Benchmarking medical laboratory performance on a global scale.

Background and aims: Laboratory performance as a relative concept needs repetitive benchmarking for continuous improvement of laboratory procedures and medical processes. Benchmarking as such establishes reference levels as a basis for improvements efforts for healthcare institutions along the diagnosis cycle, with the patient at its center. But while this concept seems to be generally acknowledged in laboratory medicine, a lack of practical implementation hinders progress at a global level. The aim of this study was to examine the utility of a specific combination of indicators and survey-based data collection approach, and to establish a global benchmarking dataset of laboratory performance for decision makers in healthcare institutions. Methods: The survey consisted of 44 items relating to laboratory operations in general and three subscales identified in previous studies. A global sample of laboratories was approached by trained professionals. Results were analyzed with standard descriptive statistics and exploratory factor analysis. Dimensional reduction of specific items was performed using confirmatory factor analysis, resulting in individual laboratory scores for the three subscales of "Operational performance," "Integrated clinical care performance," and "Financial sustainability" for the high-level concept of laboratory performance. Results and conclusions: In total, 920 laboratories from 55 countries across the globe participated in the survey, of which 401 were government hospital laboratories, 296 private hospital laboratories, and 223 commercial laboratories. Relevant results include the need for digitalization and automation along the diagnosis cycle. Formal quality management systems (ISO 9001, ISO 15189 etc.) need to be adapted more broadly to increase patient safety. Monitoring of key performance indicators (KPIs) relating to healthcare performance was generally low (in the range of 10-30% of laboratories overall), and as a particularly salient result, only 19% of laboratories monitored KPIs relating to speeding up diagnosis and treatment. Altogether, this benchmark elucidates current practice and has the potential to guide improvement efforts and standardization in quality & safety for patients and employees alike as well as sustainability of healthcare systems around the globe.

Effective stewardship strategies to enhance appropriateness of refer-out test requests in a Canadian tertiary centre laboratory.

OBJECTIVES: Specialized testing conducted in reference laboratories is costly and often not optimally directed. Since 2016, our institution has worked to ensure the appropriateness of refer-out (RO) tests. We examine the impact of utilization initiatives on the patterns of requests and completed tests. DESIGN AND METHODS: In 2016, 81 RO tests were selected for a more rigorous approval process. Physicians not pre-approved for testing received a prompt to consult with laboratory subject matter experts (SMEs) for further detail. After review, SMEs provided responses, approving or rejecting requests based on clinical relevance. Stewardship activities also included: repatriating tests locally, preferring Canadian over foreign institutions, unbundling tests, distributing educational memos, and introducing staged testing. We collected data on the number of requested (NoR) and number of completed (NoC) tests in 2015, before the implementation of the new vetting procedures, and for the post-implementation phase from 2016-2022. RESULTS: For 62 targeted RO tests (including trace metals, vitamins, antibodies, and endocrine-related tests), there was a 33% reduction in NoR and a 51% reduction in NoC in 2022 compared to 2015. The total savings for the study period based on NoC was $807,736. The NoC rate for Neuronal antibody tests decreased to 48.6% in 2022, with cost savings of $17,123, and an additional $50,000 saved by changing the testing site. Insourcing apolipoprotein B and fecal calprotectin tests resulted in cost savings of $3,380 and $3,371, respectively, in 2022. CONCLUSIONS: Automated messaging followed by a formal review of RO test requests is an effective utilization strategy that prevents redundant or clinically unjustified testing. This approach leads to significant economic savings and is expected to improve the efficiency of patient care.

Hospital at Home programs: Decentralized inpatient care but centralized laboratory testing?

