Internal quality control (IQC) is a set of procedures that a laboratory runs alongside patient samples to verify that its testing systems are producing accurate and consistent results. Every day that patient specimens are tested, the lab also tests special control materials with known values. If those control results fall within an expected range, the lab can trust its patient results. If they fall outside that range, something has gone wrong and patient results are held until the problem is fixed.
IQC is the backbone of daily laboratory reliability. It catches errors in real time, before incorrect results reach a patient or clinician, and it applies to everything from routine blood chemistry panels to molecular tests and tissue staining.
What IQC Actually Monitors
IQC tracks two core properties of a testing system: accuracy and precision. Accuracy refers to how close a result is to the true value. When a control material has a known target value and the lab consistently measures something slightly higher or lower, that gap is called bias, and it reflects a systematic error in the process. Precision refers to how consistently the system reproduces the same result when measuring the same material over time. A lab can measure its precision by looking at how spread out its control results are from the average. A wider spread means more random error creeping into results.
Both types of error matter for patient care. A systematic bias might cause every cholesterol result to read 5% too high, leading to unnecessary treatment decisions. Random imprecision might cause the same patient’s glucose level to bounce unpredictably between draws, making it hard for clinicians to track real changes.
How Control Materials Work
Control materials are manufactured samples with established target values. They come in two main formats: liquid-stable controls, which are ready to use straight from the vial, and lyophilized (freeze-dried) controls, which need to be reconstituted with water before testing. Both serve the same purpose, but liquid controls eliminate the variability that can come from inconsistent reconstitution. Lyophilized materials, on the other hand, tend to have a longer shelf life.
Labs typically run controls at two or more concentration levels. A low-value control and a high-value control together cover a wider range of the test’s measurement capability. This matters because a test system might perform well in the normal range but drift at very low or very high concentrations.
How Often Labs Must Run QC
In the United States, the Clinical Laboratory Improvement Amendments (CLIA) set minimum frequencies. The baseline requirement is at least once each day that patient specimens are tested. For quantitative tests, that means two control materials of different concentrations. For qualitative tests (those that produce a positive or negative answer), a positive and a negative control must be included. Molecular amplification tests require two controls plus, when relevant, a material that can detect reaction inhibition, a common source of false negatives.
Some testing areas have stricter schedules. Routine chemistry tests require one control material every eight hours of testing, using a combination that covers both low and high values each day. If automated instruments internally verify their calibration at least every 30 minutes, one control per testing event may suffice. Manual coagulation testing requires each individual analyst to run two levels of controls before testing patient samples and again whenever a reagent changes. For histopathology stains like fluorescent or immunohistochemical markers, positive and negative reactivity checks are required each time the stain is used.
Levey-Jennings Charts and Westgard Rules
Raw QC numbers are hard to interpret in isolation. Labs plot their control values over time on a Levey-Jennings chart: a simple graph with the control result on the vertical axis and date or run number on the horizontal axis. The chart is marked with lines at the mean value and at one, two, and three standard deviations above and below the mean. When results cluster tightly around the mean, the system is stable. When points start drifting or scattering, the chart makes that visible at a glance.
To turn those visual patterns into clear decision rules, most labs apply Westgard rules. These define specific conditions that signal a problem:
- 1-3s rule: A single control value falls more than three standard deviations from the mean. This usually indicates a random error and triggers immediate investigation.
- 2-2s rule: Two consecutive values land more than two standard deviations on the same side of the mean, suggesting a systematic shift.
- 3-1s rule: Three consecutive values exceed one standard deviation on the same side. This is a subtler signal of a trend or gradual drift in the system.
When any of these rules is violated, patient results from that run are not reported until the issue is resolved.
What Happens When QC Fails
A failed QC result triggers a structured troubleshooting process. The first step is to repeat the control. If the repeat result falls within two standard deviations of the mean, the failure is treated as a random occurrence, and patient results can be reported. If the repeat also falls outside limits, the run is rejected and all patient results are held.
Next, the lab determines whether the error pattern looks random or systematic. Random errors point toward problems like air bubbles in samples, inconsistent pipetting, or temperature fluctuations. Systematic errors, where results consistently shift in one direction, point toward expired reagents, a degraded calibrator, or a change in the control material itself.
Once the cause is identified and corrected, the instrument is recalibrated, controls are retested, and if those results pass, every patient sample believed to have been affected by the out-of-control condition is retested before reporting. If the root cause can’t be identified or the controls continue to fail, the lab must sequester all results and conduct a formal root cause analysis before resuming testing.
IQC vs. External Quality Assessment
Internal QC is something a lab does on its own, every day, to monitor its own performance. External quality assessment (EQA), sometimes called proficiency testing, is a separate process where an outside organization sends identical samples to many laboratories. Each lab tests the sample and reports its result, and the organizing body compares results across all participants. EQA functions as an inter-laboratory benchmark, revealing whether a given lab’s results are in line with what other labs using similar methods are producing.
The two systems complement each other. IQC catches day-to-day problems in real time. EQA, which typically happens on a periodic schedule, catches longer-term biases that a lab might not notice internally because its own control data looks stable. In Europe, EQA programs have traditionally emphasized their educational role, helping labs identify and correct systematic differences rather than simply passing or failing them.
Risk-Based Quality Control Plans
Not every test carries the same risk of error, and not every error carries the same risk to patients. Recognizing this, CLIA now allows laboratories to develop an individualized quality control plan (IQCP) as an alternative to the default QC frequency requirements. An IQCP requires the lab to perform a formal risk assessment of the entire testing process, covering the pre-analytical phase (specimen collection, handling, transport), the analytical phase (the measurement itself), and the post-analytical phase (result reporting and interpretation).
Based on that assessment, the lab designs a QC plan tailored to the specific risks of each test system. A highly automated, well-validated analyzer with built-in error detection might warrant a leaner QC schedule, while a manual test with many operator-dependent steps might need more frequent controls. The lab must also maintain a quality assurance plan to continuously monitor whether the IQCP is actually working. This approach aligns with broader principles of risk management in laboratory medicine, shifting the focus from rigid one-size-fits-all rules toward evidence-based strategies matched to actual sources of error.
Regulatory Standards
The international standard governing medical laboratory quality is ISO 15189, most recently updated in 2022. It requires laboratories to implement IQC strategies that include selecting appropriate control materials, defining control frequency, setting acceptable limits, applying statistical decision rules, comparing results across instruments, and handling nonconformities when QC fails. The International Federation of Clinical Chemistry (IFCC) has published detailed guidance on how to put these requirements into practice, covering everything from how to evaluate whether your control materials behave like patient samples to how to calculate measurement uncertainty from your QC data.
In the U.S., CLIA regulations carry the force of law, and laboratories must meet their QC requirements to maintain certification. ISO 15189 accreditation is voluntary in some countries but mandatory in others, and many labs pursue it as a mark of competence regardless of local requirements.