Integrating quality control and external quality assurance

Longitudinal analysis of 20 Years of external quality assurance schemes for PCR/NAAT-based bacterial genome detection in diagnostic testing

Background

Quality control (QC), quality assurance, and standardization are crucial for modern diagnostic testing in the field of medical microbiology. The need for efficient QC to ensure accurate laboratory results, treatment, and infection prevention has led to significant efforts in standardizing assay reagents and workflows. External quality assessment (EQA) schemes, like those offered by INSTAND, play a vital role in evaluating in-house and commercial routine diagnostic assays, regarded as mandatory by national and global guidelines. The recent impact of polymerase chain reaction/nucleic acid amplification technology (PCR/NAAT) assays in medical microbiology requires that high-performing assays be distinguished from inadequately performing ones, especially those made by inexperienced suppliers.

Objectives

The study assesses the evolving diagnostic performance trends over 2 decades for the detection of EHEC/STEC, Borrelia (B.) burgdorferi, and MRSA/cMRSA. It explores the historical context of assay utilization, participant engagement, and rates of correct results in EQA schemes. The research seeks to identify patterns in assay preferences, participant proficiency, and the challenges encountered in detecting emerging variants or clinical strains.

Results

The study highlights the decline in in-house PCR assay usage, the emergence of new diagnostic challenges, and educational aspects within EQA schemes. Specific examples, such as the inclusion, in certain EQA surveys, of EHEC strains carrying stx-2f or B. miyamotoi, highlight the role of EQAs in increasing awareness and diagnostic capabilities. Advancements in MRSA detection, especially through the adoption of commercial assays, demonstrate the impact that technology evolution has had on diagnostic performance.

Conclusion

Achieving excellence in diagnostic molecular microbiology involves a multifaceted approach, including well-evaluated assays, careful instrumentation selection, and structured training programs. EQA schemes contribute significantly to this pursuit by providing insights into the evolving diagnostic landscape and identifying areas for improvement in the diagnostic workflow as well as in PCR/NAAT assay design.

External proficiency testing for histocompatibility and immunogenetics in today and future

The Histocompatibility and Immunogenetics laboratories provide disease association and pharmacogenetic analyses as well as the tests required for transplantation immunology and transfusion medicine. They perform Human Leukocyte Antigen (HLA) genotyping in patients/recipients and potential donor candidates for solid organ and stem cell transplants using various molecular methods, and determine mismatches. In addition, they also perform HLA antibody tests to detect anti-HLA antibodies in patients and flow cross-matches to evaluate donor-recipient compatibility. Evidence-based clinical guidelines have emphasized the importance of laboratory tests in clinical practices for a long time. Understanding the principles of Quality Control and External Quality Assurance is a fundamental requirement for the effective management of Tissue Typing laboratories. When these processes are effectively implemented, errors in routine assays for transplantation are reduced and quality is improved. In this review, the importance of Quality Assurance, Quality control and proficiency testing in Histocompatibility and Immunogenetic testing, the necessity of external proficiency testing (EPT) for accreditation, and existing and potential EPT programmes will be reviewed and evaluated in the light of the literature.

Advances in internal quality control

Quality control practices in the modern laboratory are the result of significant advances over the many years of the profession. Major advance in conventional internal quality control has undergone a philosophical shift from a focus solely on the statistical assessment of the probability of error identification to more recent thinking on the capability of the measurement procedure (e.g. sigma metrics), and most recently, the risk of harm to the patient (the probability of patient results being affected by an error or the number of patient results with unacceptable analytical quality). Nonetheless, conventional internal quality control strategies still face significant limitations, such as the lack of (proven) commutability of the material with patient samples, the frequency of episodic testing, and the impact of operational and financial costs, that cannot be overcome by statistical advances. In contrast, patient-based quality control has seen significant developments including algorithms that improve the detection of specific errors, parameter optimization approaches, systematic validation protocols, and advanced algorithms that require very low numbers of patient results while retaining sensitive error detection. Patient-based quality control will continue to improve with the development of new algorithms that reduce biological noise and improve analytical error detection. Patient-based quality control provides continuous and commutable information about the measurement procedure that cannot be easily replicated by conventional internal quality control. Most importantly, the use of patient-based quality control helps laboratories to improve their appreciation of the clinical impact of the laboratory results produced, bringing them closer to the patients.Laboratories are encouraged to implement patient-based quality control processes to overcome the limitations of conventional internal quality control practices. Regulatory changes to recognize the capability of patient-based quality approaches, as well as laboratory informatics advances, are required for this tool to be adopted more widely.