The Hospital at Home (HaH) program has experienced accelerated growth in major Canadian provinces, driven in part by technological advancements and evolving patient needs during the COVID-19 pandemic. As an increasing number of hospitals pilot or implement these innovative programs, substantial resources have been allocated to support clinical teams. However, it is crucial to note that the vital roles played by clinical laboratories remain insufficiently acknowledged. This mini review aims to shed light on the diverse functions of clinical laboratories, spanning the preanalytical, analytical, and post-analytical phases within the HaH program context. Additionally, the review will explore recent advancements in clinical testing and the potential benefits of integrating new technologies into the HaH framework. Emphasizing the integral role of clinical laboratories, the discussion will address the current barriers hindering their active involvement, accompanied by proposed solutions. The capacity and efficiency of the HaH program hinge on sustained collaborative efforts from various teams, with clinical laboratories as crucial team players. Recognizing and addressing the specific challenges faced by clinical laboratories is essential for optimizing the overall performance and impact of the HaH initiative.

Comparative study on the quality control effectiveness of AI-PBRTQC and traditional PBRTQC model in identifying quality risks.

Introduction: We compared the quality control efficiency of artificial intelligence-patient-based real-time quality control (AI-PBRTQC) and traditional PBRTQC in laboratories to create favorable conditions for the broader application of PBRTQC in clinical laboratories. Materials and methods: In the present study, the data of patients with total thyroxine (TT4), anti-Müllerian hormone (AMH), alanine aminotransferase (ALT), total cholesterol (TC), urea, and albumin (ALB) over five months were categorized into two groups: AI-PBRTQC group and traditional PBRTQC group. The Box-Cox transformation method estimated truncation ranges in the conventional PBRTQC group. In contrast, in the AI-PBRTQC group, the PBRTQC software platform intelligently selected the truncation ranges. We developed various validation models by incorporating different weighting factors, denoted as λ. Error detection, false positive rate, false negative rate, average number of the patient sample until error detection, and area under the curve were employed to evaluate the optimal PBRTQC model in this study. This study provides evidence of the effectiveness of AI-PBRTQC in identifying quality risks by analyzing quality risk cases. Results: The optimal parameter setting scheme for PBRTQC is TT4 (78-186), λ = 0.03; AMH (0.02-2.96), λ = 0.02; ALT (10-25), λ = 0.02; TC (2.84-5.87), λ = 0.02; urea (3.5-6.6), λ = 0.02; ALB (43-52), λ = 0.05. Conclusions: The AI-PBRTQC group was more efficient in identifying quality risks than the conventional PBRTQC. AI-PBRTQC can also effectively identify quality risks in a small number of samples. AI-PBRTQC can be used to determine quality risks in both biochemistry and immunology analytes. AI-PBRTQC identifies quality risks such as reagent calibration, onboard time, and brand changes.

Quality and resilience of clinical laboratories in Rwanda: a need for sustainable strategies.

BACKGROUND: Quality healthcare is a global priority, reliant on robust health systems for evidence-based medicine. Clinical laboratories are the backbone of quality healthcare facilitating diagnostics, treatment, patient monitoring, and disease surveillance. Their effectiveness depends on sustainable delivery of accurate test results. Although the Strengthening Laboratory Management Towards Accreditation (SLMTA) programme has enhanced laboratory quality in low-income countries, the long-term sustainability of this improvement remains uncertain. OBJECTIVE: To explore the sustainability of quality performance in clinical laboratories in Rwanda following the conclusion of SLMTA. METHODS: A quasi-experimental design was adopted, involving 47 laboratories divided into three groups with distinct interventions. While one group received continuous mentorship and annual assessments (group two), interventions for the other groups (groups one and three) ceased following the conclusion of SLMTA. SLMTA experts collected data for 10 years through assessments using WHO's StepwiseLaboratory Quality Improvement Process Towards Accreditation (SLIPTA) checklist. Descriptive and t-test analyses were conducted for statistical evaluation. RESULTS: Improvements in quality were noted between baseline and exit assessments across all laboratory groups (mean baseline: 35.3%, exit: 65.8%, p < 0.001). However, groups one and three experienced performance declines following SLMTA phase-out (mean group one: 64.6% in reference to 85.8%, p = 0.01; mean group three: 57.3% in reference to 64.7%, p < 0.001). In contrast, group two continued to enhance performance even years later (mean: 86.6%compared to 70.6%, p = 0.03). CONCLUSION: A coordinated implementation of quality improvement plan that enables regular laboratory assessments to pinpoint and address the quality gaps is essential for sustaining quality services in clinical laboratories.

