The Three Phases of Laboratory Quality

Quality in the clinical laboratory is managed across three distinct phases of the testing process, each with its own failure modes and quality control strategies. A comprehensive quality management program must address all three to ensure that final results reliably reflect the true clinical state of the patient.

Pre-Analytical Phase

The pre-analytical phase covers everything that happens to a specimen before it reaches the testing instrument: the clinical indication for ordering the test, the specimen collection technique, the tube or container type, the labeling of the specimen, its transport conditions and timing, and its processing in the laboratory (centrifugation, aliquoting, storage). Studies consistently show that 60 to 70 percent of all laboratory errors occur in this phase — a proportion that has changed little despite advances in analytical technology, because many pre-analytical steps involve manual processes performed at the bedside or during specimen transport.

Pre-analytical quality control includes standardized collection procedures, staff training and competency assessment, specimen rejection criteria for inadequate samples, and barcode-based specimen tracking systems that reduce the risk of specimen identification errors. In molecular diagnostics, pre-analytical quality is particularly critical because nucleic acids are vulnerable to degradation from improper collection, temperature excursions during transport, and delays between collection and processing.

Analytical Phase

The analytical phase covers the actual testing process on the instrument. This is where traditional internal quality control — using materials of known concentration processed alongside patient samples — monitors the performance of the assay and instrument over time. Analytical quality control detects problems with reagents, instruments, calibrators, and operator technique before they affect patient results.

Post-Analytical Phase

The post-analytical phase covers result review, reporting, interpretation, and clinical communication. Post-analytical errors include transcription errors in result entry, failure to recognize clinically critical values and notify the ordering physician, erroneous reference range displays, and delays in result delivery. Auto-verification systems, critical value alerting, and electronic LIS-to-EHR result transmission address many post-analytical risks in modern laboratories.

Internal Quality Control: The Real-Time Watchdog

Internal quality control (IQC) in molecular diagnostics uses materials of known nucleic acid concentration — typically consisting of positive controls at defined high, medium, and low concentrations, and a negative control — processed in each testing run alongside patient specimens. The measured value for each control is compared against acceptance limits derived from the historical performance of that control on that assay. Results that fall outside acceptance limits indicate potential analytical problems and trigger a hold on patient result reporting pending investigation.

Westgard Rules: Statistical Framework for QC Decisions

The Westgard rules provide a widely adopted statistical framework for deciding when a quality control result indicates a random error (a chance fluctuation unlikely to affect patient results) versus a systematic error (a real shift in assay performance that requires investigation). Developed by Dr. James Westgard in the 1980s and subsequently updated as evidence and computing power evolved, these rules define objective criteria for QC rejection that minimize both false rejections (unnecessarily stopping a run that was actually in control) and false acceptances (allowing a run with a real problem to continue).

External Quality Assessment: Benchmarking Against Peers

External quality assessment (EQA) — also called proficiency testing (PT) in the United States — supplements internal QC by providing laboratories with anonymous unknown specimens prepared by an independent organization, which the laboratory tests using its routine methods and reports results for comparison against peer laboratory performance and expected values.

Proficiency testing serves two distinct purposes. For the individual laboratory, it provides an objective external check that cannot be influenced by internal biases or familiarity with the control material — the laboratory does not know the true value before testing, which prevents any conscious or unconscious bias in the testing process. For the broader laboratory community, aggregated PT data identify systematic performance differences between different test methods, platforms, and calibrator lots that may affect result comparability between laboratories — a critical issue when patients change hospitals or when results from different laboratories are compared in clinical trials.

In the United States, CLIA mandates that laboratories performing clinical testing in many categories participate in accredited PT programs and achieve satisfactory performance on a defined proportion of proficiency testing challenges. Failure to achieve satisfactory PT performance triggers mandatory corrective action, which must be documented in the LIS quality management system. Repeated or uncorrected PT failure can result in restriction or revocation of the laboratory’s CLIA certificate — the authorization to perform patient testing.

