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Background: Transgender people may avoid seeking medical care due to previous negative experiences and fear of discrimination. Clinical laboratories can contribute to a poor patient experience and clinical outcome when the design and functionality of laboratory information management systems (LIMS) do not consider the needs of transgender patients. This survey aimed to capture current practices in United Kingdom and Republic of Ireland clinical laboratories concerning how transgender patient data and test requests are managed throughout the total testing process. Methods: An anonymous survey was distributed to clinical laboratory professionals in November 2021. Thirty-three questions covered how gender variables are recorded for transgender patients and used to inform gender-specific calculations, test access, and reference intervals (RIs). Results: Of the 66 respondents, 70% were based in laboratories in England, with a majority of laboratories having ISO 15189 accreditation and processing 1000–10,000 blood samples daily. Eighty-five percent stated that their LIMS had a single field recording sex or gender information. Forty-three percent did not limit test access based on gender, but 68% did not append RIs for patients with unknown or indeterminate gender. Conclusions: This survey was the first to quantify how clinical laboratories manage sex and gender information and report results for transgender and non-binary patients, and details several key recommendations based on the survey responses. [ABSTRACT FROM AUTHOR]

This article discusses a case of a post-analytical error in a clinical laboratory that resulted in a misinterpretation of potassium levels and unnecessary treatment for hyperkalemia. The error occurred due to the omission of a comment about hemolysis in the test results. The article emphasizes the importance of including comments on specimen integrity, particularly regarding hemolysis, in test results, and highlights the need for automated detection of hemolysis, icterus, and lipemia in point-of-care devices. The laboratory has implemented re-education measures to prevent similar errors in the future. [Extracted from the article]

Introduction: Laboratory results play an essential role in both medical decision-making and inpatient management. In many clinical scenarios, laboratory test results are essential to make the right diagnosis or choosing the suitable treatment regimen. The aims and objectives were to study 13 National Accreditation Board for Testing and Calibration Laboratories (NABL)-specific common quality indicators (QIs) in the haematology laboratory of a tertiary care teaching hospital. Materials and Methods: NABL accredited a laboratory-based, cross-sectional study done in the haematology laboratory of NABH-recognised tertiary care teaching hospital over 5 years from January 2017 to April 2022 with a sample size of 1586,096. Quality parameters studied include sample rejection rates, sample redo rates, routine turnaround time (TAT), critical reports and their TAT, corrected reports, staining quality etc. The QI rates were calculated on a monthly basis, and trends were analysed. P < 0.05 was considered statistically significant. Results: The most common error was clotted sample 634 (0.04%), followed by rejection due to the misidentification of sample 128 (0.008%). Several monthly critical alerts showed an upward trend (P = 0.045) which could be attributed to increased awareness amongst laboratory staff. Redo rates showed no significant change in trend over the study period. Conclusion: Updating the knowledge on laboratory services, adequate training of the staff and sensitisation about the importance of the QIs in all three phases will help minimise errors.

Hyponatremia is the most frequent electrolyte disorder in hospitalized patients with increased mortality and morbidity. In this study, we evaluated the follow-up diagnostic, the risk of inadequate fast correction and the outcome of patients with profound hyponatremia (pHN), defined as a blood sodium concentration below 120 mmol/L. The aim was to identify a promising approach for a laboratory-based clinical decision support system (CDSS). This retrospective study included 378,980 blood sodium measurements of 83,315 cases at a German tertiary care hospital. Hospitalized cases with pHN (n=211) were categorized into two groups by the time needed for a follow-up measurement to be performed (time to control, TTC) as either <12 h (group 1: "TTC≤12 h", n=118 cases) or >12 h (group 2: "TTC>12 h", n=93 cases). Length of hospital stay, sodium level at discharge, ward transfers, correction of hyponatremia, and risk of osmotic demyelination syndrome (ODS) due to inadequate fast correction were evaluated with regard to the TTC of sodium blood concentration. pHN was detected in 1,050 measurements (0.3%) in 211 cases. Cases, in which follow-up diagnostics took longer (TTC>12 h), achieved a significantly lower sodium correction during their hospitalization (11.2 vs. 16.7 mmol/L, p<0.001), were discharged more frequently in hyponatremic states (<135 mmol/L; 58 (62.4%) vs. 43 (36.4%), p<0.001) and at lower sodium blood levels (131.2 vs. 135.0 mmol/L, p<0.001). Furthermore, for these patients there was a trend toward an increased length of hospital stay (13.1 vs. 8.5 days, p=0.089), as well as an increased risk of inadequate fast correction (p<0.001). Our study shows that less frequent follow-up sodium measurements in pHN are associated with worse outcomes. Patients with a prolonged TTC are at risk of insufficient correction of hyponatremia, reduced sodium values at discharge, and possible overcorrection. Our results suggest that a CDSS that alerts treating physicians when a control time of >12 h is exceeded could improve patient care in the long term. We are initiating a prospective study to investigate the benefits of our self-invented CDSS (www.ampel.care) for patients with pHN. [ABSTRACT FROM AUTHOR]

