# Troubleshooting Out-of-Control Results in Clinical Laboratory QC ## Quick Answer - When a QC result fails Westgard rules, work through a fixed sequence: confirm the error, inspect the control and reagent records, then check instrument function before repeating or replacing materials. - Document every observation and corrective action in the laboratory quality record so the investigation is traceable and defensible during audits. - A single failed control does not always mean patient results are wrong, but patient results should be held until the cause is identified and the system is verified. ## At a Glance | Failure Pattern | Likely Cause Category | First Action | Escalation Criteria | | --- | --- | --- | --- | | Single control value outside 2 SD | Random error, reagent lot change, or operator variation | Repeat the control once after checking reagent volume and expiration | Repeat failure or failure on a second level triggers full investigation | | Shift (5 to 7 consecutive values on one side of mean) | Calibrator change, reagent lot change, or temperature drift | Verify calibration status and reagent lot records | Shift persists after recalibration, escalate to instrument service | | Trend (steadily increasing or decreasing values) | Reagent degradation, lamp aging, or gradual temperature change | Check reagent open dates and instrument maintenance log | Trend continues after reagent replacement, escalate to manufacturer support | | Increased standard deviation | Mixing error, pipette malfunction, or unstable control material | Inspect pipette calibration and control reconstitution records | SD remains elevated after corrective action, perform method validation review | ## Understanding the Purpose of Quality Control in the Clinical Laboratory Quality control in the clinical laboratory exists to verify that an analytical system produces reliable results within an acceptable range of error. Control materials are stable samples with known target values that are tested alongside patient samples. When control results fall outside established limits, the laboratory cannot assume patient results are valid. The investigation that follows is a structured process of elimination that identifies whether the problem lies in the reagent, the calibrator, the instrument, the control material, or the operator. The National Institute of Standards and Technology describes measurement science as the foundation for ensuring that results are comparable and trustworthy across different laboratories and over time. In clinical diagnostics, this principle translates directly into the requirement that every analytical run includes controls that verify the measurement system is performing as expected. Without this verification step, a laboratory cannot distinguish between a true patient result and an artifact of instrument or reagent failure. Control materials are manufactured to be stable and homogeneous, which means they should produce consistent results when the analytical system is functioning properly. A control result that falls outside the expected range signals that something in the measurement process has changed. The change could be small, such as a reagent that has begun to degrade, or large, such as a failed instrument component. The troubleshooting process is designed to identify which of these possibilities is most likely and to guide the laboratorian toward a corrective action that restores the system to proper function. The statistical basis for quality control relies on the mean and standard deviation of control values established during method validation or over an initial testing period. These statistics define the acceptable range for future control results. When a control value falls outside this range, the laboratory applies decision rules, often called Westgard rules, to determine whether the failure is random or systematic. Random failures occur by chance and may not require extensive investigation. Systematic failures, such as shifts or trends, indicate a persistent problem that must be corrected before patient testing can continue. ## Core Principles of Control Interpretation ### The Mean and Standard Deviation as the Foundation Every control material has an assigned target value, but the laboratory must establish its own mean and standard deviation for each lot of control material on each instrument. This is because instruments vary in their calibration and performance characteristics. The laboratory mean is calculated from a minimum number of control measurements collected over a defined period, typically 20 or more data points collected across multiple days. This approach accounts for day-to-day variation that is inherent in any analytical system. The standard deviation describes the dispersion of control results around the mean. A small standard deviation indicates that the system produces consistent results, while a large standard deviation indicates greater variability. The acceptable range for control results is typically defined as the mean plus or minus two standard deviations, which should contain approximately 95 percent of results when the system is in control. Some laboratories use three standard deviations as the action limit, which contains approximately 99.7 percent of results. The choice of control limits affects the sensitivity of the quality control system. Narrower limits detect problems earlier but produce more false alarms. Wider limits produce fewer false alarms but may miss subtle problems. The laboratory must balance these considerations based on the clinical requirements of the assay and the acceptable risk of reporting incorrect patient results. ### Westgard Rules and Their Application Westgard rules are a set of decision criteria used to interpret control results. The most commonly used rules include the 1-2s rule, which flags a single control value exceeding two standard deviations from the mean, and the 1-3s rule, which flags a single control value exceeding