Main findings: We found that continuous laboratory quality improvement was achieved by laboratories that kept up with regular follow-ups, as opposed to those which phased out these followups prematurely.Added knowledge: This study has affirmed the necessity of maintaining mentorship and conducting regular quality assessments until requisite quality routines are established to sustain laboratory quality services.Global health impact for policy and action: These findings emphasise the significance of instituting a laboratory quality plan, with regular assessments, as policy directives to uphold and enhance quality standards, which benefits both local and global communities, given the pivotal role of laboratories in patient treatment, disease prevention, and surveillance.

Next-Generation Patient-Based Real-Time Quality Control Models.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

[Six Sigma driven QC management in hepatitis C serology]. / La méthodologie six sigma dans la gestion des contrôles de qualité en sérologie de l'hépatite C.

The Westgard quality control (QC) rules are often applied in infectious diseases serology to validate the quality of results, but this requires a reasonable tradeoff between maximum sensitivity to errors and minimum false rejections. This article, in addition to illustrate the six sigma methodology in the QC management of the (anti-HCV Architect®) test, it discusses the main influencing factors on sigma value. Data from low positive and in-kit control materials spreading over 6 months and using four reagent kits, were used to calculate the precision of the test. The difference between the control material reactivity and the cut-off defined the error budget. Sigma values were > 6, which indicates that the method produces four erroneous results per million tests. The application of the six sigma concept made it possible to argue the choice of the new QC strategy (use of 13S rule with one positive control) and to relax the existing QC rules. This work provides a framework for infectious diseases serology laboratories to evaluate tests performances against a quality requirement and design an optimal QC strategy.

Artificial intelligence in the clinical laboratory.

Laboratory medicine has become a highly automated medical discipline. Nowadays, artificial intelligence (AI) applied to laboratory medicine is also gaining more and more attention, which can optimize the entire laboratory workflow and even revolutionize laboratory medicine in the future. However, only a few commercially available AI models are currently approved for use in clinical laboratories and have drawbacks such as high cost, lack of accuracy, and the need for manual review of model results. Furthermore, there are a limited number of literature reviews that comprehensively address the research status, challenges, and future opportunities of AI applications in laboratory medicine. Our article begins with a brief introduction to AI and some of its subsets, then reviews some AI models that are currently being used in clinical laboratories or that have been described in emerging studies, and explains the existing challenges associated with their application and possible solutions, finally provides insights into the future opportunities of the field. We highlight the current status of implementation and potential applications of AI models in different stages of the clinical testing process.

Results of a Pilot External Quality Assessment Scheme for Genetic Testing of Newborns with Spinal Muscular Atrophy.

BACKGROUND: This study aims to evaluate the ability of laboratories to perform spinal muscular atrophy (SMA) genetic testing in newborns based on dried blood spot (DBS) samples, and to provide reference data and advance preparation for establishing the pilot external quality assessment (EQA) scheme for SMA genetic testing of newborns in China. METHODS: The pilot EQA scheme contents and evaluation principles of this project were designed by National Center for Clinical Laboratories (NCCL), National Health Commission. Two surveys were carried out in 2022, and 5 batches of blood spots were submitted to the participating laboratory each time. All participating laboratories conducted testing upon receiving samples, and test results were submitted to NCCL within the specified date. RESULTS: The return rates were 75.0% (21/28) and 95.2% (20/21) in the first and second surveys, respectively. The total return rate of the two examinations was 83.7% (41/49). Nineteen laboratories (19/21, 90.5%) had a full score passing on the first survey, while in the second survey twenty laboratories (20/20, 100%) scored full. CONCLUSIONS: This pilot EQA survey provides a preliminary understanding of the capability of SMA genetic testing for newborns across laboratories in China. A few laboratories had technical or operational problems in testing. It is, therefore, of importance to strengthen laboratory management and to improve testing capacity for the establishment of a national EQA scheme for newborn SMA genetic testing.