Introduction: Laboratory results play an essential role in both medical decision-making and inpatient management. In many clinical scenarios, laboratory test results are essential to make the right diagnosis or choosing the suitable treatment regimen. The aims and objectives were to study 13 National Accreditation Board for Testing and Calibration Laboratories (NABL)-specific common quality indicators (QIs) in the haematology laboratory of a tertiary care teaching hospital. Materials and Methods: NABL accredited a laboratory-based, cross-sectional study done in the haematology laboratory of NABH-recognised tertiary care teaching hospital over 5 years from January 2017 to April 2022 with a sample size of 1586,096. Quality parameters studied include sample rejection rates, sample redo rates, routine turnaround time (TAT), critical reports and their TAT, corrected reports, staining quality etc. The QI rates were calculated on a monthly basis, and trends were analysed. P < 0.05 was considered statistically significant. Results: The most common error was clotted sample 634 (0.04%), followed by rejection due to the misidentification of sample 128 (0.008%). Several monthly critical alerts showed an upward trend (P = 0.045) which could be attributed to increased awareness amongst laboratory staff. Redo rates showed no significant change in trend over the study period. Conclusion: Updating the knowledge on laboratory services, adequate training of the staff and sensitisation about the importance of the QIs in all three phases will help minimise errors. [ABSTRACT FROM AUTHOR]

Background. Historically, paper-based laboratory reports were delivered by couriers to health facilities resulting in post-analytical delays. As a result, Short Message Service (SMS) printers were deployed to address this gap, the majority using the global data service platform (GDSP) to simplify deployment. In addition, these printers generate binary and quantitative information that can be used to assess utilization. Objectives. The objective of this study was to determine the costs and utilization of the SMS printer program in South Africa. Materials and Methods. A costing analysis for the 2020 calendar year was undertaken. We determined annual equivalent costs (AEC) for staffing, printers, fixed costs related to the national coordinator, consumables, travel costs, database support/hosting/dashboard development, printer repairs, and results transmission. The main outcome of interest was the cost per SMS printer result delivered. Data were extracted to assess utilization as follows: (i) months active (based on internet protocol data), (ii) signal, and (iii) battery strength. Results. There were 4,450,116 results delivered to printers that were situated at 2,232 primary healthcare facilities. An AEC of $687,727 was reported, with a cost per result delivered of $0.1618. The SMS printers contributed 73.52% to the total AEC. Overall, 90% of the printers were GDSP based, of which only 69.5% were determined to be active. The majority of active printers reported a signal strength =60% and a battery strength of =6 volts. Conclusions. Although the SMS printer program has the potential to reduce post-analytical delays, pathology services should migrate to an end-to-end electronic interface to improve patient care. [ABSTRACT FROM AUTHOR]