three standard deviations. Additional rules detect systematic patterns, such as the 2-2s rule, which flags two consecutive control values exceeding two standard deviations on the same side of the mean, and the R-4s rule, which flags a range of four standard deviations between two control values in the same run. The 4-1s rule flags four consecutive control values exceeding one standard deviation on the same side of the mean, indicating a shift. The 10x rule flags ten consecutive control values on the same side of the mean, also indicating a shift. These rules are applied in combination to maximize the detection of both random and systematic errors while minimizing false rejections. When a control result triggers a Westgard rule, the laboratory must decide whether to accept or reject the run. A single 1-2s violation may be acceptable if the assay is stable and the violation appears random. However, a 1-3s violation or any violation of the multi-rule criteria requires investigation and corrective action before patient results are reported. ### The Difference Between Random and Systematic Error Random error produces control results that vary unpredictably around the mean. A single control value outside two standard deviations may represent random error, especially if the control result on the other level is within range. Random error is often caused by operator variation, such as inconsistent pipetting, or by transient conditions, such as a brief power fluctuation. Systematic error produces control results that are consistently shifted in one direction or that trend progressively in one direction. A shift is an abrupt change in the mean of control results, while a trend is a gradual change over time. Systematic error is caused by persistent problems, such as a reagent that has degraded, a calibrator that was prepared incorrectly, or an instrument component that is failing. Distinguishing between random and systematic error is the first step in troubleshooting because it narrows the range of possible causes. Random error points toward operator technique or transient conditions. Systematic error points toward reagents, calibrators, or instrument components that have changed over time. ## The Troubleshooting Workflow ### Step 1: Confirm the Control Failure The first action when a control result fails is to confirm that the failure is real and not the result of a data entry error or a misidentified control. Check that the correct control material was tested, that the control lot number and expiration date were recorded correctly, and that the result was entered into the quality control system accurately. This step takes minutes and can prevent an unnecessary investigation. If the control failure is confirmed, examine the control results from the current run and from previous runs. Determine whether the failure is isolated to one control level or affects both levels. Determine whether the failure is a single point outside the limit or part of a pattern, such as a shift or trend. This information guides the next steps in the investigation. ### Step 2: Review the Control Material Records Control material can fail for reasons related to its preparation, storage, or handling. Check the reconstitution date and time for lyophilized controls. Verify that the correct volume of diluent was used and that the diluent was at the correct temperature. Check whether the control material was mixed thoroughly after reconstitution and whether it was allowed to equilibrate to room temperature before use. Check the storage conditions for the control material. Most controls require refrigeration or freezing and are stable only until the expiration date printed on the vial. If the control material was left at room temperature for an extended period, exposed to light, or used past its expiration date, the control results may be unreliable. In this case, the corrective action is to prepare a fresh vial of control material and repeat the control test. Also check whether the control material lot has changed recently. A new lot of control material will have a different target value and may require the laboratory to establish new mean and standard deviation values. If the laboratory is using a new lot without updating the quality control parameters, the control results will appear to fail even though the system is performing correctly. ### Step 3: Inspect the Reagent and Calibrator Status Reagents are a common source of systematic error in clinical assays. Check the reagent lot number and expiration date. Verify that the reagent was stored at the correct temperature and that it has not been exposed to conditions that could cause degradation. Check whether the reagent has been opened for an extended period and whether the open stability date has been exceeded. Check whether the reagent lot has changed recently. A new reagent lot may have a slightly different composition or performance characteristics that require recalibration. If the laboratory did not perform the required calibration after introducing the new reagent lot, the control results may be shifted. Calibrators establish the relationship between the instrument response and the analyte concentration. If the calibrator was prepared incorrectly, expired, or stored improperly, the calibration curve will be inaccurate, and control results will fail. Check the calibrator lot number, expiration date, and preparation records. If the calibrator is suspect, recalibrate the instrument using a fresh vial of calibrator and repeat the control test. ### Step 4: Evaluate Instrument Function and Maintenance Instrument components can fail gradually or suddenly, producing changes in control results. Check the instrument maintenance log to determine when the last preventive maintenance was performed and whether any maintenance is due. Common maintenance items include cleaning the sample probe, replacing the lamp, and checking the fluidics system. Check the instrument temperature records. Many