The importance of quality control in laboratories

• Quality control in laboratories ensures high diagnostic accuracy, consistency, and patient safety.
• Following QC procedures and building a robust laboratory quality management system (LQMS) framework is critical for achieving reliable lab results.
• Inadequate QC can lead to potential misdiagnoses, delayed treatments, and compromised patient safety.
• Digital solutions streamline QC processes by automating key tasks, improving data integration, and providing real-time insights into laboratory performance.
• Adopting automated QC tools enhances efficiency, reduces manual errors, and ensures compliance with accreditation standards, ultimately impacting patient care and lab operations.

While no good laboratory ever sets out to make mistakes, it is impossible to plan for every eventuality. That’s why maintaining quality control in a laboratory setting is imperative. Not only does it help ensure the accuracy, reliability, and consistency of diagnostic test results but it also safeguards patient health.^1,2

So how exactly do you go about ensuring effective quality control in a lab-based environment? And how can you recognize which processes you need to hone and optimize to maximize the potential benefits that maintaining effective quality control can offer? Let’s take a closer look.

Quality control in the lab refers to all the healthcare measures that are put in place to identify and resolve issues with lab results.^1,2 It involves regularly incorporating systems that improve the accuracy, reliability, and timeliness of results, to ultimately support the overall goal of enhancing clinical decision-making.^1-3

Quality control procedures are critical to managing the overall quality of patient sample results and identifying any errors before they potentially impact patient care.³ This, in turn, helps to build trust among lab leaders, healthcare professionals, and patients alike.

As laboratory operations grow more complex and data-intensive, digital tools are becoming essential to support the accuracy and reliability of test results. Modern, web-based quality management solutions use peer group comparisons and statistical analysis to evaluate quality control (QC) data, helping laboratories understand how their performance compares within a network, across a country, or around the world.

By automating critical metrics—such as Six Sigma calculations and measurement of uncertainty—these solutions provide real-time insights that support compliance with ISO 15189 requirements, strengthen accreditation efforts, and give laboratories greater confidence in their results.⁴

One of the most essential aspects of laboratory operations is internal quality control (IQC). As defined by the World Health Organization, this involves using “a set of procedures to continuously assess laboratory work and the emergent results”.⁵ IQC differs from external quality control, which consists of using processes and materials to compare one laboratory against another.^6,7

IQC procedures employ statistical and non-statistical techniques to verify the overall quality of results, such as Levey-Jennings charts for data interpretation.^2,7These processes also involve using control materials that resemble patient samples to verify test results and equipment performance.⁷ By comparing these control results to established standards, labs can detect — and act upon — any inconsistencies or errors more quickly, helping ensure the reliability of patient test results.² This is critical in helping to identify trends that may indicate potential quality issues, such as with testing reagents or equipment.²

For example, if a glucose quality control reagent was expected to produce results of 100 mg/dL on average, yet repeat results of the same reagent gave 96, 98, 101, 92, 93, 88, 92, 93, 91, 90, and 98 mg/dL, this would indicate a low bias result in the instrument.² Not running IQC tests to determine this information could lead to inaccurate readings being passed on to patients, resulting in less successful patient care.

As laboratories work to maintain high-quality results in increasingly complex environments, digital instrument maintenance solutions offer a proactive way to support quality control. Modern, web-based platforms can automate the scheduling, tracking, and documentation of instrument maintenance, replacing fragmented logbooks and manual records with a unified digital workspace. This helps ensure that critical equipment is maintained consistently and in line with applicable standards.

By integrating maintenance information with quality control (QC) results, laboratories can uncover patterns between instrument performance and QC deviations, enabling earlier intervention to reduce errors and downtime. Real-time monitoring, automated audit trails, and centralized dashboards strengthen collaboration, improve operational efficiency, and support ongoing readiness for inspections and accreditation.⁸

A laboratory quality management system (LQMS) is defined by The International Organization for Standardization (ISO) and the Clinical and Laboratory Standards Institute (CLSI) as “coordinated activities to direct and control an organization about quality” in a way that investigates the entire laboratory system.⁹

Creating a strong LQMS framework should be centered around ensuring all aspects of laboratory operations meet quality standards and that all elements of quality control — including documentation, standard operating procedures (SOPs), and continuous improvement processes — are sufficiently integrated. It should also include all the managerial and technical aspects that are associated with lab procedures.¹

Since approximately 70 - 75% of all medical diagnoses are obtained via clinical lab reports, the quality of a lab’s service can directly impact the quality of healthcare provided.⁶ Therefore, each LQMS framework should strive to keep all laboratory processes controlled and consistent, emphasizing the importance of standardized procedures, staff training, and regular instrument audits.^6,10

To support the framework of a Laboratory Quality Management System (LQMS), digital quality¹¹ and operations¹² management solutions can provide real-time visibility and automate key quality control (QC) tasks, reducing the burden on laboratory staff and supporting more efficient operations. By integrating the entire sample flow from pre- to post-analytics, these platforms can help optimize workflows and reduce the risk of errors through automated sample routing, rule-based alerts, and continuous monitoring. Advanced validation capabilities and peer group comparisons empower laboratories to identify and address QC issues more quickly, strengthening confidence in results.

These digital solutions also centralize data storage and generate time-stamped audit trails, helping to streamline compliance activities and support alignment with ISO 15189 requirements. With features such as automated reporting and customizable, audit-ready summaries, laboratories can track quality metrics more easily, manage performance across sites or instruments, and stay prepared for inspections and regulatory audits, all while lowering the risk of human error.

Due to the nature of the clinical laboratory environment, there are various types of quality control to consider when ensuring the accuracy and reliability of test results. These need to be enforced at different stages of laboratory processes, including:¹

1. Pre-analytical stage — errors in the pre-analytical stage occur when test samples or materials are mishandled before being analyzed. These errors can include samples being mixed up, mislabeled, not stored properly, or being collected in an unsuitable way. To minimize these errors, it is important to follow proper sample collection procedures by ensuring clear labeling, correct transportation, and appropriate storage protocols are followed.
2. Analytical stage — errors during the analytical stage often arise due to using incorrect test reagents or quantities of reagents, defective equipment, or not complying with SOPs. To minimize these errors, it is important to correctly maintain and calibrate equipment, regularly update the reagent inventory, clearly document SOPs, and ensure staff are trained to comply with these procedures.
3. Post-analytical stage — errors in the post-analytical stage can include the incorrect calculation, recording, or interpretation of a patient’s result. As such, minimizing these errors can be achieved by avoiding manual calculations and ensuring only trained staff members are allowed to interpret and make appropriate recommendations based on the results.

Each type of quality control plays a crucial role in the overall accuracy and reliability of laboratory operations, helping to identify and correct errors at every stage of the testing process.

Failing to integrate quality control in a laboratory can result in severe negative consequences, including:¹

• Potential misdiagnoses or incorrect treatments being administered

• Treatment delays 

• Compromised patient safety

• Time wastage

• Budget implications

Errors in laboratory results can also damage a laboratory’s reputation, leading to a potential loss of trust amongst healthcare providers and patients. As such, ensuring rigorous quality control procedures is vital to help minimize these risks. 

Quality control in laboratories is crucial to ensuring the accuracy, reliability, and consistency of diagnostic tests.^1,2 By implementing robust internal and external quality control procedures and maintaining a comprehensive LQMS, laboratories can help safeguard patient safety, enhance diagnostic accuracy, and meet the ever-evolving demands of modern healthcare in the right way.²