Background: Efficient Laboratory services are the backbone of the modern healthcare facility. 70% of all medical decisions are based on laboratory data. We need to assess errors in the testing process to reduce their negative effect on patient outcomes and the entire healthcare sector. Objective: To assess total laboratory errors in terms of pre-analytical, analytical, post-analytical in the clinical chemistry laboratory. Materials and Methods: This cross-sectional study was conducted in Clinical Chemistry Laboratory, Sheikh Zayed Hospital, Rahim Yar Khan from 1st January to 30th June 2021. All blood samples received in Chemical Pathology Section for routine chemistry analysis in 6 months were included in the study using a consecutive sampling technique. 61891 blood samples were assessed for the following pre-analytical errors: Hemolysis, icterus, lipemia, incorrect order of draw, insufficient quantity, wrong tube, mislabeled specimen, missed patient information. Analytical errors were a violation of westgard rules while post-analytical errors included uninformed critical results, prolonged turnaround time and data transcription errors. Urine and other body fluids such as cerebrospinal fluid (CSF), ascitic fluid, pleural fluid, pericardial fluid received for chemical analysis were excluded. Data analysis was done using SPSS 16. Results: Out of the total laboratory errors 5574(9%), pre-analytical errors were the most frequently occurring errors (80.95%) followed by post-analytical errors (18.25%) and analytical errors (0.80%). The most frequently occurring pre-analytical error was hemolysis (64.38% of 80.95%). The most frequently occurring post-analytical error was uninformed critical results (70.79% of 18.25%). Conclusion: Pre-analytical errors have the highest percentage in total laboratory errors followed by post-analytical errors. Errors in the analytical phase are less due to Internal Quality Control & laboratory automation

OBJECTIVE: To assess the key performance indicators and the laboratory errors in the hematology laboratory. METHODOLOGY: A cross-sectional study was conducted at the DDRRL Hematology laboratory from October 2021 to September 2022. Data from the blood bank and hematological laboratory were collected. The primary investigator managed every step of the data-gathering operation. All the tools required for the process were gathered and arranged on a tray or trolley to be safe, accessible, and readily visible. Sterile glass or plastic tubes with rubber covers were used for blood collection. The information acquired during the study was inserted into a computer using an Excel sheet. SPSS version 20 was used for the analysis. All samples from the hematology section of DDRRL were included in this study, while all error-free samples were excluded. RESULT: From July to December, 414,400 hematology request forms were collected from OPD, private wards, IPD and Emergency. Overall, 2376 (0.573%) hematology laboratory errors were detected, of which 419 were Pre-analytical errors, 122 were analytical, and 1834 were post-analytical errors. CONCLUSION: We can lower the errors' likelihood if we appropriately handle the pre-analytical variables. Additionally, care must be taken when training workers to minimize the possibility of mistakes. [ABSTRACT FROM AUTHOR]

ISO 15189:2012 establishes the requirements for clinical sample management, ensuring quality of process and laboratory information management. The accreditation authority, ENAC in Spain, established the requirements for the authorized use of the label in reports issued by accredited laboratories. These recommendations are applicable to the postanalytical processes and the professionals involved. The Standard requires laboratories to define and document the duration and conditions of sample retention. Laboratories are also required to design an internal quality control scheme to verify whether postanalytical activities attain the expected standards. Information management requirements are also established and laboratories are required to design a contingency plan to ensure the communication of laboratory results. Instructions are finally provided about the correct use of the accreditation label in laboratory reports. A range of nations and scientific societies support that clinical laboratories should be required to obtain accreditation. With ISO 15189 being the most specific standard for demonstrating technical performance, a clear understanding of its requirements is essential for proper implementation.

Background: Since its detection in December 2019 in the city of Wuhan, China, the COVID-19 pandemic has grappled the world. Laboratories have been central in the diagnosis, prognosis and therapeutic monitoring of COVID-19 patients. With this pandemic spreading, laboratory personnel have become vital in the efforts to halt the advance of the virus. Aims and Objective: In this article, we will address various concerns in all the three phases of testing of the COVID-19 blood and serum samples in a clinical chemistry laboratory and discuss the issues pertaining to a resource-limited setting. Materials and Methods: International, national and regional guidelines on bio-safety and operational management available at the time of preparation of this manuscript were analyzed. Additionally, literature search through PubMed was done on the keywords “bio-safety”, “pre-analytical”, “analytical”, “post-analytical” and “COVID-19”. Results: The pre-analytical, analytical, post analytical, general management problems we faced in our laboratory and the best practices that we followed to address the same has been included in this paper. Conclusion: Some unprecedented challenges the laboratories have encountered during this outbreak are maintaining the lab safety of highest standards, management of human resource while sustaining the quality of testing. Laboratories will have to constantly innovate in order to meet the demands of this outbreak.