assays are temperature sensitive, and a drift in temperature can produce a trend in control results. Verify that the instrument temperature is within the specified range and that there have been no recent fluctuations. Check the instrument for error messages or flags that may have been recorded during the run. Some instruments record internal diagnostics that can indicate a problem with a specific component. If the instrument has a service log, review recent entries to determine whether any repairs or adjustments were made that could affect assay performance. ### Step 5: Assess Operator Technique and Sample Handling Operator variation is a common cause of random error in control results. If the control failure is isolated and the control material and reagent records are normal, consider whether the operator may have made an error during the test. Common errors include using the wrong pipette volume, failing to mix the sample thoroughly, or introducing air bubbles into the reaction vessel. Check whether the operator followed the standard operating procedure for the assay. If the procedure was not followed, the corrective action is to repeat the test with proper technique. If the operator is new or has not performed the assay recently, additional training may be required. Sample handling can also affect control results. Controls should be treated the same as patient samples in terms of preparation and handling. If the control material was not allowed to reach room temperature before testing, or if it was vortexed too vigorously, the results may be affected. ### Step 6: Repeat the Control Test After completing the initial checks, repeat the control test using the same control material and reagent. If the repeat result is within range, the original failure may have been a random event, and the run can be accepted. If the repeat result is also out of range, the problem is systematic, and further investigation is required. When repeating the control test, use a fresh aliquot of control material if possible. This distinguishes between a problem with the control material itself and a problem with the analytical system. If the fresh aliquot produces an in-range result, the original control material may have been compromised. If the fresh aliquot also produces an out-of-range result, the problem lies in the reagent, calibrator, or instrument. ### Step 7: Isolate the Cause Through Systematic Replacement If the control failure persists after repeating the test, the next step is to isolate the cause through systematic replacement. This process involves changing one variable at a time and testing the effect on control results. The order of replacement should follow the likelihood of the cause, starting with the most common and easiest to replace. Replace the reagent with a fresh vial from the same lot. If the control results return to range, the original reagent was the cause. If the control results remain out of range, replace the reagent with a vial from a different lot. If the control results return to range, the reagent lot was the cause, and the laboratory should contact the manufacturer. If reagent replacement does not resolve the problem, recalibrate the instrument using a fresh calibrator. If the control results return to range after recalibration, the original calibration was the cause. If the control results remain out of range, the problem may be in the instrument itself, and the laboratory should contact the instrument manufacturer for service. ### Step 8: Document the Investigation and Corrective Action Every troubleshooting investigation must be documented in the laboratory quality record. The documentation should include the date and time of the control failure, the control material lot number and expiration date, the reagent lot number and expiration date, the calibrator lot number and expiration date, the instrument used, and the operator who performed the test. The documentation should also include a description of the investigation steps taken, the observations made at each step, and the corrective action that resolved the problem. If the problem could not be resolved, the documentation should include the escalation to the instrument manufacturer or the laboratory supervisor. The documentation serves multiple purposes. It provides a record of the laboratory's response to the control failure, which may be reviewed during accreditation inspections. It also provides a reference for future troubleshooting, because the laboratory can review past investigations to identify recurring problems with specific reagents, calibrators, or instruments. ## Common Failure Patterns and Their Causes ### Single Control Value Outside Two Standard Deviations A single control value outside two standard deviations is the most common control failure. This pattern may represent random error, which occurs in approximately 5 percent of control tests even when the system is functioning properly. If the control value on the other level is within range, and if the failure does not recur on repeat testing, the run can be accepted. However, a single control value outside two standard deviations can also be the first indication of a developing problem. If the control value is close to the three standard deviation limit, or if the failure recurs within a short period, the laboratory should investigate further. The investigation should focus on operator technique, reagent handling, and instrument function. ### Shift in Control Values A shift is an abrupt change in the mean of control values, with five to seven consecutive values falling on the same side of the mean. A shift indicates a sudden change in the analytical system, such as a new reagent lot, a new calibrator lot, or a change in instrument settings. The most common cause of a shift is a change in reagent or calibrator lot. When a new lot is introduced, the laboratory should verify that the new lot performs equivalently to the previous lot. This verification may involve