Internal quality control charts for colorimetric PNB testing

A colorimetric para-nitrobenzoic acid (PNB) test provides a categorical result: the control organism either grows or is inhibited, with a corresponding change in the medium’s colour. An internal quality control chart turns those observations into a traceable record, showing whether each run meets the laboratory’s acceptance criteria and whether performance is drifting over time. It supports quality management without replacing the need to read and validate every patient result.

Designing a TB lab internal quality control chart for colorimetric PNB test results starts with the test’s purpose and the work the laboratory actually performs. In Australia, many hospital pathology services in cities such as Sydney and Melbourne refer tuberculosis (TB) isolates for specialised drug-susceptibility testing, while reference laboratories in other states perform or coordinate confirmatory work. Quality requirements should therefore cover the testing site, any referral handover and the point where results are authorised, even when a local laboratory mainly prepares or forwards specimens.

The operating environment matters. Australia’s small specialist market for TB media means teams may purchase imported PNB products through local distributors and rely on manufacturer instructions, certificates of analysis and lot documentation. Hot weather in Brisbane and Perth can affect storage and courier journeys, while remote services may experience long transit times. Teams should preserve transport records and document any excursion against the product’s stated conditions rather than assuming that arrival at the laboratory proves stability.

Common Australian laboratory habits include electronic pathology reporting alongside controlled spreadsheets and email notifications for exceptions. A PNB chart should fit that environment without exposing patient identifiers: use control codes in the working chart and retain identifiable clinical information in the authorised laboratory record. The result is a practical quality tool that can be reviewed across sites, staff and shifts.

Define the purpose and scope

The chart must answer defined questions. It should show whether the control material performs as expected, whether each run is acceptable, and whether repeated failures or gradual changes require investigation. Record growth, inhibition and colour appearance separately so that a normal final colour is not mistaken for acceptable performance throughout the run. A reference control that fails invalidates the associated patient results under the laboratory’s documented rules.

Agree who will use the chart and how often they will review it. The laboratory supervisor may need immediate notification of failed controls, while the quality manager may examine monthly trends and the medical director may assess the effect on reported results. A structured gap review is more useful than an unused form. The phase-specific checklists provided by the GLI Quality Tool can help identify the documents, responsibilities and records that still need to be established.

Build the quality system around the chart

A practical quality framework should connect the chart with safety, personnel, equipment, documentation, assessment and continual improvement. The GLI Quality Tool provides a four-phase roadmap organised around twelve Quality Systems Essentials. These provide useful context for a PNB chart because a failed control may originate in training, equipment, storage, documentation or another part of the laboratory system.

Australian laboratories seeking NATA accreditation are assessed against ISO 15189 and applicable national requirements. TB is also notifiable under state and territory legislation, including the Public Health Act 2008 in New South Wales and the Public Health and Disease Prevention Act 2008 in Victoria. These laws shape notification and liaison duties, while the Privacy Act 1988 and applicable health-records laws govern identifiable information. The control chart itself should contain no patient names or unnecessary clinical details.

Assign ownership without creating overlapping responsibilities. Name the person responsible for completing each run, the person reviewing exceptions and the person authorised to decide whether affected results require action. Keep one controlled master chart, version its templates, restrict editing rights and maintain a backup. Working copies held by individual staff or teams should be reconciled with the master so that a result cannot disappear between shifts.

Choose controls and a reading method

Select control materials with known, documented performance and suitable traceability. The set should allow detection of both failure to inhibit a susceptible organism and unwanted growth of a resistant organism. Use materials authorised by the product instructions or the laboratory’s validation, and keep their identity, lot, expiry and expected appearance linked to the chart. Any new control material or major change to preparation should undergo the same qualification process as the original material.

Colour reading requires consistency. For many PNB formulations, retained red colour or visible growth indicates resistance, while conversion to yellow indicates inhibition, but the precise endpoint must come from the manufacturer’s instructions. Establish a documented lighting condition, background and viewing method, and check that readers can distinguish the specified colours. If a validated instrument supplies a numerical reading, record its identification, settings and quality status alongside the visual assessment.