D-dimer is a multifaceted biomarker of concomitant activation of coagulation and fibrinolysis, which is routinely used for ruling out pulmonary embolism (PE) and/or deep vein thrombosis (DVT) combined with a clinical pretest probability assessment. The intended use of the tests depends largely on the assay used, and local guidance should be applied. D-dimer testing may suffer from diagnostic errors occurring throughout the pre-analytical, analytical, and post-analytical phases of the testing process. This review aims to provide an overview of D-dimer testing and its value in diagnosing PE and discusses the variables that may impact the quality of its laboratory assessment.

Background: Quality Indicators are utilized globally to collect data from its documentation, to identify the recent most effective performance criteria as well as to reduce errors in the total testing process. However, it is essential to maintain the credibility of the tools by close monitoring with effective and correct record keeping. The Quality Indicators monitors and controls the total testing process which includes the Pre-analytical, Analytical and Post-Analytical Phases. The present study is necessary to study the status of quality of testing processes and to set quality goals and to achieve those goals by monitoring and assessing those quality indicators. Aims and Objective: To study the Quality Indicators of Clinical Biochemistry Laboratory. Material & Methods: The Quality Indicators were studied and analyzed post-recording and monitoring on daily basis from August 2019 to December 2019 in Clinical Biochemistry Laboratory. Result: The present study indicates significant occurrence of errors in Pre-analytical phase Quality Indicators as compared to Post-Analytical and Analytical Phases. The major challenge for the documentation of Quality Indicators indicate a requirement for round-the-clock basis monitoring to record the deviations in the total testing process as observed in the present study. Conclusion: The present study emphasizes upon the necessity of monitoring the Quality Indicators in clinical laboratories. The selected Quality Indicators should be specific, sensitive and diagnostically appropriate and relevant to the various test profiles utilized in clinical laboratories. The Quality Indicators improve accuracy and precision, sets benchmark for laboratory performance for both within and inter-laboratory comparisons which enables decision making and set priorities post-corrective actions which supports accountability, quality improvement and accreditation. [ABSTRACT FROM AUTHOR]

• Harmonization of lipid profiles across European laboratories is poor. • Two-thirds of laboratories use nonfasting lipid measurements. • Less than 50% of laboratories flag guideline-recommended LDLC thresholds. • Less than 50% of laboratories automatically calculate non-HDLC. • Less than one-fourth of laboratories apply alert values for FH. The CArdiac MARker Guidelines Uptake in Europe Study (CAMARGUE) initiated by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) aims to survey the current use of evidence-based guidelines for dyslipidemia testing in Europe. In 2019 a web-based questionnaire was distributed via EFLM National Societies to clinical laboratories in Europe. Questions covered pre-analytics, analytical methods, measurement units, flagging of decision thresholds, and use of decision-enhancing comments. Returns were obtained from 452 laboratories from 28 countries. Most laboratories always use nonfasting blood samples for lipid assays (66%). Lipid profiles are reported in mmol/L by 59% of the laboratories, mainly from 14 countries promoting the use of SI units. Important differences in flagging of decision thresholds were observed, with less than half of the laboratories applying the guideline-recommended LDL cholesterol threshold. Only 17% of the laboratories add an alert comment when familial hypercholesterolemia is suspected and 23% when risk of pancreatitis from hypertriglyceridemia is high. There are marked differences among laboratories in Europe in terms of pre-analytical, analytical, and post-analytical lipid management that could have an important clinical impact. This relates to different availability of assays or different laboratory practices on reporting and flagging of lipid profiles. [ABSTRACT FROM AUTHOR]

Background: Since its detection in December 2019 in the city of Wuhan, China, the COVID-19 pandemic has grappled the world. Laboratories have been central in the diagnosis, prognosis and therapeutic monitoring of COVID-19 patients. With this pandemic spreading, laboratory personnel have become vital in the efforts to halt the advance of the virus. Aims and Objective: In this article, we will address various concerns in all the three phases of testing of the COVID-19 blood and serum samples in a clinical chemistry laboratory and discuss the issues pertaining to a resource-limited setting. Materials and Methods: International, national and regional guidelines on bio-safety and operational management available at the time of preparation of this manuscript were analyzed. Additionally, literature search through PubMed was done on the keywords "biosafety", "pre-analytical", "analytical", "post-analytical" and "COVID-19". Results: The pre-analytical, analytical, post analytical, general management problems we faced in our laboratory and the best practices that we followed to address the same has been included in this paper. Conclusion: Some unprecedented challenges the laboratories have encountered during this outbreak are maintaining the lab safety of highest standards, management of human resource while sustaining the quality of testing. Laboratories will have to constantly innovate in order to meet the demands of this outbreak. [ABSTRACT FROM AUTHOR]