testing the new lot alongside the old lot or performing a calibration with the new lot. A shift can also be caused by a change in the control material lot. If the new control lot has a different target value than the previous lot, the control results will shift even though the analytical system is performing correctly. The laboratory should establish new mean and standard deviation values for the new control lot before using it for quality control. ### Trend in Control Values A trend is a gradual change in control values over time, with values steadily increasing or decreasing. A trend indicates a progressive change in the analytical system, such as reagent degradation, lamp aging, or gradual temperature drift. Reagent degradation is a common cause of trends. Most reagents have a limited open stability period, after which their performance gradually deteriorates. If the reagent has been in use for an extended period, the laboratory should replace it with a fresh vial and monitor the control results for improvement. Lamp aging is a common cause of trends in spectrophotometric assays. As the lamp ages, its intensity decreases, which can cause a gradual change in absorbance readings. The laboratory should monitor the lamp usage hours and replace the lamp according to the manufacturer's recommendations. ### Increased Standard Deviation An increase in the standard deviation of control values indicates that the analytical system has become less precise. This pattern is often caused by problems with mixing, pipetting, or sample handling. It can also be caused by a failing instrument component, such as a worn pump or a clogged probe. If the standard deviation increases, the laboratory should review the operator technique and the instrument maintenance records. The laboratory should also check whether the control material was prepared correctly, because improper reconstitution can increase variability. ## Records and Measurements for Effective Troubleshooting ### The Quality Control Log The quality control log is the primary record of control results and the actions taken in response to control failures. Each entry should include the date and time of the test, the control material lot number, the reagent lot number, the calibrator lot number, the instrument identifier, and the operator name. The control result should be recorded along with the mean and standard deviation used for interpretation. The quality control log should also include a section for documenting control failures and the corrective actions taken. This section should describe the problem, the investigation steps, the cause identified, and the action taken to resolve the problem. The log should be reviewed regularly by the laboratory supervisor to identify trends and recurring problems. ### The Instrument Maintenance Log The instrument maintenance log records all preventive maintenance and repairs performed on the instrument. Each entry should include the date of the maintenance, the type of maintenance performed, the name of the person who performed the maintenance, and any parts that were replaced. The log should also include the instrument readings or diagnostics that were recorded during the maintenance. The instrument maintenance log is an essential tool for troubleshooting because it provides a history of the instrument's condition. If a control failure occurs shortly after a maintenance event, the maintenance may have introduced a problem. If the instrument is due for maintenance, the maintenance may resolve the control failure. ### The Reagent and Calibrator Inventory Records The reagent and calibrator inventory records track the receipt, storage, and use of reagents and calibrators. Each record should include the lot number, the expiration date, the date of receipt, and the date the material was opened. The record should also include the storage conditions and any issues observed during use. The inventory records are used to determine whether a control failure is related to a specific reagent or calibrator lot. If multiple control failures occur with the same lot, the laboratory should contact the manufacturer to report the problem and request a replacement. ## Practical Implementation Steps for the Laboratory ### Establish a Written Troubleshooting Procedure Every laboratory should have a written procedure for responding to control failures. The procedure should describe the steps to be taken when a control result fails, the documentation requirements, and the criteria for escalating the problem to a supervisor or the instrument manufacturer. The procedure should be reviewed and updated regularly to reflect changes in the laboratory's methods and instruments. The written procedure ensures that all laboratory staff respond to control failures consistently. It also provides a training tool for new staff and a reference for experienced staff who may encounter an unfamiliar problem. ### Train Staff on Troubleshooting Techniques All laboratory staff who perform testing should be trained on the troubleshooting procedure. The training should cover the interpretation of Westgard rules, the common causes of control failures, and the steps for isolating the cause. The training should also cover the documentation requirements and the importance of accurate record keeping. Training should be documented in the staff training records. Refresher training should be provided periodically, especially when new instruments or methods are introduced. ### Use a Decision Tree for Troubleshooting A decision tree can help laboratory staff work through the troubleshooting process systematically. The decision tree should guide the user through the steps of confirming the failure, reviewing the records, and isolating the cause. The decision tree should be posted near the instrument or included in the laboratory procedure manual. ```mermaid flowchart TD A[Control result fails] --> B{Confirm failure} B -->|Data entry error| C[Correct entry and repeat] B -->|Failure confirmed| D{Review control records} D -->|Control expired or mishandled| E[Prepare fresh control and repeat] D -->|Records normal| F{Review reagent and calibrator} F -->|Reagent or calibrator suspect| G[Replace and recalibrate] F -->|Records normal| H{Review instrument and operator} H -->|Instrument issue| I[Perform maintenance or call service] H -->|Operator issue| J[Retrain and repeat] G --> K{Control in range} I --> K J --> K K -->|Yes| L[Document and release results] K -->|No| M[Escalate to supervisor or manufacturer] ``` ### Monitor Control Performance Over Time The laboratory should monitor control performance over time to identify trends before they become control failures. This monitoring can be done by reviewing the quality control log regularly and by using statistical process control charts. Control charts display control results over time and make it easier to identify shifts and trends. The laboratory should also monitor the frequency of control failures. An increase in the frequency of control failures may indicate a developing problem with the instrument, the reagents, or the control material. The laboratory should investigate the cause of the increase and take corrective action. ## Common Failure Patterns in Troubleshooting ### Assuming the Control Material Is the Problem A common mistake in troubleshooting is assuming that the control material is the problem without verifying the other components of the analytical system. Control material can fail, but it is not the most common cause of control failures. Reagents and calibrators are more likely to cause systematic errors. The troubleshooting process should be systematic and should not skip steps. The laboratory should review the control material records, the reagent records, and the calibrator records before concluding that the control material is the cause. ### Repeating the Control Test Without Investigating Another common mistake is repeating the control test multiple times without investigating the cause of the failure. If the control result is out of range, repeating the test may produce an in-range result by chance, but the underlying problem remains. The laboratory should investigate the cause of the failure before repeating the test. If the repeat test produces an in-range result, the laboratory should still document the original failure and the investigation steps. The laboratory should also monitor subsequent control results to ensure that the problem does not recur. ### Failing to Document the Investigation Failing to document the investigation is a serious error because it leaves the laboratory without a record of the problem and the corrective action. Without documentation, the laboratory cannot demonstrate that it responded appropriately to the control failure. The documentation is also essential for identifying recurring problems and for training new staff. The laboratory should document every control failure and every investigation, even if the cause is not identified. The documentation should include the date, the control results, the investigation steps, and the outcome. ## Limitations of Troubleshooting and When to Escalate ### When the Cause Cannot Be Identified Sometimes the cause of a control failure cannot be identified through the standard troubleshooting process. This situation can occur when the problem is intermittent, when the instrument has an internal fault that is not detected by routine diagnostics, or when the reagent or control material has a subtle defect that is not apparent from the records. When the cause cannot be identified, the laboratory should escalate the problem to the instrument manufacturer or the reagent manufacturer. The manufacturer may have access to additional diagnostic tools and may be able to identify the cause. The laboratory should provide the manufacturer with the documentation from the investigation, including the control results, the reagent and calibrator lot numbers, and the instrument maintenance records. ### When the Problem Recurs If the same control failure pattern recurs after corrective action, the laboratory should escalate the problem. A recurring problem indicates that the corrective action did not address the root cause. The laboratory should review the previous investigation to determine whether any steps were missed or whether the cause was misidentified. The laboratory should also consider whether the problem is related to a specific reagent or control lot. If multiple laboratories using the same lot report similar problems, the manufacturer should be notified. ### When Patient Results May Be Affected If a control failure occurs and patient results have already been reported, the laboratory must assess whether the patient results are affected. The laboratory should review the patient results from the affected run and determine whether any results are likely to be incorrect. If patient results are affected, the laboratory should notify the clinicians who ordered the tests and take corrective action. The decision to release or hold patient results is a clinical decision that should be made in consultation with the laboratory director or the medical director. The laboratory should have a written policy for handling patient results when a control failure occurs. ## Biosafety and Regulatory Context ### Biosafety Considerations in the Clinical Laboratory Clinical laboratories handle biological samples that may contain infectious agents. The Biosafety in Microbiological and Biomedical Laboratories publication from the CDC and NIH provides guidance on the safe handling of biological materials. Laboratories should follow the biosafety level appropriate for the types of samples they handle and should use appropriate personal protective equipment and containment practices. Control materials are typically manufactured to be free of infectious agents, but they should still be handled with the same precautions as patient samples. This approach protects