Beyond Routine QC Metrics
Lecture 1: Moving Averages
Jemmerlyn Lorenzo, Asst. Manager, Product & Applications Group – Sysmex Philippines
Lecture 2: Importance of External Quality Assurance Program
Dr. Wayne Dimech, Executive Manager – Scientific & Business Relations – NRL Science of Quality
Objectives of the Lectures
In this Webinar, we will be focusing on the importance of quality in the laboratory. The various approach done to achieve quality and reliable laboratory results which will aid in the correct diagnosis of our patients.
Abstracts of Talk
Quality control measures which use control blood samples are crucial, but may only represent a snapshot of the analyser’s condition when the procedure was carried out. In contrast, the XbarM control function is a long-term and continuous control process, which runs continuously over the entire working day and can reveal any drifts in the results much more rapidly.
The XbarM control program (sometimes also called ‘moving calculation’) is based on the calculation of weighted moving averages for all the parameters of the blood count using a very complex algorithm developed from Bull’s algorithm (which is limited to only some parameters of the red blood cell count).
In contrast to traditional quality control systems, which use preserved control blood samples, the XbarM control system uses routine blood samples measured on the respective analyser. Each blood test result obtained by the analyser is indirectly and automatically used to calculate these averages. Equally-sized groups of individual results are combined continuously to form batches and an average is calculated for every parameter from each batch. This causes the averages to ‘move’ over time, within specific tolerances, as each batch of measurements will be composed of different results.
The results of testing for infectious diseases informs the diagnosis and treatment of patients, safeguards the blood supply from transfusion-transmitted infections, support epidemiology and sero-surveillance and underpins the efficacy of intervention programs. Incorrect test results lead to infected individuals missing treatment and further spreading disease; uninfected individuals given inappropriate treatment, contaminated blood supply and misleading epidemiology. Therefore, it is vitally important that medical testing and blood screening laboratories minimise the risk of invalid test results. Quality assurance is the foundation of risk minimisation.
Quality assurance starts with the selection of assays that are fit for purpose and have evidence of acceptable performance. This is usually represented by registration by a regulatory body. Once in use, laboratories have a responsibility to monitor the performance of the assay, and its use, over time. Operators of the assay should be trained and competence demonstrated. Two main quality assurance activities are used to monitor assay performance; external quality assessment schemes (EQA) and quality control (QC) programs.
EQA programs assess the quality of testing from receipt of samples to the interpretation and reporting of test results. EQA samples should be similar to those of patient samples and represent different disease states, genotype/serotypes, and concentrations of analytes. Sufficient samples should be provided to accurately assess laboratory performance. Where possible, the chosen EQA provider should be accredited to ISO17043, thereby demonstrating compliance with the standard.
Quality control of infectious disease testing differs from that used for clinical chemistry. Where chemistry tests for inert analytes, infectious disease testing measures biological functionality. Principles generally accepted in chemistry do not apply to infectious disease serology. NRL has developed a more appropriate model for monitoring QC results; called QConnect™. This presentation will provide a brief overview of QConnect and how it can detect unexpected test results.