Background: Precise estimation of measurement uncertainty (MU) would offer an excellent opportunity to improve quality and to receive appropriate explanations of test results. However, MU estimates differ significantly across laboratories before guidance is applied. This study aimed to compare the differences in the determination of MU for quantitative immunoassay analytes before and after using ISO/TS 20914:2019 to promote its application in both laboratory and clinical settings. Materials and Methods: Internal Quality Control (IQC) data from seventeen chemiluminescence immunoassays (CLIA) were collected. Two strategies (CNAS-TRL-001: 2012 and ISO/TS 20914:2019), were used separately for MU estimation. Permissible imprecision was defined using the surrogate empirical coefficient of biological variation (BV). Pooled MUs were compared against the permissible relative expanded uncertainty (pU%) and permissible expanded uncertainty (pU) criteria. Results: The reductions of %U and U from the new strategy to the previous one on all analyte levels were 51.22% and 92.68%. Measurement uncertainty estimated by the two strategies which was less than the permissible uncertainty, across all analyte levels increased from 92.68% to 97.56% when the new strategy was applied. For example, with alpha-fetal protein (AFP), the new strategy altered the distance between test values and the medical decision limit because of changes in its MU under the two strategies. Conclusion: The new strategy for MU evaluation, considering reagent lot changes, is better matched to real laboratory settings, and possesses the property of robustness and representativeness. A more accurate estimate of MU enables improvements in laboratory measurement quality and clinical applications.

Background Benchmarking is a valuable quality improvement activity for any organisation. Peer comparisons for non-analytical processes are difficult in laboratory medicine because of a lack of structured opportunities. Lab Insights is a Roche program that provides benchmarking across management, operations, and productivity. This paper examines the relationship among physical laboratory automation, IT capabilities, and productivity. Methods The anonymous electronic Survey was conducted from 2022 to 2024 in the Asia-Pacific region, including 5089 professionals from across 22 countries. The Survey has been run triennially since 2010, allowing some comparison between years. For statistical modelling, multiple linear regression using ordinary least squares was employed to assess the strength and significance of operational factors, with staff productivity (samples per full-time equivalent (FTE)) as the dependent variable. Results The surveys from 2019 and 2022 were compared to evaluate engagement, which was found to be high. The automation components most closely associated with productivity increases are sample aliquoting, add-on/rerun, sample quality check/serum indices, and sample delivery automation, in that order. Negative factors impacting productivity include limited space availability, the lack of an aliquoter for all samples, and the need to manually email critical results. Conclusions This analysis showed that some IT functionalities are associated with improved productivity, namely turnaround time monitoring for urgent/routine assays, sample rejection rates, automatic reporting of critical results, test billing software, productivity and data export functions. Perhaps a productivity/KPI (key performance indicator) dashboard is also perceived by the survey respondents as significant for improving workflow management and, hence, productivity.

Laboratory accreditation may be mandatory in some countries, and ISO 15189 is the most relevant international standard. Despite this, there are few laboratories globally that are accredited. The aim of this paper is to present information on the number of laboratories accredited in the Asia–Pacific region and to which standards. Roche Diagnostics runs a triennial laboratory Survey, Lab Insights, which collects data on accreditation. The Roche benchmarking Survey gathers feedback from clinical laboratory managers and directors on their laboratories’ operation and performance. Participants from the region access the platform using any internet browser and complete the Survey digitally. The final report is available on the same platform for participants once it is validated and finalised. In some countries where translation was required or internet connectivity was limited, Roche affiliates distributed the questionnaires in hard copy. The proportion of laboratories holding ISO 15189 accreditation increased substantially from 31.9 in 2019 to 42.3

The Joint Committee for Traceability in Laboratory Medicine (JCTLM) supports worldwide equivalence and comparability of measurement results in laboratory medicine to improve health care and facilitate national and international trade in in vitro diagnostic (IVD) medical devices. The 2025 biennial members and stakeholders' workshop focused on the expectations and benefits of harmonized results among medical laboratories, as well as the challenges associated with achieving this goal. Harmonization of results from end-user IVD measurement procedures (IVD-MPs) can be achieved by applying the principles of metrological traceability; however, there are several historical examples of standardization efforts that did not achieve the required level of harmonization. The reasons for these failures can be found in various elements of the calibration hierarchy including: a) an unclear definition of the measurand, b) differences in selectivity of the IVD-MPs, c) issues with the commutability characteristics of secondary certified reference materials (CRM), d) inconsistencies in handling of CRMs to prepare calibrators, and e) lack of adoption and implementation by the IVD manufacturers. The lack of harmonized results can lead to confusion, treatment delays, errors in medical decisions, and increased healthcare costs. There are still assays in common use that lack metrological traceability because they lack CRMs, reference method procedures (RMPs), and/or reference method services (RMSs). Producing and maintaining reference measurement system components is complex and expensive. There are multiple regulatory frameworks and requirements that IVD manufacturers must meet worldwide. There is a vital role for External Quality Assessment (EQA) providers to assess the agreement status of results across different IVD-MPs and identify any changes in their equivalence. However, EQA materials must be commutable with clinical samples for each of the examined IVD-MDs for results to reflect the status of harmonization of clinical sample results. The future will need leadership and cooperation between bodies such as JCTLM, the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC), and IVD manufacturers.