laboratory staff and prevents contamination of the laboratory environment. ### Regulatory Oversight of Laboratory Quality Control Clinical laboratories in the United States are regulated under the Clinical Laboratory Improvement Amendments, which establish quality control requirements for all testing performed in the laboratory. The regulations require laboratories to perform quality control testing, to document the results, and to take corrective action when control results are out of range. The National Institute of Standards and Technology provides the measurement science that underpins laboratory quality control. NIST develops standard reference materials and calibration standards that are used to verify the accuracy of laboratory measurements. Laboratories should use NIST-traceable standards where available to ensure the accuracy of their calibration. ### The Role of the Laboratory Director The laboratory director is responsible for the overall quality of the laboratory's testing. The director should review the quality control records regularly and should be notified of any control failures that cannot be resolved through the standard troubleshooting process. The director should also ensure that the laboratory has adequate resources for quality control, including trained staff, appropriate control materials, and functioning instruments. The director should also ensure that the laboratory has a written quality control procedure and that all staff are trained on the procedure. The director should review the procedure periodically and update it as needed to reflect changes in the laboratory's methods and instruments. ## A Structured Comparison Framework for Troubleshooting QC Failures When a control failure occurs, laboratorians often struggle to determine whether the problem originates from the reagent, calibrator, instrument, control material, or operator. A structured comparison framework provides a practical method for isolating the cause by testing one variable against a known reference. This approach differs from the sequential replacement method because it uses parallel testing to generate comparative data quickly, reducing downtime and preserving patient testing capacity. ### The Paired Comparison Method The paired comparison method involves running the suspect component alongside a known good component under identical conditions. This method works best when the laboratory has access to a second vial of control material, a second reagent lot, or a second instrument. The comparison produces direct evidence about whether the suspect component is responsible for the out-of-range result. For control material, prepare a fresh vial from the same lot and run it alongside the suspect vial. If the fresh vial produces in-range results while the suspect vial produces out-of-range results, the control material is compromised. If both vials produce out-of-range results, the problem lies elsewhere in the analytical system. This comparison takes approximately the same time as a single repeat test but provides more definitive information. For reagent, the comparison requires a second vial from the same lot or a different lot. Run the suspect reagent and the comparison reagent on the same instrument using the same control material. If the comparison reagent produces in-range results, the suspect reagent is the cause. If both reagents produce out-of-range results, the problem is in the instrument, the calibrator, or the control material. For calibrator, the comparison involves running the current calibration curve against a fresh calibration curve prepared from a new vial. This comparison is more time consuming because it requires a full recalibration, but it provides definitive evidence about whether the calibrator is the cause. ### The One-Variable-at-a-Time Sequence The one-variable-at-a-time sequence is the structured alternative to the paired comparison method. This approach changes one component at a time and observes the effect on control results. The sequence should follow a fixed order based on the likelihood of the cause and the ease of replacement. The recommended sequence is control material first, then reagent, then calibrator, then instrument components. Control material is the easiest to replace and the most common source of random error. Reagent is the next most common cause of systematic error. Calibrator replacement requires more time and should be done only after reagent and control material have been ruled out. Instrument service should be the final step because it requires the most time and may require the instrument to be taken out of service. Each step in the sequence should be documented with the control results before and after the change. If the control results return to range after a change, the cause is identified. If the control results remain out of range, the laboratory moves to the next step in the sequence. ### The Two-Instrument Comparison When the laboratory has two instruments that use the same reagent and control lots, the two-instrument comparison provides a powerful diagnostic tool. Run the same control material on both instruments. If one instrument produces in-range results and the other produces out-of-range results, the problem is isolated to the failing instrument. If both instruments produce out-of-range results, the problem is in the shared reagent, calibrator, or control material. This comparison is particularly useful for distinguishing between instrument-specific problems and reagent or control problems. It also provides evidence for the instrument maintenance log and for communication with the instrument manufacturer. The two-instrument comparison requires that both instruments are calibrated and maintained according to the same schedule. If one instrument has a different calibration history, the comparison may not be valid. The laboratory should verify that both instruments are in the same calibration state before performing the comparison. ### The Lot-to-Lot