How to Determine Risk-Based QC Frequency

By Dr. Zubair Khalid, DVM, MS, PhD · 2026-08-27

Quick Answer

Risk-based QC frequency uses patient harm potential and assay stability to set control schedules instead of fixed daily rules.
Start by scoring each assay for clinical impact, error detection capability, and historical failure rate to assign a QC tier.
CLSI EP23 provides the framework, but your laboratory must document the rationale for each QC frequency decision.

Understanding Risk-Based Quality Control

Quality control in the clinical laboratory has traditionally followed fixed schedules, often running QC samples at the start of each day or with each batch of patient samples. This approach treats all assays as equal in risk, which does not reflect the actual clinical consequences of an undetected error. A glucose result used to adjust insulin therapy carries different risk than a screening test with low clinical actionability. Risk-based QC frequency aligns the intensity of quality monitoring with the potential harm to patients from incorrect results.

The Clinical and Laboratory Standards Institute document EP23, Laboratory Quality Control Based on Risk Management, provides the framework for this approach. instead of prescribing a universal QC frequency, EP23 asks laboratories to identify failure modes, estimate the probability of harm, and design a QC plan that mitigates those risks. The resulting QC frequency is a documented decision based on assay characteristics, patient population, and laboratory workflow.

This approach does not eliminate the need for daily QC in all situations. It replaces an arbitrary schedule with a defensible one. The laboratory director, quality manager, and testing personnel must agree on the risk categories and the QC frequency assigned to each. The decision must be recorded and reviewed periodically, especially when the assay, instrument, or patient population changes.

Core Principles of Risk-Based QC

Risk Assessment as the Foundation

Risk assessment begins with a systematic review of each assay in the laboratory. The review considers what can go wrong, how likely the failure is, and what the consequence would be for a patient. This process is similar to the risk assessment used in biosafety, where the potential hazard of an agent is weighed against the containment and work practices in place. The CDC and NIH Biosafety in Microbiological and Biomedical Laboratories describes this approach for infectious agents, and the same logic applies to assay risk. The hazard is the erroneous result, the containment is the QC system, and the work practice is the frequency of QC testing.

For each assay, the laboratory should identify failure modes. These include reagent degradation, calibration drift, sample carryover, operator error, and instrument malfunction. Each failure mode has a probability and a consequence. A failure mode with a low probability but a high consequence, such as a false negative for a critical infection marker, may warrant more frequent QC than a failure mode with a high probability but a low consequence.

Patient Risk Categories

Patient risk is not uniform across all tests. A test used to monitor a chronic condition with a wide therapeutic range carries a different risk than a test used to diagnose a life-threatening condition. The laboratory must consider how the result is used in clinical decision making. Tests that trigger immediate treatment decisions, such as potassium for cardiac patients or glucose for insulin dosing, require more frequent QC than tests that are part of a screening panel with follow-up confirmation.

The patient population also matters. A test performed on inpatients in an intensive care unit carries a different risk profile than the same test performed on outpatients in a routine screening clinic. The laboratory should document the patient population served by each assay and use that information to assign the QC frequency.

Statistical Quality Control

Statistical QC uses control materials with known values to detect systematic and random errors. The laboratory runs these materials and compares the results to a defined range. The frequency of running these materials determines how quickly an error is detected. More frequent QC detects errors sooner but increases cost and labor. Less frequent QC reduces cost but allows errors to persist longer.

The statistical design of the QC system includes the number of control measurements per run, the control limits, and the decision rules. The laboratory must choose a design that detects the medically significant error with a high probability. This is the error detection capability of the QC system. The laboratory must also consider the false rejection rate, which is the probability that the QC system flags a problem when the assay is actually performing correctly.

The CLSI EP23 Framework

Risk Management Process

CLSI EP23 describes a risk management process that includes risk identification, risk analysis, risk evaluation, risk control, and risk monitoring. The laboratory applies this process to each assay to develop a QC plan. The plan specifies the number of QC levels, the frequency of QC, the rules for accepting or rejecting runs, and the actions to take when QC fails.

The risk identification step lists the potential sources of error. The risk analysis step estimates the probability and severity of each error. The risk evaluation step determines whether the risk is acceptable or requires additional control. The risk control step selects the QC measures, including frequency. The risk monitoring step reviews the QC results over time to confirm that the plan is working.

