Abstract
Introduction
Medical laboratory service plays a central role in modern healthcare. It is essential that proper analytical quality control (QC) plans are implemented to ensure timely and reliable laboratory results. Over the last twenty years, there has been increased attention on implementing Six Sigma-driven, risk-based statistical quality control (SQC) for evidence-based analytical quality management in clinical laboratories. Nonetheless, there is a lack of relevant studies in New Zealand and Australia based on their local analytical performance specifications (APS), particularly on the recently launched analytical platform Roche Cobas 8000. To fill the research gaps, the study aimed to assess the efficiency and cost-effectiveness of such SQC model on the analytical platform, using New Zealand/Australian APS. It is hypothesised that the SQC model is an applicable tool for quality management in clinical laboratories and the implementation of risk-based SQC plans improves analytical performance while allowing substantial reduction in QC-related costs, thereby allowing improved quality of medical laboratory service for better patient care.
Method
The study was carried out on the Roche Cobas 8000 analytical platform in an internationally accredited clinical laboratory in New Zealand. A Six Sigma-based analytical performance assessment was carried out for a total of 62 biochemistry assays based on the local QC data over a three-month period, using the APS as defined by The Royal College of Pathologists of Australasia (RCPA). This was followed by the development of risk-based SQC plans for the assays assessed using Westgard QC frequency calculator. A trial of the proposed risk-based SQC plans was then carried out on seven randomly selected assays for a period of three months, followed by a post-trial analysis where the trialled SQC plans were comparatively assessed against the traditional SQC plans applied pre-trial, based on the observed analytical performance, efficiencies in error detection, and QC-related costs.
Results
Out of the 62 assays evaluated, 14 (22.6%) assays showed world-class performance (SM>6); 9 (14.5%) assays had excellent performance (5≤SM<6); 8 (12.9%) assays had good performance (4≤SM<5); 11 (17.7%) assays had marginal performance (3≤SM<4); 20 (32.3%) assays had unacceptable performance (SM<3). For the seven assays trialled, statistically significant improvements in SM results were observed post-implementation of the risk-based SQC plans, (p=0.004 for QC level 1, p=0.024 for QC level 2), with average SM results being 7.4 for QC level 1 and 8.2 QC level 2, which were 37% and 30% higher than their respective pre-trial counterparts of 5.41 and 6.33. In addition, compared to the pre-trial SQC plans, the risk-based SQC plans trialled demonstrated better efficiencies in error detection and allowed a slightly (5.5%) reduced QC-related cost.
Conclusion
The Six Sigma-driven, risk-based SQC model is a powerful and applicable tool for analytical quality management in clinical laboratories. The risk-based SQC plans, once fully and appropriately implemented, have the potential to improve the overall efficiency and cost-effectiveness of analytical QC, thereby permitting a more reliable and timely medical laboratory service for patient care.