Comparison Record The lot-to-lot comparison record is a systematic method for evaluating new lots of reagent, calibrator, or control material before they are introduced into routine use. This record documents the performance of the new lot against the current lot over a defined number of runs. For reagent, the new lot should be tested alongside the current lot using the same control material. The results should be compared to determine whether the new lot produces equivalent results. The comparison should include at least five control measurements per level, collected across multiple days to account for day-to-day variation. For control material, the new lot should be tested alongside the current lot on the same instrument. The mean and standard deviation of the new lot should be compared to the current lot. If the new lot has a different mean, the laboratory must establish new quality control parameters before using the new lot. The lot-to-lot comparison record should include the lot numbers, the dates of testing, the control results, and the conclusion about whether the new lot is acceptable for use. This record is reviewed during accreditation inspections and provides evidence that the laboratory has verified the performance of new lots before introducing them into routine. ### The Root Cause Analysis Worksheet The root cause analysis worksheet is a structured document that guides the laboratorian through the comparison framework and records the evidence at each step. The worksheet includes sections for the control failure details, the comparison tests performed, the results of each comparison, and the conclusion. The worksheet should be completed for every control failure that requires more than a single repeat test. The worksheet serves as the primary documentation for the investigation and provides a reference for future troubleshooting. The worksheet should be reviewed by the laboratory supervisor before the investigation is closed. The worksheet format ensures that the investigation is systematic and that no steps are skipped. It also provides a training tool for new staff who are learning the troubleshooting process. ### Practical Implementation Steps Implement the comparison framework by first establishing the paired comparison method as the standard approach for control failures that persist after a single repeat test. Train all laboratory staff on the method and the documentation requirements. Post a summary of the comparison sequence near the instrument for quick reference. Second, establish the lot-to-lot comparison record as a standard procedure for all new reagent, calibrator, and control lots. This record should be completed before the new lot is introduced into routine use. The record should be filed with the quality control records and reviewed by the laboratory supervisor. Third, establish the root cause analysis worksheet as the standard documentation for all control failures that require investigation. The worksheet should be completed for every failure that persists after the initial records review and repeat test. The worksheet should be reviewed by the laboratory supervisor and filed in the quality control record. ### Records and Measurements The comparison framework requires specific records to be effective. The paired comparison record should include the date and time of the comparison, the instrument identifier, the control lot number, the reagent lot number, the calibrator lot number, and the results of each comparison test. The record should also include the conclusion and the corrective action taken. The lot-to-lot comparison record should include the old lot and new lot numbers, the dates of testing, the control results for each lot, and the calculated mean and standard deviation for each lot. The record should include the conclusion about whether the new lot is acceptable for use. The root cause analysis worksheet should include the problem description, the comparison tests performed, the results of each test, the cause identified, and the corrective action taken. The worksheet should also include the date and time of the investigation and the names of the staff involved. ### Common Failure Patterns in the Comparison Framework A common failure pattern is skipping the comparison step and moving directly to replacement. This pattern wastes time and resources because the laboratory may replace a component that is not the cause. The comparison framework should be followed in the fixed sequence to avoid this error. Another common failure pattern is performing the comparison without documenting the results. The comparison is only useful if the results are recorded and reviewed. The laboratory should document every comparison test, even if the results are inconclusive. A third common failure pattern is using the comparison framework without verifying that the comparison components are in the same state. For example, if the comparison reagent has been opened for a different length of time than the suspect reagent, the comparison may not be valid. The laboratory should verify that the comparison components are in the same state before performing the comparison. ### When to Escalate The comparison framework should be escalated to the laboratory supervisor when the cause cannot be identified after completing the full comparison sequence. The supervisor should review the comparison records and determine whether additional testing is needed. If the supervisor cannot identify the cause, the problem should be escalated to the instrument manufacturer or the reagent manufacturer. The comparison framework should also be escalated when the comparison results are contradictory. For example, if the paired comparison indicates that the reagent is the cause but the lot-to-lot comparison indicates that the reagent is acceptable, the laboratory should escalate the problem to the manufacturer for further investigation. The comparison framework should be escalated when the problem recurs