This process is documented in a QC plan for each assay. The plan is a living document that changes when the assay changes. The laboratory must review the plan at least annually and after any significant change to the assay, instrument, reagent, or patient population.

Risk Scoring Systems

Several risk scoring systems have been developed to make the risk assessment more objective. These systems assign points to different risk factors and sum the points to determine the QC frequency. The scoring system is not a substitute for professional judgment, but it provides a structured way to compare assays and justify the QC frequency.

A common scoring system considers the clinical consequence of an error, the probability of an error, and the detectability of the error. Each factor is scored on a scale, and the total score determines the QC tier. The laboratory must define the scoring criteria and the QC frequency for each tier. The scoring system must be documented and applied consistently.

The risk score is not a fixed number. It changes when the assay changes. A new reagent lot with a different stability profile may change the probability of an error. A new instrument with a different calibration schedule may change the detectability of an error. The laboratory must recalculate the risk score when these changes occur.

Practical Implementation Steps

Step 1: Inventory Your Assays

Create a list of every assay performed in your laboratory. Include the assay name, the instrument, the reagent, the sample type, and the clinical use. This inventory is the basis for the risk assessment. The inventory should be complete and current. A missing assay is a gap in the QC plan.

Step 2: Assign Risk Categories

For each assay, assign a risk category based on the clinical consequence of an incorrect result. Use a scale that is meaningful for your laboratory. A three-tier scale is common: high risk, medium risk, and low risk. High risk assays are those where an incorrect result could lead to immediate patient harm. Medium risk assays are those where an incorrect result could lead to delayed or inappropriate treatment. Low risk assays are those where an incorrect result is unlikely to cause harm.

The risk category is a professional judgment. It should be made by the laboratory director in consultation with the clinical staff. The rationale for each category must be documented.

Step 3: Determine the QC Frequency

For each risk category, determine the QC frequency. The frequency is the number of times QC materials are run in a given period. The frequency can be expressed as per run, per day, per week, or per batch. The frequency must be sufficient to detect the error rate that would cause harm.

The QC frequency is not a universal number. It depends on the assay, the instrument, the reagent, and the patient population. A high risk assay on an instrument with a history of failures may require QC with every run. A low risk assay on a stable instrument may require QC once per week.

Step 4: Document the QC Plan

Write a QC plan for each assay. The plan should include the risk category, the QC frequency, the number of QC levels, the control rules, and the actions to take when QC fails. The plan should be reviewed and approved by the laboratory director. The plan should be available to all laboratory staff.

Step 5: Monitor and Review

Monitor the QC results and the assay performance. Review the QC plan at least annually. Review the plan more frequently if the assay, instrument, reagent, or patient population changes. The review should confirm that the QC frequency is still appropriate and that the QC plan is being followed.

At a Glance

Risk Category	Example Assay	QC Frequency	Rationale
High	Glucose for insulin dosing	Every run	An incorrect result can cause immediate patient harm
Medium	Creatinine for renal function	Once per day	An incorrect result can cause delayed treatment
Low	Screening panel for a chronic condition	Once per week	An incorrect result is unlikely to cause immediate harm

Practical Assessment Steps

Conducting the Risk Assessment

The risk assessment is a team activity. The team should include the laboratory director, the quality manager, the technical supervisor, and a representative from the clinical staff. The team should meet to review each assay and assign the risk category. The meeting should be documented with the date, the attendees, and the decisions.

The risk assessment should use a structured approach. The team should identify the failure modes for each assay. The team should estimate the probability of each failure mode and the severity of the consequence. The team should then assign the risk category and the QC frequency.

The risk assessment is not a one-time event. The team should review the risk assessment when the assay changes. The team should also review the risk assessment when the QC results show a pattern of errors.

Using Risk Scores

A risk score can make the risk assessment more objective. The score is a number that reflects the risk of the assay. The score is calculated by adding the scores for each risk factor. The score is then used to assign the QC frequency.

The risk factors and the scoring scale must be defined by the laboratory. The scoring scale should be simple and reproducible. The scoring should be applied consistently by all members of the team.