Background and aims: The importance of clinical laboratories work and test results is clearly related with the community health. This study aimed to evaluate the variety and rate of Pre and Post-Analytical errors among reception staff in clinical laboratories of governmental, private and military hospitals. Methods: In this cross-sectional descriptive study, 183 of reception staff of clinical laboratories in governmental, private and military hospitals from Tehran and Tabriz Cities were enrolled. The required data was collected using a self-designed specific form (voluntary human error reporting Form). At first, the CTA (Cognitive Task analysis) method was used to elicit the cognitive task demands and identify the probable human errors. The data collection form was designed based on the obtained results and distributed in study population. After 6 months, the fulfilled forms were collected and the reported data were analyzed using some statistical tests such as chi-square. . Results: According to the results, the study population was young (mean age 33.86 ± 6.92 years) with a relatively low experience (7.75± 6.72 years). 14 various human errors were identified in studied tasks via CTA method. The 93% of subjects reported at least one error during study period and a total of 1188 errors were reported by individuals. The error report rate in pre and post- analytical phases were 57.4% and 42.6%, respectively. Conclusion: Because of the relatively high variety and rate of reported errors and also, the importance of laboratory errors in the medical diagnosis and treatment, it is necessitate to record, analysis and control of human errors in medical laboratory tasks.

Magnesium (Mg 2+ ) is a predominantly intracellular cation that plays significant roles in various enzymatic, membrane, and structural body functions. As a calcium (Ca 2+ ) antagonist, it is imperative for numerous neuromuscular activities. The imbalance of body Mg 2+  concentration leads to clinical manifestations ranging from asymptomatic to severe life-threatening complications. Therefore, the contribution of Mg 2+ measurement regarding various laboratory and clinical aspects cannot be ignored. Mg 2+ is often described as the forgotten analyte. However, its close relationship with body potassium (K + ), Ca 2+, and phosphate homeostasis proves that Mg 2+ imbalance could co-exist as the root cause or the consequence of other electrolyte disorders. Meanwhile, several preanalytical, analytical, and postanalytical aspects could influence Mg 2+ measurement. This review highlights Mg 2+ measurement's laboratory and clinical issues and some analyte disturbances associated with its imbalance. Understanding this basis could aid clinicians and laboratory professionals in Mg 2+  result interpretation and patient management., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Ab Rahim et al.)

Introduction: Quality indicators in a clinical laboratory are considered as useful tools for continual improvement of the laboratory services. Aim: The aim of this study was to assess timely performance of the NARI service laboratories in three phases of testing - pre-analytical, analytical and post-analytical, in an effort to improve their performance. Methodology: The study included an assessment of different quality indicators from six laboratories - Clinical Biochemistry, Hematology, Serology, Microbiology, Virology and Immunology at the NARI central laboratory which provide service for the patient care. Results: Data obtained from a total of 39139 clinical samples collected over a period of two years was used in the study. The overall error rate was found to be 2.72%. The commonly observed indicators were revision of the laboratory requisition form (0.49%) and sample rejection (0.31%) during the pre-analytical phase, equipment breakdown (0.12%) and failure of the controls (0.03%) during the analytical phase, turnaround time (1.55%) and revision of the report form (0.15%) during the post- analytical phase. Conclusions: Quality indicators are important tools in improving the quality system in a clinical laboratory and patient care.