Doping yesterday, today, tomorrow: A challenge for the clinical laboratory.

This work highlights the role of the clinical laboratory, in the early detection of the use of substances prohibited for doping. This is because most people who practice sports today are non-professional athletes and amateurs, in particular young kids. These persons are not subjected to anti-doping controls but are at risk for their health. Endocrinologists and laboratory tests, by detecting evidence of such usage can help protect their health. Anti-doping testing require specific instruments for qualitative and quantitative chemistry, to meet regulations of official competitions but are impossible to be used in every person because of high cost. A particular role the clinical laboratory can acquire in the future is through its molecular biology sections, when genetic doping will probably be a reality and quantitative chemistry will be unable to detect it. A brief history of doping is provided to understand the reasons of its spread. Although doping has great resonance nowadays, it is not a recent problem. It was common among ancient Greek wrestlers and Romans, who used mixtures of herbs and stimulants. Ancient Greece started the Olympic Games and winners assumed great esteem, akin to demi-god status. Therefore, any attempt to improve athletic performance was a norm, also because the damage caused by the substances used was not known at that time. The use became so widespread that soldiers also used drugs to better combat during recent wars, and doping was practiced by athletes, actors and musicians in attempts to obtain better performance results. Today, doping has been refined so as not to be discovered and there is a continuous race between those who promote new substances and those who, like the World Anti-Doping Agency (WADA), were created to defend the health of athletes and comply with regulations of competitions. The clinical laboratory plays a fundamental role in identifying the use of prohibited substances, especially in competitions not classified as official, which are the majority and involve thousands of amateurs. In this paper a series of laboratory tests are proposed in this perspective, at low cost without the need of qualitative/quantitative chemical analyses required by the sport jurisdictions. Finally, a glance into genetic doping illustrates a likely future and imminent practice.

Critical test result management at Danish hospital laboratories: a national survey.

Critical test results in clinical laboratories are crucial for timely patient care, serving as indicators of potentially life-threatening conditions. Despite their importance, a notable heterogeneity in management practices exists globally. This study investigates the current practices of managing critical results at Danish clinical biochemistry laboratories and identifies areas prone for improvement. A comprehensive online survey was distributed to all 21 Danish clinical biochemistry laboratories regarding their critical result management, including documentation practices, critical limit selection, and quality assurance measures. A total of 17 laboratories (81%) responded. The answers revealed a generally uniform approach to managing critical results, with all laboratories having 24-h reporting, local instructions and using the telephone as communication channel. However, variations were noted in documentation practices and critical limit selection. Notably, 23.5% of the laboratories reported that one out of every ten critical results was not reported, indicating a significant risk of delayed critical results. This is further complicated by the limited use of predefined timeframes for reporting and also, only few laboratories actively monitored response times. The findings emphasize the need for more standardized documentation and evaluation practices to align with international standards and to enhance patient safety. While the laboratories showed a commitment to standardized procedures, the study emphasizes the necessity of a National or Nordic guideline to supplement the ISO 15189:2022. This study is a step towards optimizing critical result management, not only in Danish clinical biochemistry laboratories but also across various laboratory specialties, thereby improving overall laboratory quality, efficiency, and patient safety.

Primer Part 1 - Preparing a laboratory quality improvement project.