The risk score is a tool, not a replacement for judgment. The team should review the score and confirm that it reflects the clinical reality. If the score does not match the clinical reality, the team should adjust the score or the QC frequency.

Setting the QC Frequency

The QC frequency is the number of times QC runs in a given period. The frequency is set by the risk category and the risk score. The frequency should be documented in the QC plan.

The QC frequency is not a fixed number. The frequency should be reviewed and adjusted when the assay changes. The frequency should also be reviewed when the QC results show a problem.

Records and Measurements

QC Records

The laboratory must maintain records of all QC results. The records should include the date and time of the QC run, the QC material lot, the instrument, the operator, and the results. The records should be reviewed by the laboratory supervisor. The records should be retained according to the laboratory policy.

The QC records are used to monitor the assay performance. The records are also used to identify trends and shifts in the assay. The records are the basis for the review of the QC plan.

Risk Assessment Records

The laboratory must maintain records of the risk assessment. The records should include the date of the assessment, the team members, the risk categories, the risk scores, and the QC frequency. The records should be reviewed and updated when the assay changes.

The risk assessment records are used to justify the QC frequency. The records are also used to demonstrate compliance with the CLSI EP023 framework. The records should be available for inspection by the laboratory director and the accrediting body.

Measurement of QC Performance

The laboratory should measure the performance of the QC system. The performance is measured by the error detection rate and the false rejection rate. The error detection rate is the probability that the QC system detects an error. The false rejection rate is the probability that the QC system rejects a run when the assay is performing correctly.

The laboratory should calculate these rates for each assay. The rates should be used to evaluate the QC plan. If the error detection rate is too low, the QC frequency should be increased. If the false rejection rate is too high, the QC rules should be adjusted.

Common Failure Patterns

Fixed Frequency Without Risk Assessment

A common failure is to use a fixed QC frequency for all assays without a risk assessment. This approach does not reflect the clinical risk of the assay. A high risk assay may be under-monitored, and a low risk assay may be over-monitored. The laboratory should replace the fixed frequency with a risk-based frequency.

Risk Assessment Not Updated

A risk assessment is a snapshot of the assay at a point in time. The risk assessment becomes outdated when the assay changes. A common failure is to continue using the old risk assessment after a reagent change or an instrument change. The laboratory should update the risk assessment when the assay changes.

QC Plan Not Followed

A QC plan is only effective if the laboratory staff follows it. A common failure is to skip QC runs or to run QC less frequently than the plan requires. The laboratory should train the staff on the QC plan and monitor the compliance with the plan.

Risk Score Not Validated

A risk score is a tool that must be validated. A common failure is to use a risk score without checking that it matches the clinical reality. The laboratory should validate the risk score by comparing the score to the actual assay performance.

Limitations of Risk-Based QC

Subjectivity in Risk Assessment

The risk assessment is a professional judgment. The risk categories and the risk scores are based on the experience and the knowledge of the team. The risk assessment can vary between laboratories. The laboratory should document the rationale for the risk assessment to ensure consistency.

Statistical Assumptions

The statistical QC design is based on assumptions about the assay performance. The assumptions may not hold for all assays. The laboratory should verify the assumptions by monitoring the QC results and the assay performance.

Regulatory Requirements

The risk-based QC approach is a framework, not a regulation. The laboratory must comply with the regulatory requirements of the accrediting agency. The regulatory requirements may be more stringent than the risk-based approach. The laboratory should check the regulatory requirements before implementing the risk-based QC.

Biosafety and Safety Context

The risk-based QC approach is a quality management tool. The approach is not a biosafety tool. The laboratory must still follow the biosafety principles for the handling of samples and reagents. The CDC and NIH Biosafety in Microbiological and Biomedical Laboratories provides the biosafety principles for the laboratory. The laboratory should follow the biosafety principles in addition to the QC plan.

The risk assessment for QC is separate from the risk assessment for biosafety. The QC risk assessment focuses on the assay error. The biosafety risk assessment focuses on the infectious agent. The laboratory should conduct both risk assessments and document both.

Professional Escalation Criteria

The laboratory should escalate the QC issue to the laboratory director when the QC results show a problem. The escalation criteria include the following:

The QC results are outside the acceptable range.
The QC results show a trend or a shift.
The QC results show a high false rejection rate.
The QC plan is not detecting the error rate.
The assay performance is not meeting the clinical requirements.