Analytical performance specifications can be based on three different models: the effect of analytical performance on clinical outcome, based on components of biological variation of the measurand or based on state-of-the-art. Models 1 and 3 may to some degree be combined by using case histories presented to a large number of clinicians. The Norwegian Quality Improvement of Primary Care Laboratories (Noklus) has integrated vignettes in its external quality assessment programme since 1991, focusing on typical clinical situations in primary care. Haemoglobin, erythrocyte sedimentation rate (ESR), HbA1c, glucose, u-albumin, creatinine/estimated glomerular filtration rate (eGFR), and Internationl Normalised Ratio (INR) have been evaluated focusing on critical differences in test results, i.e., a change from a previous result that will generate an 'action' such as a change in treatment or follow-up of the patient. These critical differences, stated by physicians, can translate into reference change values (RCVs) and assumed analytical performance can be calculated. In general, assessments of RCVs and therefore performance specifications vary both within and between groups of doctors, but with no or minor differences regarding specialisation, age or sex of the general practitioner. In some instances state-of-the-art analytical performance could not meet clinical demands using 95% confidence, whereas clinical demands were met using 80% confidence in nearly all instances. RCVs from vignettes should probably not be used on their own as a basis for setting analytical performance specifications, since clinicians seem 'uninformed' regarding important principles. They could rather be used as a background for focus groups of 'informed' physicians in discussions of performance specifications tailored to 'typical' clinical situations. [ABSTRACT FROM AUTHOR]

Quality in healthcare is ideally at an optimal benchmark, but must be at least above the minimal standards for care. While laboratory quality is ideally judged in clinical terms, laboratory medicine has also used biological variations and state-of-the-art criteria when, as is often the case, clinical outcome studies or clinical consensus are not available. The post-analytical phase involves taking quality technical results and providing the means for clinical interpretation in the report. Reference intervals are commonly used as a basis for data interpretation; however, laboratories vary in the reference intervals they use, even when analysis is similar. Reference intervals may have greater clinical value if they are both optimised to account for physiological individuality, as well as if they are harmonised through professional consensus. Clinical decision limits are generally superior to reference intervals as a basis for interpretation because they address the specific clinical concern in any patient. As well as providing quality data and interpretation, the knowledge of laboratory experts can be used to provide targeted procedural knowledge in a patient report. Most profoundly critically abnormal results should to be acted upon to minimise the risk of mortality. The three steps in quality report interpretation, (i) describing the abnormal data, (ii) interpreting the clinical information within that data and (iii) providing knowledge for clinical follow-up, highlight that the quality of all laboratory testing is reflected in its impact on clinical management and improving patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Currently, more than two-thirds of medical decisions are made based on laboratory test results. However, due to the compromised pre-analytical and post-analytical phases (or extra-analytical phase), the reporting of incorrect or inappropriate test results was still prevalent. Studies focusing on the prevalence of and factors associated with laboratory error remain very limited in Ethiopia., Objective: This study aimed to assess the magnitude of extra-analytical errors and associated factors in medical laboratory services in 13 public hospitals in Addis Ababa, Ethiopia, from January to April 2020., Materials and Methods: A hospital-based cross-sectional study was conducted in the medical laboratories of public hospitals in Addis Ababa from January to April 2020 to assess extra-analytical errors and associated factors. Data were collected from 2401 laboratory request forms ordered within the study period and 169 laboratory professionals working in public hospitals. The collected data were entered and analyzed using SPSS version 23 software. Data were analyzed using simple descriptive statistics, percentages, and frequencies and summarized using tables and text. Bivariate logistic regression analysis was conducted, and variables (with a p value below 0.25) were included in the multivariate logistic regression model. A p value <0.05 was considered a cutoff point in the final model., Results: In this study, of the errors detected, 60.3% occurred in the pre-analytical phase and 39.7% in the post-analytical phase. Extra-analytical errors in laboratory services were significantly associated with lack of written procedures for laboratory activities (adjusted odds ratio = 2.79, 95% confidence interval = 1.34-5.86), 1-2 years of work experience (adjusted odds ratio = 5.5, 95% confidence interval = 2.54-9.31), work experience (3-5 years) (adjusted odds ratio = 2.67, 95% confidence interval = 0.94-4.56), and education (diploma) (adjusted odds ratio = 6.30, 95% confidence interval = 2.17-12.26)., Conclusion: This study discovered errors in the pre-analytical (60.3%) and post-analytical (39.7%) phases, and none of the requisition papers had complete data. This frequency may be affected by workload, a lack of written procedures, the number of years of work experience, and the level of education of the staff., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Background: Proficient laboratory service is the cornerstone of modern healthcare systems and has an impact on over 70% of medical decisions on admission, discharge, and medications. In recent years, there is an increasing awareness of the importance of errors in laboratory practice and their possible negative impact on patient outcomes. Aim: We retrospectively analyzed data spanning a period of 3 years on analytical errors observed in our laboratory. The data covered errors over the whole testing cycle including pre-, intra-, and post-analytical phases and discussed strategies pertinent to our settings to minimize their occurrence. Materials and Methods: We described the occurrence of pre-analytical, analytical and post-analytical errors observed at the Komfo Anokye Teaching Hospital clinical biochemistry laboratory during a 3-year period from January, 2010 to December, 2012. Data were analyzed with Graph Pad Prism 5(GraphPad Software Inc. CA USA). Results: A total of 589,510 tests was performed on 188,503 outpatients and hospitalized patients. The overall error rate for the 3 years was 4.7% (27,520/58,950). Pre-analytical, analytical and post-analytical errors contributed 3.7% (2210/58,950), 0.1% (108/58,950), and 0.9% (512/58,950), respectively. The number of tests reduced significantly over the 3-year period, but this did not correspond with a reduction in the overall error rate (P = 0.90) along with the years. Conclusion: Analytical errors are embedded within our total process setup especially pre-analytical and post-analytical phases. Strategic measures including quality assessment programs for staff involved in pre-analytical processes should be intensified. [ABSTRACT FROM AUTHOR]