after corrective action. A recurring problem indicates that the comparison framework did not identify the root cause. The laboratory should review the comparison records and the worksheet to determine whether any steps were missed or whether the cause was misidentified. ## Frequently Asked Questions ### What is the first step when a QC result fails? Confirm that the failure is real by checking the control material identification, the recorded result, and the data entry. A data entry error or a misidentified control can produce a false failure that does not require a full investigation. ### How do I know if a control failure is random or systematic? A single control value outside two standard deviations with the other control level in range is likely random. A shift of five to seven consecutive values on one side of the mean or a trend of steadily increasing or decreasing values indicates a systematic problem. ### Should I repeat the control test before investigating the cause? Repeat the control test after completing the initial records review, but do not repeat the test repeatedly without investigating. If the repeat result is in range, the original failure may have been random. If the repeat result is out of range, continue the investigation. ### What is the most common cause of a shift in control values? A change in reagent lot or calibrator lot is the most common cause of a shift. When a new lot is introduced, the laboratory should verify that the new lot performs equivalently to the previous lot and should recalibrate if required. ### What is the most common cause of a trend in control values? Reagent degradation is the most common cause of a trend. Most reagents have a limited open stability period, after which their performance gradually deteriorates. Lamp aging and gradual temperature drift can also cause trends. ### When should I escalate a control failure to the instrument manufacturer? Escalate when the cause cannot be identified through the standard troubleshooting process, when the problem recurs after corrective action, or when the instrument diagnostics indicate an internal fault. Provide the manufacturer with the documentation from the investigation. ### Can patient results be reported if a control fails? Patient results should be held until the cause of the control failure is identified and the system is verified. If patient results were already reported, the laboratory must assess whether the results are affected and notify the clinicians if necessary. ### How long should I keep quality control records? Quality control records should be kept according to the laboratory's regulatory requirements and accreditation standards. The records should be retained for a period that allows review during inspections and for the identification of long-term trends in control performance. ## Using the Evidence | Source | Best use in this topic | Important limitation | |---|---|---| | [Molecular Biology and Laboratory Methods](https://www.ncbi.nlm.nih.gov/books) | official guidance | Check the linked page for current local requirements | | [Biosafety in Microbiological and Biomedical Laboratories](https://www.cdc.gov/labs/bmbl/index.html) | official guidance | Check the linked page for current local requirements | | [NIH Guidelines for Recombinant or Synthetic Nucleic Acid Molecules](https://osp.od.nih.gov/policies/biosafety-and-biosecurity-policy/nih-guidelines-for-research-involving-recombinant-or-synthetic-nucleic-acid-molecules) | official guidance | Check the linked page for current local requirements | ## Related Diagnostic Guides - [Method Validation in Clinical Laboratories: A Practical Protocol](/knowledge/diagnostics/emerging-tech/method-validation-in-clinical-laboratories-a-practical-protocol) - [Quality Control in Clinical Chemistry: Best Practices and Troubleshooting](/knowledge/diagnostics/clinical-pathology/quality-control-in-clinical-chemistry-best-practices-and-troubleshooting) - [ELISA Troubleshooting: A Systematic Approach to Common Assay Problems](/knowledge/diagnostics/serology-immunology/elisa-troubleshooting-a-systematic-approach-to-common-assay-problems) ## References and Further Reading - [Molecular Biology and Laboratory Methods](https://www.ncbi.nlm.nih.gov/books). National Library of Medicine. - [Biosafety in Microbiological and Biomedical Laboratories](https://www.cdc.gov/labs/bmbl/index.html). CDC and NIH. - [NIH Guidelines for Recombinant or Synthetic Nucleic Acid Molecules](https://osp.od.nih.gov/policies/biosafety-and-biosecurity-policy/nih-guidelines-for-research-involving-recombinant-or-synthetic-nucleic-acid-molecules). National Institutes of Health. - [Addgene Protocols](https://www.addgene.org/protocols). Addgene. - [MIQE Guidelines](https://academic.oup.com/clinchem/article/55/4/611/5631762). Clinical Chemistry. - [NIST Laboratory Programs](https://www.nist.gov/laboratories). National Institute of Standards and Technology. - [Laboratory Biosafety Manual](https://www.who.int/publications/i/item/9789240011311). World Health Organization. - [NCBI Literature Resources](https://www.ncbi.nlm.nih.gov/). National Center for Biotechnology Information. - [MAGNETO-THERAPY IN PHYSIOTHERAPY UNITS: INTRODUCTION OF QUALITY CONTROL PROCEDURE DUE TO LACK OF MAINTENANCE.](https://pubmed.ncbi.nlm.nih.gov/31329986). Radiation protection dosimetry, 2019. - [Repeat patient testing-quality control compared to commercial quality control material for the Sysmex XT-2000iV hematology analyzer in a multi-site veterinary laboratory.](https://pubmed.ncbi.nlm.nih.gov/38356015). Veterinary clinical pathology, 2024. - [What We Should Consider in Point of Care Blood Glucose Test, Current Quality Management Status of a Single Institution.](https://pubmed.ncbi.nlm.nih.gov/33806620). Medicina (Kaunas, Lithuania), 2021. > This article is educational and does not replace validated laboratory procedures, institutional biosafety review, manufacturer instructions, or professional interpretation.