The laboratory director should review the QC issue and take the appropriate action. The action may include the investigation of the assay, the adjustment of the QC plan, or the suspension of the assay.

Building a Defensible QC Frequency Decision Record

A risk-based QC frequency decision is only as strong as the documentation that supports it. An accreditor, inspector, or laboratory director reviewing your QC plan will ask three questions: What did you decide, why did you decide it, and what evidence supports that decision? Without a structured record system, the answers become vague references to professional judgment. This section provides a practical decision framework, a record system, and a troubleshooting method that you can implement directly in your laboratory.

The QC Frequency Decision Matrix

The decision matrix is the core tool that translates risk assessment into a concrete QC frequency. It is a table that your laboratory team completes for each assay. The matrix forces the team to consider the same factors for every assay, which reduces the subjectivity that can creep into risk-based decisions.

The matrix has five columns: assay name, clinical consequence score, error probability score, detection capability score, and assigned QC frequency. The clinical consequence score reflects what happens to a patient if the result is wrong. The error probability score reflects how likely the assay is to fail based on historical performance and reagent or instrument stability. The detection capability score reflects how well the current QC rules and control materials catch an error when it occurs.

Each score uses a simple three point scale. A score of one means low, two means medium, and three means high. The team adds the three scores to get a total between three and nine. The total determines the QC frequency tier. A total of three to four points assigns the assay to a low monitoring tier. A total of five to seven points assigns the assay to a standard monitoring tier. A total of eight to nine points assigns the assay to an intensive monitoring tier.

The QC frequency for each tier is not fixed by any external regulation. Your laboratory must define the frequency for each tier based on your workflow, instrument stability, and staffing. A common starting point is low monitoring with QC once per week, standard monitoring with QC once per day, and intensive monitoring with QC with every run or every batch. The starting point is a baseline that you adjust based on the evidence you collect.

The matrix is not a substitute for judgment. It is a structured way to apply judgment consistently. The team should review the total score and ask whether it matches the clinical reality. If a glucose assay used for insulin dosing scores a four because the instrument has been stable for years, the team should still consider whether the clinical consequence alone justifies more frequent QC. The matrix is a starting point for discussion, not an automated answer.

How to Score Each Risk Factor

The clinical consequence score is the most important factor in the matrix. It reflects the potential harm to a patient from an incorrect result. The team should consider how the result is used in clinical decision making. A result that triggers an immediate treatment decision, such as insulin dosing or potassium replacement, receives a score of three. A result that influences a treatment decision but does not trigger immediate action, such as a creatinine used to adjust a medication dose, receives a score of two. A result that is part of a screening panel with follow-up confirmation, such as a screening test for a chronic condition, receives a score of one.

The error probability score reflects the likelihood that the assay produces an incorrect result. The team should use historical QC data, reagent stability data, and instrument performance records. An assay with a history of QC failures, frequent reagent lot changes, or an instrument with a high rate of malfunctions receives a score of three. An assay with occasional QC failures or a moderate rate of reagent changes receives a score of two. An assay with a stable history and no recent failures receives a score of one.

The detection probability score reflects how well the current QC system can catch an error. This factor depends on the number of control levels, the control rules, and the sensitivity of the control material. An assay where the QC system can detect a small error, such as a shift of one standard deviation, receives a score of three. An assay where the QC system can detect a moderate error, such as a shift of two standard deviations, receives a score of two. An assay where the QC system can only detect a large error, such as a shift of three standard deviations, receives a score of one.

The detection probability score is the most technical factor in the matrix. The team should consult the statistical quality control literature and the instrument manufacturer recommendations. The National Institute of Standards and Technology provides measurement science resources that can help the team understand the statistical basis for error detection. The team should not guess at this score. It should be based on the actual control rules and the observed performance of the control material.

The QC Frequency Decision Record

The decision record is the written output of the matrix. It is a one page document for each assay that captures the decision and the rationale. The record should include the assay name, the date of the decision, the team members who participated, the scores for each risk factor, the total score, the assigned QC frequency, and the rationale for any override.