Method Validation: Proving the Assay Works Before It Tests Patients

Before a new molecular assay is introduced into clinical use, it must be validated to demonstrate that its analytical performance meets defined acceptance criteria for the intended clinical application. For commercially manufactured assays with FDA clearance or approval, laboratories must verify — rather than fully validate — the manufacturer’s performance claims by confirming that the assay performs as specified in the manufacturer’s labeling under the local laboratory’s conditions. For laboratory-developed tests (LDTs), full validation including establishing the method’s own performance claims is required.

Validation studies for molecular assays typically establish the limit of detection (the lowest concentration reliably detected by the assay), the limit of quantitation (the lowest concentration that can be accurately quantified), the linear range, the analytical specificity against non-target organisms and common interfering substances, and the performance across the full menu of specimen types for which the assay will be used. Cross-reactivity testing evaluates whether the assay produces false-positive results when tested against organisms related to but distinct from the intended target — a critical specificity check for assays designed to detect specific pathogens in specimens that may contain a variety of commensal organisms.

For automated molecular platforms where the instrument and assay reagents are validated as a system, verification must confirm that the platform functions as specified in the local laboratory environment, using locally sourced specimens from the patient population it will serve. Performance in the specific laboratory — which may differ from the manufacturer’s study sites in ways that affect result quality — must be confirmed before patient testing begins.

Automation and QC: How Modern Platforms Simplify Compliance

Fully automated molecular diagnostic platforms have significantly simplified quality control management while simultaneously improving the reliability and comprehensiveness of QC monitoring. On-board process controls — internal controls included within every patient reaction cartridge by the manufacturer — continuously monitor extraction, amplification, and detection in every patient run without requiring separate control specimens to be prepared and tracked by laboratory staff.

Electronic QC management within integrated molecular platforms automatically records all quality control data, applies acceptance rules, and prevents patient result reporting when QC criteria are not met — all without requiring manual documentation or judgment by the operator. Electronic QC records are time-stamped, user-attributed, and stored in secure audit trails that satisfy accreditation and regulatory requirements for QC documentation. The burden of manual QC documentation that consumed significant laboratory staff time in earlier generations of molecular testing is largely eliminated in modern automated systems.

Reagent lot management is another area where automation improves QC. Automated systems track the lot numbers and expiration dates of all reagents used in each patient run, automatically preventing the use of expired materials and generating lot-specific QC data that allows laboratory managers to compare performance across reagent lots — identifying lot-to-lot variation that might otherwise go undetected until it affects patient results.

The Human Element: Competency, Training, and Culture

No system of quality controls, automated checks, and statistical rules can substitute for the foundational requirement of a skilled, knowledgeable, and quality-focused laboratory workforce. Competency assessment — the ongoing evaluation that laboratory staff can correctly perform all aspects of the testing process for which they are responsible — is a CLIA and accreditation requirement that reflects the recognition that technical skills must be actively maintained, not assumed.

Competency assessment for molecular laboratory staff typically includes direct observation of test performance, review of quality control and instrument maintenance records, evaluation of the analyst’s ability to identify and respond to instrument flags and QC failures, and periodic testing using unknown specimens to confirm technical accuracy. Initial competency assessment is performed before an analyst begins independent patient testing; ongoing assessment at defined intervals ensures that skills are maintained as methods evolve and staff experience changes.

Beyond formal competency assessment, the quality culture of a laboratory — the collective commitment of all staff to identifying and reporting errors, near-misses, and potential quality risks — determines whether the formal quality management system functions as intended. A laboratory where staff feel safe to report errors and where leadership responds constructively to quality concerns with system improvements rather than individual blame is one where the formal QC system is reinforced by the attitudes and behaviors of the people who work within it. Quality management in the molecular laboratory is ultimately a human endeavor, supported by technology but driven by the professional standards and personal commitment of the laboratory scientists who perform the tests and the leaders who set the expectations for their work.