Often regarded as the grandfather of quality control, Dr. Walter A. Shewhart made a groundbreaking contribution to the field of manufacturing quality with the publication, “Economic Control of Quality of Manufactured Product,” in 1931. This practically century-old work laid the foundation for modern statistical quality control (SQC) and introduced key concepts that continue to shape laboratory medicine.
In his book, Shewhart explored fundamental principles such as statistical control, design limits on variability, and the specification of standard quality. His idea that, “we can find and remove causes of variability until the remaining system of causes is constant, or until we reach that state where the probability that the deviations in quality remain within any two fixed limits is constant.”1 This concept would influence the development of Lean Six Sigma, Total Quality Management (TQM), modern process improvement methodologies, and the birth of statistical process control. Statistical process control introduced the notion of control charts. This tool is now widely used to monitor process stability and detect disparities that require action by the operator. Shewhart’s work is the foundation for quality and played a crucial role in shaping modern quality management systems.
Levey-Jennings chart
Building on Shewhart’s work, in the 1950s, two pathologists, Dr. Stanley Levey and Dr. E.R. Jennings, introduced the principles of statistical quality control (SQC) to the field of clinical laboratory science. They proposed applying Shewhart’s control chart to medical laboratories to improve the reliability and accuracy of diagnostic testing. Their revolutionary paper, “The use of Control Charts in the Clinical Laboratory,” laid the foundation for a more systematic approach to monitoring laboratory performance, ensuring consistent and high-quality test results. As a result of their work, a type of control chart was developed and named in their honor.
The Levey-Jennings chart (LJ) is a graphical tool used to plot quality control data over time. Each point represents a QC measurement, which is compared against a predefined mean and control limit. By analyzing these values, laboratory personnel can quickly evaluate whether an assay or analytical instrument is functioning correctly. If the data points fall within the acceptable range, the test system is considered in control, however, if the points fall outside the control limits or display a recognizable pattern, corrective action is necessary to prevent inaccurate patient results. This innovation enhanced the accuracy, precision, and reliability of laboratory testing, allowing for early detection of systematic errors, reagent inconsistencies, and potential equipment malfunctions.
In 1957 while working in the Bioscience Laboratories, clinical chemists Milton and Henry Segalove made another significant advancement in the field of laboratory quality control. They began applying the Levey-Jennings chart on a daily basis. Their biggest contribution involved their structured approach to monitor performance by using multiple levels of control values.
A few years later, the use of the Levey-Jennings charts gained a broader acceptance when researchers Freier and Rausch introduced an improvement to quality control methodology. Instead of relying on traditional patient samples, they recommended the use of serum pools. These pooled samples would provide a more consistent and standardized reference for evaluating assay performance. Initially, these pooled samples were referred to as “standards,” but as their application in quality control continued, they became known as “control samples.”
The adoption of consistent control samples transformed clinical laboratory quality assurance, enabling laboratories to improve accuracy, precision, and reproducibility of testing. The advancements made by Freier and Rausch set the foundation for traditional quality controls and formed the basic concepts for quality management systems (QMS) in the clinical laboratory.
The Westgard Rules
In 1977, Dr. James Westgard and his colleagues introduced what would become the widely recognized and influential Westgard rules, a groundbreaking framework for internal quality control in laboratory testing. Their paper, “Performance Characteristics of Rules for Internal Quality Control: Probabilities for False Rejection and Error Detection,” gave rise to the development of modern quality assurance in clinical laboratories.
In this study, Westgard examined two distinct groups of quality control rules. The first group, which would later be known as the Westgard rules, is applied when each individual control measurement is assessed independently to determine whether a test run should be accepted or rejected. As noted in the book by Westgard, “For this group, the probability of false rejection will increase as the number of control observations that are made during the run.”2 This statement highlights a key challenge in quality control, balancing the need for error detection while minimizing unnecessary rejections.
It took four years, but in 1981 Westgard and his colleagues published “A Multi-Rule Shewhart Chart for Quality Control in Clinical Chemistry.” This paper defined “the control rule to indicate the criterion for judging whether the observed control measurements (or observations) represent typical or atypical (stable or unstable) performance of the analytical method.”3 By developing these statistical rules, Westgard transformed laboratory quality control. They provided a methodical approach to detecting errors and ensuring the reliability of test results. Today, the Westgard rules remain a cornerstone of clinical laboratory quality control practices worldwide.
CLIA
The 1980s ended with the introduction of the Clinical Laboratory Improvement Amendments (CLIA) of 1988, a landmark regulation that set new standards for laboratory testing. Officially published in 1992, CLIA established stringent quality assurance and minimum quality control requirements to ensure accuracy and reliability in diagnostics. By standardizing these requirements CLIA enhances the consistency and dependability of laboratory results. The amendments also introduced comprehensive quality assurance programs to monitor test performance, equipment maintenance, and most importantly, provide ongoing training for laboratory personnel. These standards ensure the highest level of patient care.
Lean Six Sigma
Bill Smith introduced Six Sigma in 1986. Its introduction into healthcare marked a significant advancement in quality control. Six Sigma is a data driven approach designed to enhance process performance by minimizing variation. In essence, it is a management system aimed at achieving near perfect quality, allowing no more than 3.4 defects per million opportunities.
Implementing Six Sigma can greatly improve the quality of control materials in laboratories. Manufacturers adhering to Six Sigma principles continuously strive to eliminate errors, beginning with the selection of raw materials, thereby ensuring a higher quality final product. This, in turn, leads to more reliable and reproducible test results, reducing deviations that could compromise patient diagnoses. By applying traditional statistical methodologies, laboratories can more accurately assess reagent performance, ensuring stability and effectiveness throughout the product’s shelf life. This approach minimizes inconsistencies, optimizes reagent selection, and ultimately enhances diagnostic accuracy.
Conclusion
The evolution of quality control in laboratory medicine has been shaped by decades of innovation, rigorous research, and the contributions of pioneering scientists. From Shewhart’s early work in statistical process control to the development of the Levey-Jennings chart, Westgard rules, and the introduction of Six Sigma, each advancement has played a crucial role in refining laboratory testing standards. The implementation of CLIA regulations further strengthened these efforts by standardizing quality requirements and ensuring greater accuracy and reliability in diagnostic medicine. Today, these foundational principles continue to guide laboratory professionals in their pursuit of excellence, ultimately improving patient care and advancing the field of clinical laboratory science. As technology and methodologies in laboratory medicine continue to advance, the commitment to quality control remains vital in driving progress and ensuring the highest standards.
References
1. Shewhart WA. Economic Control of Quality of Manufactured Product. 1931.
2. Westgard JO, Groth T, Aronsson T, Falk H, de Verdier CH. Performance characteristics of rules for internal quality control: probabilities for false rejection and error detection. Clinical Chemistry. 1977;23(10):1857-1867.
3. Westgard JO, Barry PL, Hunt MR, Groth T. A multi-rule Shewhart chart for quality control in clinical chemistry. Clinical Chemistry. 1981;27(3):493-501.