Quality in laboratory medicine encompasses multiple components related to total quality management, including quality control (QC), quality assurance (QA), quality indicators, and quality improvement (QI). Together, they contribute to minimizing errors (pre-analytical, analytical, or post-analytical) in clinical service delivery and improving process appropriateness and efficiency. In contrast to static quality benchmarks (QC, QA, quality indicators), the QI paradigm is a continuous approach to systemic process improvement for optimizing patient safety, timeliness, effectiveness, and efficiency. Healthcare institutions have placed emphasis on applying the QI framework to identify and improve healthcare delivery. Despite QI's increasing importance, there is a lack of guidance on preparing, executing, and sustaining QI initiatives in the field of laboratory medicine. This has presented a significant barrier for clinical laboratorians to participate in and lead QI initiatives. This three-part primer series will bridge this knowledge gap by providing a guide for clinical laboratories to implement a QI project that issuccessful and sustainable. In the first article, we introduce the steps needed to prepare a QI project with focus on relevant methodology and tools related to problem identification, stakeholder engagement, root cause analysis (e.g., fishbone diagrams, Pareto charts and process mapping), and SMART aim establishment. Throughout, we describe a clinical vignette of a real QI project completed at our institution focused on serum protein electrophoresis (SPEP) utilization. This primer series is the first of its kind in laboratory medicine and will serve as a useful resource for future engagement of clinical laboratory leaders in QI initiatives.

Using analytical performance specifications in a medical laboratory.

Analytical performance specifications (APS) are used for the quantitative assessment of assay analytical performance, with the aim of providing information appropriate for clinical care of patients. One of the major locations where APS are used is in the routine clinical laboratory. These may be used to assess and monitor assays in a range of settings including method selection, method verification or validation, external quality assurance, internal quality control and assessment of measurement uncertainty. The aspects of assays that may be assessed include imprecision, bias, selectivity, sample type, analyte stability and interferences. This paper reviews the practical use of APS in a routine clinical laboratory, using the laboratory I supervise as an example.

Quality assurance of SARS-CoV-2 testing laboratories during the pandemic period in India - An experience from a designated provider laboratory.

PURPOSE: Indian Council of Medical Research (ICMR) initiated an Inter-Laboratory Quality Control testing (ILQC) program for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing. Under this program, SARS-CoV-2 testing laboratories across the country submit specimens to the assigned State Quality Control (SQCs) laboratories for ILQC testing. This study aimed to investigate the performance of public and private SARS-CoV-2 testing laboratories in Delhi and highlights the country's effort in ramping up testing facility with close monitoring of the quality of Covid-19 testing results. METHODS: In the present study, two-years of SARS-CoV-2 testing data is included. During July 2020 through February 2022, a total of 1791 anonymised specimens were received from 56 public and private laboratories. These specimens were processed by reverse transcriptase - polymerase chain reaction (RT-PCR) tests as per National Institute of Virology (NIV) protocol and the results were uploaded on the ICMR quality control/quality assurance (QC/QA) portal without directly conveying the results to respective participating laboratories. This portal generated a final report stating concordance and intimate results to individual laboratories. RESULTS: Among the 1791 specimens, 25 were rejected and the remaining 1766 were tested. Among these specimens 1691 (95.75%) revealed concordance, and 75 (4.24%) were discordant. A total of 29 laboratories had 100% concordance, 21 laboratories had over 90% concordance and six laboratories had over 80% concordance. CONCLUSIONS: The study demonstrates that the establishment of an inter-laboratory comparison program for SARS-CoV-2 testing helped in monitoring quality of SARS-CoV-2 testing in the country.

New solutions to old problems: A practical approach to identify samples with intravenous fluid contamination in clinical laboratories.