The record should also include the evidence that supports the decision. This evidence includes the historical QC data, the instrument performance records, the reagent stability data, and the clinical use of the test. The evidence does not need to be attached to the record, but the record should reference where the evidence is stored. An accreditor should be able to follow the reference and find the evidence.

The decision record is a living document. It is reviewed at least annually and updated when the assay changes. A new reagent lot with a different stability profile may change the error probability score. A new instrument with a different calibration schedule may change the detection probability score. A change in the patient population may change the clinical consequence score. Each change triggers a new decision record.

The decision record is also the basis for the QC plan. The QC plan states the frequency, the number of control levels, the control rules, and the actions to take when QC fails. The decision record explains why the QC plan is set the way it is. The two documents work together. The decision record is the rationale, and the QC plan is the instruction.

A Worked Example of the Decision Matrix

Consider a hypothetical laboratory that performs a glucose assay for insulin dosing and a screening assay for a chronic condition. The team completes the decision matrix for each assay.

For the glucose assay, the clinical consequence score is three because an incorrect result can lead to immediate patient harm. The error probability score is two because the instrument has had two QC failures in the past year. The detection probability score is three because the QC system uses two control levels and a multi-rule approach that can detect a shift of one standard deviation. The total score is eight, which assigns the assay to the intensive monitoring tier. The QC frequency is every run.

For the screening assay, the clinical consequence score is one because an incorrect result is unlikely to cause immediate harm and the result is confirmed by a follow-up test. The error probability score is one because the instrument has had no failures in the past year. The detection probability score is two because the QC system uses one control level and can detect a shift of two standard deviations. The total score is four, which assigns the assay to the low monitoring tier. The QC frequency is once per week.

The team reviews the scores and confirms that they match the clinical reality. The glucose assay is high risk and requires intensive monitoring. The screening assay is low risk and can tolerate less frequent monitoring. The team signs the decision records and files them with the QC plan.

How to Use Historical QC Data to Set the Error Probability Score

The error probability score should not be a guess. It should be based on the historical QC data that the laboratory has already collected. The laboratory should review the QC records for the past six to twelve months for each assay. The review should count the number of QC failures, the number of times the QC was repeated, and the number of times the assay was suspended.

The review should also look for trends and shifts in the QC data. A trend is a gradual change in the QC values over time. A shift is a sudden change in the QC values. Both can indicate a problem with the assay that is not yet a failure. The team should consider these trends and shifts when assigning the error probability score.

The National Institute of Standards and Technology provides resources on measurement science and quality that can help the laboratory understand how to analyze the QC data. The laboratory should use these resources to build a systematic approach to reviewing the QC data. The review should be documented and the findings should be included in the decision record.

The error probability score is not a permanent number. It changes when the QC data changes. If the assay has a new failure, the score should be reviewed. If the assay has a period of stability, the score may be reduced. The laboratory should review the error probability score at least quarterly, or more frequently if the assay is unstable.

How to Use the QC Data to Validate the Detection Probability Score

The detection probability score is the most difficult factor to estimate. It requires an understanding of the statistical power of the QC system. The laboratory can validate the detection probability score by reviewing the QC data for the assay. The review should look at the control values and the control rules.

The laboratory should calculate the standard deviation of the control values for each control level. The standard deviation is a measure of the variability of the control values. The laboratory should then compare the standard deviation to the control limits. The control limits are typically set at two or three standard deviations from the mean. The laboratory should verify that the control limits are appropriate for the assay.

The laboratory should also review the control rules. The control rules define when a run is rejected. A common rule is the 1-2s rule, which rejects a run when one control value exceeds two standard deviations from the mean. Another common rule is the 2-2s rule, which rejects a run when two consecutive control values exceed two standard deviations on the same side of the mean. The laboratory should verify that the control rules are appropriate for the assay.

The MIQE guidelines provide a framework for reporting and interpreting quantitative PCR data. The guidelines emphasize the importance of controls and the need for transparency in reporting. The same principles apply to the QC system. The laboratory should document the control rules and the standard deviation for each assay. The documentation should be available for review.

The detection probability score is not a fixed number. It changes when the control rules or the control material changes. The laboratory should review the detection probability score when the control rules are changed or when a new control material is introduced.

