC Practices: Training in Statistical Quality Control for Healthcare Laboratories. 4th ed.
- CLSI. Statistical Quality Control for Quantitative Measurement Procedures (C24).