OBJECTIVES:Unified Code for Units of Measure (UCUM) encodes syntax without prescribing which unit should be used. The Nomenclature for Properties and Units (NPU) terminology, developed by IFCC and IUPAC, specifies both the kind-of-quantity (e.g., mass concentration or substance concentration) and the recommended unit for each code, and can serve as a governance layer, yet no study has evaluated how NPU-recommended units align with actual laboratory practice. METHODS:30 clinical chemistry measurands in blood were selected from the overlap between a Korean multi-institutional unit-usage survey and a consensus study on commonly tested analytes mapped to LOINC. For each measurand, commonly used units in Korean laboratories, RCPA-recommended units, and NPU-recommended units were compared, along with LOINC example units. RESULTS:Of the 30 measurands, 6 (20 %) were fully concordant across Korean practice, Australian practice, and NPU. For 15 (50 %), a kind-of-quantity discordance was observed: Korean laboratories reported mass concentration (mg/dL), whereas Australian practice and NPU used substance concentration (mmol/L). For 6 (20 %), Korean laboratories used IU/L while Australian practice and NPU used U/L. Korean and Australian LOINC code selections overlapped for only 15 (50 %), reflecting different national choices of kind-of-quantity; Korean practice uniformly matched LOINC example units, whereas Australian practice deviated in three instances. NPU did not provide mass concentration codes for the 15 discordant measurands that are reported in mass concentration units in Korea. CONCLUSIONS:The predominant discordance reflects a lack of international agreement on kind-of-quantity selection. A stepwise transition strategy - from unit symbol correction to kind-of-quantity transition - can be informed by the degree of discordance.

Background:Reference intervals (RIs) are critical for accurate clinical decision-making, yet many laboratories rely on manufacturer-provided RIs without local validation. This study assessed the knowledge, attitudes, and practices (KAP) of clinical laboratories in Nepal regarding RI utilization, highlighting challenges and opportunities for standardization in alignment with ISO 15189:2022 accreditation. Methods:A nationwide cross-sectional KAP survey was conducted among 56 laboratory professionals. Data were collected via an online questionnaire, covering demographics, RI knowledge, current practices, challenges, and attitudes toward national standardization. Descriptive and inferential statistics (chi-square, Fisher's exact tests) were used for analysis. Results:While 71.4% of respondents correctly defined RIs as the 2.5th-97.5th percentiles, 28.6% held misconceptions. Most laboratories relied on manufacturer-provided RIs (87.5%) or published literature (67.9%). Key challenges to derive one's own RI included method variability and recruiting reference individuals. Accredited labs (ISO 15189) demonstrated better knowledge of RI (93.3% vs. 63.4%, p=0.032) and higher confidence in using current RI (26.7% vs. 7.3%, p=0.047). Strong interest existed in national RI standardization (92.9%) and training (85.7% preferred hands-on workshops). Conclusions:This survey of higher tier clinical laboratories in Nepal reveals that while these laboratories generally understand the importance of reference intervals, significant gaps in practice and standardization remain. The findings highlight an urgent need for inclusive strategies that also address the unique constraints of smaller, widespread laboratories, which perform a large proportion of routine testing in the country. The intense interest in a national program presents an opportunity to improve. Multicenter studies and RI validation integration into accreditation are needed to improve diagnostic accuracy.

OBJECTIVES:Point-of-care (POC) International Normalised Ratio (INR) testing provides rapid anticoagulation monitoring. Still, it is susceptible to systematic bias, particularly at supratherapeutic levels, which can lead to inappropriate warfarin dose adjustments and increased thrombotic risk. This study evaluated bias trends between Abbott and Roche POC INR devices. METHODS:Bias trends were assessed using Royal College of Pathologists of Australasia Quality Assurance Programs survey data (2023-2025), in-house verification, and patient sample comparisons against laboratory instrument testing used as a comparative reference mark (Werfen ACL TOP). RESULTS:Abbott PT INR cartridges demonstrated a shift from negative bias in 2023 to pronounced positive bias in 2024, with discrepancies most evident at INR >4.0. The introduction of Abbott PT Plus cartridges in 2025 significantly reduced bias, achieving near alignment with Roche CoaguChek Pro II and laboratory methods tested in this study. Comparative reagent analysis highlighted the influence of thromboplastin source and ISI values on harmonisation. CONCLUSIONS:Findings reinforce the need for confirmatory venous testing when POC INR exceeds critical thresholds, and emphasise the importance of ongoing performance monitoring, structured escalation policies, and transparent communication with manufacturers.