Common Failure Patterns in the Decision Process

The decision matrix is a tool, and like any tool, it can be used incorrectly. The most common failure pattern is to assign the same score to every assay. This happens when the team does not take the time to consider the specific characteristics of each assay. The result is a matrix that does not differentiate between assays, and the QC frequency is the same for all assays. The laboratory should review the matrix to ensure that the scores vary across the assays.

Another common failure pattern is to assign a high clinical consequence score to every assay. This happens when the team is overly cautious and does not consider the actual clinical use of the result. The result is that every assay is assigned to the intensive monitoring tier, and the laboratory is running QC more frequently than necessary. The laboratory should review the clinical consequence scores and ensure that they reflect the actual clinical use of the result.

A third common failure pattern is to ignore the historical QC data. The team assigns the error probability score based on a general impression of the assay, instead of the actual QC records. The result is a score that does not reflect the actual performance of the assay. The laboratory should review the QC data before assigning the error probability score.

A fourth common failure pattern is to use the decision matrix as a one-time exercise. The team completes the matrix, files the record, and never reviews it again. The matrix becomes outdated when the assay changes. The laboratory should review the matrix at least annually and update it whenever the assay changes.

How to Handle Overrides and Exceptions

The decision matrix is a structured tool, but it is not a rigid rule. The team may override the matrix when the clinical reality requires it. The override should be documented in the decision record. The override should state the reason for the override and the evidence that supports it.

A common override is to increase the QC frequency for an assay that has a low total score but a high clinical consequence. The team may decide that the clinical consequence is so high that the assay should be monitored more frequently than the matrix suggests. The override should be documented and the rationale should be clear.

Another common override is to decrease the QC frequency for an assay that has a high total score but a low clinical consequence. The team may decide that the assay is so stable that the QC frequency can be reduced. The override should be documented and the rationale should be clear.

The override is not a way to avoid the decision matrix. It is a way to adjust the decision matrix when the clinical reality requires it. The override should be rare and should be justified by the evidence. The laboratory director should approve all overrides.

Records and Measurements for the Decision Matrix

The decision matrix is a record that must be maintained. The record should include the assay name, the date of the decision, the team members, the scores for each risk factor, the total score, the assigned QC frequency, and the rationale for any override. The record should be signed by the laboratory director.

The record should be stored in a location that is accessible to the laboratory staff. The record should be available for review by the accrediting body. The record should be retained according to the laboratory policy.

The laboratory should also maintain the evidence that supports the decision. The evidence includes the historical QC data, the instrument performance records, the reagent stability data, and the clinical use of the assay. The evidence should be stored in a location that is accessible to the laboratory staff.

The laboratory should measure the performance of the decision matrix. The performance is measured by the error detection rate and the false rejection rate. The error detection rate is the probability that the QC system detects an error. The false rejection rate is the probability that the QC system rejects a run when the assay is performing correctly. The laboratory should calculate these rates for each assay and use them to evaluate the decision matrix.

Professional Escalation Criteria for the Decision Matrix

The decision matrix is a tool that should be reviewed when the QC results show a problem. The laboratory should escalate the issue to the laboratory director when the QC results show a pattern of errors. The escalation criteria include the following:

The QC results show a trend or a shift that is not detected by the current QC system.
The QC results show a high false rejection rate.
The QC results show a high error detection rate that is not consistent with the decision matrix.
The assay performance is not meeting the clinical requirements.

The laboratory director should review the decision matrix and take the appropriate action. The action may include the investigation of the assay, the adjustment of the decision matrix, or the suspension of the assay. The action should be documented in the decision record.

Biosafety and Safety Context for the Decision Matrix

The decision matrix is a quality management tool. It is not a biosafety tool. The laboratory must still follow the biosafety principles for the handling of samples and reagents. The CDC and NIH Biosafety in Microbiological and Biomedical Laboratories provides the biosafety principles for the laboratory. The laboratory should follow the biosafety principles in addition to the decision matrix.

The decision matrix for QC is separate from the risk assessment for biosafety. The QC decision matrix focuses on the assay error. The biosafety risk assessment focuses on the infectious agent. The laboratory should conduct both risk assessments and document both.