A comparative analysis of Sigma metrics using conventional and alternative formulas

BACKGROUND AND AIM

The Six Sigma approach, employing Sigma Metrics (SM), is commonly used to evaluate analytical performance in clinical laboratories. However, there is ongoing debate regarding the suitability of the conventional SM formula, which incorporates total allowable error (TEa) and bias. To address this, an alternative formula based on within-subject biological variation (CVI) as the tolerance range (TR) has been proposed. The study aimed to calculate and compare SM values using both formulas.

MATERIAL AND METHODS

Twenty clinical chemistry parameters were evaluated, and SM values were calculated using conventional formula with two TEa goals and the alternative formula. Intermediate precision (CVA%) values were obtained from internal quality control data, while bias values were derived from external quality assessment reports.

RESULTS

The results showed that using the conventional formula, 11 SM values based on CLIA TEa goals and 21 SM values based on BV TEa goals were deemed unacceptable (SM < 3). Additionally, 22 SM values calculated using the alternative formula were below 3.

CONCLUSION

The choice of TR had a substantial impact on the assessed analytical performance. Laboratories should carefully consider the appropriateness of each approach based on their specific quality objectives, analyte characteristics, and laboratory operations.

From research cohorts to the patient - a role for "omics" in diagnostics and laboratory medicine?

Human pathologies are complex and might benefit from a more holistic diagnostic approach than currently practiced. Omics is a concept in biological research that aims to comprehensively characterize and quantify large numbers of biological molecules in complex samples, e.g., proteins (proteomics), low molecular weight molecules (metabolomics), glycans (glycomics) or amphiphilic molecules (lipidomics). Over the past decades, respective unbiased discovery approaches have been intensively applied to investigate functional physiological and pathophysiological relationships in various research study cohorts. In the context of clinical diagnostics, omics approaches seem to have potential in two main areas: (i) biomarker discovery i.e. identification of individual marker analytes for subsequent translation into diagnostics (as classical target analyses with conventional laboratory techniques), and (ii) the readout of complex, higher-dimensional signatures of diagnostic samples, in particular by means of spectrometric techniques in combination with biomathematical approaches of pattern recognition and artificial intelligence for diagnostic classification. Resulting diagnostic methods could potentially represent a disruptive paradigm shift away from current one-dimensional (i.e., single analyte marker based) laboratory diagnostics. The underlying hypothesis of omics approaches for diagnostics is that complex, multigenic pathologies can be more accurately diagnosed via the readout of "omics-type signatures" than with the current one-dimensional single marker diagnostic procedures. While this is indeed promising, one must realize that the clinical translation of high-dimensional analytical procedures into routine diagnostics brings completely new challenges with respect to long-term reproducibility and analytical standardization, data management, and quality assurance. In this article, the conceivable opportunities and challenges of omics-based laboratory diagnostics are discussed.

Technical quality assurance and quality control for medical laboratories: a review and proposal of a new concept to obtain integrated and validated QA/QC plans

Technical quality assurance (QA) and quality control (QA/QC) are important activities within medical laboratories to ensure the adequate quality of obtained test results. QA/QC tools available at medical laboratories include external QC and internal QC, patient-based real-time quality control (PBRTQC) tools such as moving average quality control (MAQC), limit checks, delta checks, and multivariate checks, and finally, analyzer flagging. Recently, for PBRTQC tools, new optimization and validation methods based on error detection simulation have been developed to obtain laboratory-specific insights into PBRTQC error detection. These developments have enabled implementation and application of these individual tools in routine clinical practice. As a next step, they also enable performance comparison of the individual QA/QC tools and integration of all the individual QA/QC tools in order to obtain the most powerful and efficient QA/QC plans. In this review, a brief overview of the individual QA/QC tools and their characteristics is provided and the error detection simulation approaches are explained. Finally, a new concept entitled integrated quality assurance and control (IQAC) is presented. To enable IQAC, a conceptual framework is suggested and demonstrated for sodium, based on available published data. The proposed IQAC framework provides ways and tools by which the performance of different QA/QC tools can be compared in a so-called QA/QC error detection table to enable optimization and validation of the overall QA/QC plan in terms of alarm rate as well as pre-analytical, analytical, and post-analytical error detection performance.