Background K2EDTA contamination of serum samples is a preanalytical error that poses a risk to patient safety. Contamination is most frequently mild to moderate, which standard detection procedures often miss. We examined whether machine learning models could improve the detection of K2EDTA contamination. Methods Artificial neural network, decision tree (both simple and complex), extreme gradient boosting, k-nearest neighbours, logistic regression, naïve Bayes, random forest, and support vector machine models were developed. Models were trained using extracted patient results for electrolytes, urea, creatinine, albumin-adjusted calcium, magnesium, and phosphate, with K2EDTA contamination errors simulated in silico. Model performance was evaluated on 300 real-world samples, half of which were intentionally contaminated with mild to moderate amounts of K2EDTA. Model performance was compared with that of limit checks, multi-analyte rules and two novel parameters, the potassium/calcium ratio and the potassium/magnesium ratio. Results All nine machine learning models identified K2EDTA contamination more accurately than standard approaches (p-values <0.05). Seven models performed similarly, with accuracies of 91.3-93.3%, sensitivities of 88.0-90.0%, specificities of 94.7-96.7%, and area under the receiver operating characteristic curve (AUROC) of 0.9727-0.9787. The simple decision tree and naïve Bayes models performed slightly worse. The potassium/calcium ratio was the most effective of the standard approaches, with accuracy of 79.7%, sensitivity of 68.7%, specificity of 90.7%, and AUROC of 0.9233. Conclusions Using machine learning models would enable better detection of mild to moderate K2EDTA serum contamination and improve patient safety. For laboratories unable to implement machine learning models, the best alternative is the potassium/calcium ratio.

Objectives:Internal Quality Control (IQC) procedures must evolve as laboratory practices change to meet the requirements of higher patient volumes and the greater need for comparability of results across laboratories. This study developed a strategy to detect significant errors in routine hematology analytical processes using a novel approach to setting IQC material targets (mean and limits) across multiple instruments. This has not been described for hematology laboratories before. Content:The approach described used a common IQC sample mean and limits determined from a manufacturer-based peer group using the same IQC material. The limits involved a new parameter, the random error of the peer group analyzers around their own mean (SDintra90), to detect bias or imprecision. The model was assessed over five months using 17 analyzers that measured hemoglobin and red cell count. Using a common mean requires that the different analyzers exhibit no significant bias. Summary:The model effectively controls analytical error in a network of laboratories using the same measurement system. This model aligns with the best theoretical principles for patient risk reduction and harmonizes practices for acceptance and rejection across the network. Outlook:The model presents an approach to IQC that meets the demands of real-world practice.

BACKGROUND:External quality assurance (EQA) programs must assess whether the analytical performance of commonly used in vitro diagnostic (IVD) devices is fit for their intended clinical use. We developed a method for this assessment based on reclassification of results at clinical decision limits and applied it to results from a haemoglobin A1c (HbA1c) EQA program. CONTENT:Using a commutable EQA program to provide analytical performance characteristics, we simulated 10,000 measurements of the HbA1c value of each of 6,326 subjects in the National Health and Nutrition Survey (NHANES) by common IVD devices and the NHANES device. A parametric empirical Bayes approach was used to account for regression to the mean. We estimated the rates at which the IVD devices would reclassify results and compared them with the estimated reclassification rate for the NHANES device, calculating the difference between them as the 'incremental reclassification rate' (IRR). IRRs were 'optimal' if <1.5 %, 'desirable' if <3.0 %, and 'minimal' if <4.7 %. SUMMARY AND OUTLOOKS:EQA performance data were available for five HbA1c devices: Abbott Afinion, Bio-Rad D series, Roche Cobas, Sebia Capillarys, and Siemens DCA. The median IRRs were optimal for all methods for diabetes diagnosis (0.11-0.22 %) and for diabetes monitoring (-0.51-1.01 %), with negative IRRs representing lower reclassification rates than the NHANES device. For prediabetes diagnosis, the Afinion failed the minimal standard (8.62 %), but median IRRs were desirable for the other methods (1.43-2.69 %). EQA providers should consider reporting IRR for suitable analytes to help identify poorly performing IVD devices.