OBJECTIVES: Contamination with intravenous (IV) fluids is a common cause of specimen rejection or erroneous results in hospitalized patients. Identification of contaminated samples can be difficult. Common measures such as failed delta checks may not be adequately sensitive nor specific. This study aimed to determine detection criteria using commonly ordered tests to identify IV fluid contamination and validate the use of these criteria. METHODS: Confirmed contaminated and non-contaminated samples were used to identify patterns in laboratory results to develop criteria to detect IV fluid contamination. The proposed criteria were implemented at a tertiary care hospital laboratory to assess performance prospectively for 6 months, and applied to retrospective chemistry results from 3 hospitals and 1 community lab to determine feasibility and flagging rates. The algorithm was also tested at an external institution for transferability. RESULTS: The proposed algorithm had a positive predictive value of 92 %, negative predictive value of 91 % and overall agreement of 92 % when two or more criteria are met (n = 214). The flagging rates were 0.03 % to 0.07 % for hospital and 0.003 % for community laboratories. CONCLUSIONS: The proposed algorithm identified true contamination with low false flagging rates in tertiary care urban hospital laboratories. Retrospective and prospective analysis suggest the algorithm is suitable for implementation in clinical laboratories to identify samples with possible IV fluid contamination for further investigation.

The role of analytical performance specifications in international guidelines and standards dealing with metrological traceability in laboratory medicine.

The goal of metrological traceability is to have equivalent results for a measurand in clinical samples (CSs) irrespective of the in-vitro diagnostic medical device (IVD-MD) used for measurements. The International Standards Organization standard 17511 defines requirements for establishing metrological traceability of values assigned to calibrators, trueness control materials and human samples used with IVD-MDs. Each step in metrological traceability has an uncertainty associated with the value assigned to a material. The uncertainty at each step adds to the uncertainty from preceding steps such that the combined uncertainty gets larger at each step. The combined uncertainty for a CS result must fulfil an analytical performance specification (APS) for the maximum allowable uncertainty (umax CS). The umax CS can be partitioned among the steps in a metrological traceability calibration hierarachy to derive the APS for maximum allowable uncertainty at each step. Similarly, the criterion for maximum acceptable noncommutability bias can be derived from the umax CS. One of the challenges in determining if umax CS is fulfilled is determining the repeatability uncertainty (u Rw) from operating an IVD-MD within a clinical laboratory. Most of the current recommendations for estimating u Rw from internal quality control data do not use a sufficiently representative time interval to capture all relevant sources of variability in measurement results. Consequently, underestimation of u Rw is common and may compromise assessment of how well current IVD-MDs and their supporting calibration hierarchies meet the needs of clinical care providers.

Establishing the Reportable Interval for Routine Clinical Laboratory Tests: A Data-Driven Strategy Leveraging Retrospective Electronic Medical Record Data.

BACKGROUND: This paper presents a data-driven strategy for establishing the reportable interval in clinical laboratory testing. The reportable interval defines the range of laboratory result values beyond which reporting should be withheld. The lack of clear guidelines and methodology for determining the reportable interval has led to potential errors in reporting and patient risk. METHODS: To address this gap, the study developed an integrated strategy that combines statistical analysis, expert review, and hypothetical outlier calculations. A large data set from an accredited clinical laboratory was utilized, analyzing over 124 million laboratory test records from 916 distinct tests. The Dixon test was applied to identify outliers and establish the highest and lowest non-outlier result values for each test, which were validated by clinical pathology experts. The methodology also included matching the reportable intervals with relevant Logical Observation Identifiers Names and Codes (LOINC) and Unified Code for Units of Measure (UCUM)-valid units for broader applicability. RESULTS: Upon establishing the reportable interval for 135 routine laboratory tests (493 LOINC codes), we applied these to a primary care laboratory data set of 23 million records, demonstrating their efficacy with over 1% of result records identified as implausible. CONCLUSIONS: We developed and tested a data-driven strategy for establishing reportable intervals utilizing large electronic medical record (EMR) data sets. Implementing the established interval in clinical laboratory settings can improve autoverification systems, enhance data reliability, and reduce errors in patient care. Ongoing refinement and reporting of cases exceeding the reportable limits will contribute to continuous improvement in laboratory result management and patient safety.