Verify each new medium and reagent lot before routine use. Compare the expected control appearance, consistency and interpretation with the established baseline, and retain the evidence used for release. Reader duties should be named rather than assumed. The staff job description guidance can support clear allocation of testing, review and sign-off responsibilities.

Structure the chart and run record

Design one row per control run, with each run uniquely identified. The chart header should identify the method version, PNB product, medium lot, expiry details, control material and lot, reader, instrument where applicable, and the applicable acceptance criteria. Each row should contain the date and run identifier, expected result, observed result, accept-or-reject decision, any deviation and the initials of the person completing and reviewing the entry.

Context turns isolated failures into useful information. Record reagent or media lots, transport-condition exceptions, equipment status and relevant environmental excursions. Add columns for repeat testing and corrective action rather than overwriting the original observation. An out-of-limit value should remain visible: erasing or adjusting it destroys the evidence needed to investigate a shift in performance.

Keep the working chart focused on quality control. Patient identifiers belong in the authorised clinical system, and referral specimens should have a separate transport and receipt record if the laboratory does not perform PNB testing itself. Review the chart at defined intervals and after changes to staff, product lots, instruments or procedures. A chart that is never reviewed remains documentation rather than a working control.

Establish limits and acceptance rules

Set warning and action criteria before reviewing the result. Individual-run requirements should follow the product instructions and the laboratory’s validation, while statistical limits, where used, should come from a stable baseline of control observations. Do not calculate limits from a period already showing drift, and do not change the criteria because an unexpected result is inconvenient. Explain each rule in a written plan so that different staff members apply it consistently.

A qualitative PNB method should usually begin with a run-acceptance chart showing the expected control result, the observed result and the pass-or-fail decision. An attribute chart may summarise the proportion of accepted runs, while a Levey–Jennings-style numerical chart requires a validated quantitative measurement, not invented scores based on visual colour judgements. For validated quantitative data, document the central value, control limits and any multirule approach used to detect random error or systematic shifts.

A control outside its expected appearance is an immediate failure, even when the surrounding run history looks good. For quantitative control data, rules such as one result beyond three standard deviations or two consecutive results beyond two standard deviations can support rejection decisions. These rules supplement the basic acceptance criteria; they do not replace them. Record the rule triggered, the decision made and the evidence used to resolve it.

Investigate exceptions and protect results

Investigate every unexpected control result rather than assuming that the medium or the operator is at fault. Review storage and transport records, product and reagent lots, expiry status, equipment checks, specimen preparation, reading conditions and transcription. Confirm whether other staff saw the same endpoint and whether nearby runs show a related pattern. This approach separates isolated procedural errors from recurring problems affecting a lot, device or work area.

Contain the impact on patient testing. Stop release of results associated with an invalid run, notify the responsible supervisor and repeat the controls after the suspected problem has been corrected. Determine whether previously reported results need review, and communicate with clinicians and the relevant reference laboratory when necessary. The assessment should follow the laboratory’s documented procedure for invalidating, repeating and reporting affected results, with clinical advice available when required.

Record corrective and preventive action, including the cause, evidence of correction and follow-up date. Look for special-cause trends such as increasing failures after a particular delivery, recurrent difficulties with one reader or consistent colour changes during hotter months. These findings can justify focused training, a supplier enquiry, an equipment check or a change in transport arrangements. Review their effectiveness later instead of closing the action simply because the next run passed.

Review performance and embed routine use

Review the chart regularly and include it in the laboratory’s internal audit programme. Trend control failures, repeat tests, invalid runs, median time to corrective action and results by lot, reader and test day where those comparisons are meaningful. Discuss persistent patterns through the quality management process, assign actions to named owners and retain evidence of follow-up. Training should cover chart completion, colour interpretation, acceptance decisions and escalation, not just the analytical steps.

Keep internal quality control distinct from external quality assessment and proficiency testing. External programmes assess performance through an independent challenge, while the internal chart monitors routine runs and reveals problems between proficiency events. A satisfactory proficiency result does not cancel a failed internal control. Use both forms of evidence to assess competence, process stability and the laboratory’s readiness to provide reliable results.

Make the next step concrete: select the PNB control set, assign the chart owner, document the acceptance rules and schedule the first review before the next test run. Open the quality record now, choose the first control and owner, and set the review date.