Few external quality assurance programs adequately address the complexity of largescale human genome or exome analysis. To bridge this gap, Australian Genomics and the Royal College of Pathologists of Australasia Quality Assurance Programs (QAP) developed a pilot interpretive module focused on genomic testing for childhood syndromes and intellectual disabilities. The program assessed laboratories' proficiency in interpreting complex genomic data for pediatric disorders. Six clinically accredited laboratories analyzed standardized genomic, phenotypic, and referral data. Reports were evaluated using a rubric adapted from the European Molecular Genetics Quality Network model, covering genotyping, variant classification, interpretation, and report content. Feedback included comparative performance results and individual recommendations. All laboratories correctly identified and classified target variants, but variation was observed in report structure, inclusion of genetic counseling advice, and application of the American College of Medical Genetics and Genomics/Association for Molecular Pathology classification framework. Participants noted that data-sharing limitations and differences in local reporting practices contributed to scoring inconsistencies. The pilot demonstrated the feasibility of a disease-specific interpretive QAP for complex pediatric genomic testing. Future rounds will address logistical challenges, refine scoring criteria, and strengthen standardization, supporting broader implementation. This initiative lays the groundwork for integrating specialized QAP modules into routine practice to improve diagnostic accuracy and consistency across laboratories.

Objectives Recent advances in information technology have renewed interest in patient-based real-time quality control (PBRTQC) as an alternative to internal quality control (IQC). However, since regulations mandate IQC, PBRTQC can only be implemented as a separate system. The additional labor required for PBRTQC may hinder widespread adoption. Therefore, a more efficient system that integrates IQC with PBRTQC is needed for laboratories to implement the methods effectively. Methods A QC system that integrates IQC with PBRTQC is proposed. The maximum average number of patients with unacceptable analytical errors (MaxANP TE ) was introduced as a critical metric to benchmark the efficiency of the integrated PBRTQC system against the IQC-only system using a modified Parvin patient risk model. With the historical data of serum sodium (Na), chloride (Cl), alanine aminotransferase (ALT), and creatinine (CREA) from Zhongshan Hospital, Fudan University, in 2019, the integrated system incorporating the simple PBRTQC model and the more advanced regression-adjusted real-time quality control (RARTQC) were compared with the IQC-only system. Results In most cases, the integrated system incorporating RARTQC models outperformed the IQC-only system, particularly for ALT, where QC events were reduced by up to 45 %. Based on these findings, we proposed strategies for laboratories to design the integrated system. Conclusions The study demonstrated the improvement of efficiency of the integrated PBRTQC system over the IQC-only system. These insights can help laboratories make informed decisions on adopting PBRTQC models and provide as evidence for revising regulation on IQC.

Introduction:Patient-based quality control (PBQC) is an alternate quality control technique to conventional (internal) quality control. It uses patient results generated for clinical care to monitor the analytical performance through statistical analysis. The use of PBQC in routine laboratory is impeded by lack of familiarity and appropriate informatics tool. Method:A Spreadsheet for PBQC Analysis and Evaluation (SPAE, based on Microsoft Excel) is developed. It incorporates IFCC recommended features for PBQC informatics tool that has been automated, including data visualization, data (Box-Cox) transformation, extreme value treatment (winsorization) and user parameter selection (block size, acceptable false positive rate, desirable bias for detection). Results:Following parameter selection and data input, the spreadsheet automatically calculates the winsorization limits, transformed values, performance verification metrics such as false positive rates and number of results affected before error detection (NPed) - a performance metric for how sensitive the PBQC model detects the predefined error (bias). The verified PBQC model can be used for routine monitoring. The performance of the spreadsheet tool was verified against an independent model based on Python. Laboratory users can download the tool at https://github.com/HuiQi96/PBQC/blob/main/PBQC_model_v2.2.zip. Discussion:The SPAE is a simple-to-use desktop tool that lowers the barrier for laboratory users to adopt PBQC in their quality control system. In addition, the spreadsheet can be used as an educational tool, such as when conducting a workshop, to help laboratory users better familiarize themselves with the PBQC concepts and used for independent verification of the output of another informatics tool.

In this Personal View, we introduce the concept of external quality assessment (EQA) super challenges, in which multiple EQA providers, at approximately the same time and in a coordinated manner, use test samples with identical characteristics in their programmes. The evaluation of test results from the resulting increase in the number of laboratories and test systems used (considering the resulting greater variety of influencing factors that apply to the analysis in the individual laboratories) enables the collection of data that reveals differences, advantages, and disadvantages of individual test systems, in addition to the extent of individual influencing factors. By comparing the analytical performance of test systems and highlighting their limitations, EQA super challenges and the examination results collected by them are valuable contributions for post-market surveillance of diagnostic tests, aid harmonisation in laboratory medicine, and help to identify areas for improvement for manufacturers, policy makers, and regulators. Especially during or in preparation for epidemics or pandemics, EQA super challenges are particularly valuable for public health institutions to quickly gain a clear picture of the testing performance.