Quality control planning is a critical function at any laboratory. It ensures the reliability of patient results and minimises the risk of errors or inconsistencies in the testing process along with being a key factor in patient care.
Research being carried out by Dunedin-based Awanui scientist Oscar Chen is examining whether the analytical quality control plans used by laboratories can be enhanced and the information provided have more individualisation and precision.
“Traditional quality control strategies generally involve a laboratory applying the same, empirically determined quality control plan for all tests being run on a particular analyser or process”, says Oscar. “For example, a laboratory may run two levels of quality control samples, which are tested two or three times a day, and then evaluating the results by a set of statistical rules which are universally applied.
“While these plans meet the requirements for gaining accreditation and deliver performance stability, the question is whether they have the accuracy, efficiency and even the cost-effectiveness to meet the requirements of modern, high‐throughput clinical laboratories and patient needs.”
Oscar’s research for his Master of Medical Laboratory Science thesis at the University of Otago is aimed at developing a set of individualized, assay-specific analytical quality control plans, based on Six Sigma methodology as a practical solution to test and improve quality control in laboratories.
The concept of Six Sigma was developed in the 1980’s to improve business processes by monitoring defects and errors, minimizing variation, and increasing quality and efficiency. The goal of Six Sigma, which is widely used in manufacturing, is to achieve a level of quality which is close to perfect with only 3.4 defects per million opportunities.
Under this approach, an index called sigma is calculated based on performance data. The value of sigma calculated represents the performance of a system in relation to the pre-defined acceptable tolerance. The higher the sigma value, the better performance quality within the system.
“My work so far indicates suboptimal quality control design can be a cause of poor analytical performance. However, we have an opportunity to use Six Sigma to develop evidence-based, statistical plans which potentially can be implemented for enhancing quality control at laboratories both across the Awanui network and elsewhere.”
Oscar says while there are studies underway overseas on optimising quality control strategies for biochemistry tests, there is no relevant, comprehensive study of this topic in Australasia, particularly for the newly launched biochemistry analyser Roche Cobas 8000.
“As part of my research, I am collecting quality control data for a range of assays processed on the Roche Cobas PRO 8000 analyser, which Awanui has installed in the Invercargill laboratory.
“The approach is to use the data to evaluate the analytical performance for each test by calculating its unique sigma value. Once the sigma value has been calculated, I will take this precise data to develop an example of a new, evidence-based quality control plan.
“This new quality control plan may include a set of individualised frequencies of the quality control measurements, quality control samples, and statistical rules applied for the quality control review,” says Oscar.
“By using these new quality control plans to monitor the test’s performance, I am aiming to see whether they are more efficient than the current plan, therefore provide laboratory results with greater accuracy and precision. If this can be achieved, then the reliability and timeliness for delivering the result to the patient can be enhanced, along with supporting better decisions and outcomes for clinical care.
“I would like to thank to my supervisor Dr Tania Slatter at University of Otago and Awanui for the support I have received during my research, in particular HoD automation Catherine Cahill, Laboratory Manager Craig Rogers, 2IC Karen Elizabeth and Quality Control Manager Roger Barton,” says Oscar.