The decision matrix should not be used to justify a reduction in biosafety practices. The QC frequency is a quality management decision. The biosafety practices are a safety decision. The two decisions are independent. The laboratory should not reduce biosafety practices because the QC frequency is low.

Practical Implementation Steps for the Decision Matrix

The decision matrix is a practical tool that can be implemented in a few steps. The laboratory should follow these steps to implement the decision matrix:

Create a list of every assay performed in the laboratory.
For each assay, assign the clinical consequence score based on the clinical use of the result.
For each assay, assign the error probability score based on the historical QC data.
For each assay, assign the detection probability score based on the control system.
Add the three scores to get the total score.
Assign the QC frequency based on the total score.
Document the decision in the decision record.
Review the decision at least annually and update it when the assay changes.

The decision matrix is a tool that can be used by any laboratory. The tool is simple enough to be used by a small laboratory and flexible enough to be used by a large laboratory. The tool is a practical way to implement the risk-based QC approach described in CLSI EP23.

Frequently Asked Questions

What is the difference between risk-based QC and traditional QC?

Traditional QC uses a fixed schedule, such as daily or per batch, for all assays. Risk-based QC uses a schedule that is based on the clinical risk of the assay. The risk-based schedule is more frequent for high risk assays and less frequent for low risk assays.

How do I determine the risk category for an assay?

The risk category is determined by the clinical consequence of an incorrect result. The laboratory team should consider the patient population, the clinical use of the result, and the potential for harm. The team should document the rationale for the risk category.

What is a risk score and how do I use it?

A risk score is a number that reflects the risk of the assay. The score is calculated from the risk factors, such as the clinical risk, the probability of error, and the detectability of the error. The score is used to determine the QC frequency.

How often should I review the QC plan?

The QC plan should be reviewed at least annually. The plan should be reviewed more frequently when the assay changes, such as a reagent change, an instrument change, or a change in the patient population.

What should I do when the QC fails?

When the QC fails, the laboratory should stop the assay, investigate the cause, and take the corrective action. The laboratory should document the failure and the corrective action. The laboratory should not release the patient results until the QC is acceptable.

Is risk-based QC accepted by the regulatory agencies?

The risk-based QC approach is described in the CLSI EP023 document. The regulatory agencies may accept the risk-based approach if the laboratory can demonstrate the rationale. The laboratory should check the regulatory requirements of the accrediting agency.

What is the role of the laboratory director in risk-based QC?

The laboratory director is responsible for the QC plan. The director approves the risk assessment, the QC frequency, and the QC plan. The director reviews the QC results and the QC plan on a regular basis.

How do I document the risk assessment?

The risk assessment should be documented in a written report. The report should include the date, the team members, the assay, the risk category, the risk score, and the QC frequency. The report should be signed by the laboratory director.

Using the Evidence

Source	Best use in this topic	Important limitation
Molecular Biology and Laboratory Methods	official guidance	Check the linked page for current local requirements
Biosafety in Microbiological and Biomedical Laboratories	official guidance	Check the linked page for current local requirements
NIH Guidelines for Recombinant or Synthetic Nucleic Acid Molecules	official guidance	Check the linked page for current local requirements

Related Diagnostic Guides

References and Further Reading

Molecular Biology and Laboratory Methods. National Library of Medicine.
Biosafety in Microbiological and Biomedical Laboratories. CDC and NIH.
NIH Guidelines for Recombinant or Synthetic Nucleic Acid Molecules. National Institutes of Health.
Addgene Protocols. Addgene.
MIQE Guidelines. Clinical Chemistry.
NIST Laboratory Programs. National Institute of Standards and Technology.
Laboratory Biosafety Manual. World Health Organization.
NCBI Literature Resources. National Center for Biotechnology Information.
Internal Quality Controls in the Medical Laboratory: A Narrative Review of the Basic Principles of an Appropriate Quality Control Plan.. 2024.
EFLM Working Group Accreditation and ISO/CEN standards on dealing with ISO 15189 demands for retention of documents and examination objects.. 2024.
Six Sigma performance of quality indicators in total testing process of point-of-care glucose measurement: A two-year review.. 2021.

This article is educational and does not replace validated laboratory procedures, institutional biosafety review, manufacturer instructions, or professional interpretation.