Abstract: Harmonisation is likely to be an important contributor to ensure high quality laboratory testing, thus potentially improving patient outcome. Efforts for harmonisation must be made in the total testing process, from test requesting to communication of the laboratory test results and its consequences to the patient. In this article, suggestions are given about what level of harmonisation is possible at the various steps of the testing process, who could be responsible for facilitating and monitoring the effects of harmonisation, and what are likely barriers to achieving harmonisation. Harmonisation can be achieved at local, national and international levels, and will be most challenging when it involves more than one profession as in the extra-analytical phases. Key facilitators will be laboratory associations, regulatory bodies and accreditation systems, whereas barriers are likely to be reimbursement systems or economic factors, opinion leaders and manufacturers. A challenge is to try to turn barriers into facilitators. Harmonisation effects can in most settings be monitored by external quality assurance organisations provided that schemes are expanded to cover all relevant steps and phases. We must combine our efforts, both within our profession as well as in cooperation with others, to achieve harmonisation of the total testing process, in the best interests of the patient. [Copyright &y& Elsevier]

The worldwide clinical and scientific interest in peptides belonging to the insulin-like growth factor (IGF) system has brought along a call for standardization of assays used to quantify the different IGF related proteins. This relates in particular to the measurement of IGF-I, which has stood the test of time as an important biochemical tool in the diagnosis and treatment of growth hormone (GH) related disorders. The first international consensus statement on the measurement of IGF-I in 2011 represents an important milestone and will undoubtedly improve commutability of reference ranges for IGF-I and clinically applicable cut-off values. By contrast, there is no consensus addressing the measurements of the other IGF-related peptides. Nevertheless, measurement of these peptides may be of interest, either as additional tools in GH disorders or as prognostic biomarkers of various diseases. Therefore, standardization of assays for the other IGF-related peptides is highly relevant. This chapter discusses the recent consensus on IGF-I measurements and how this approach may be applied to measurement of the other IGF-related peptides. In addition, assay pitfalls, pre- and post-analytical challenges, alternative methods for IGF-I measurements and potential assays of tomorrow will be discussed. [Copyright &y& Elsevier]

Background: A national cross-sectional survey on the reporting of critical values was conducted to provide suggestions on monitoring of the quality indicator and obtain the goal of quality improvement. Methods: All clinical laboratories participating in the external quality assessment (EQA) programs of chemistry, blood gas, and hematology tests organized by the National Center for Clinical Laboratories (NCCL) were enrolled in our study. General information on the policy of critical values reporting and the particular problems about critical limits and practice of critical values reporting in the last 2 months were asked in the questionnaire. All collected data were analyzed by the special statistical software designed by the NCCL. Results: The return rate of surveys for critical values on clinical biochemistry, blood gas, and hematology testing were 46.11%, 41.14%, and 39.42%, respectively. Most laboratories in the surveys suggested they set different critical limits for children and adults. The analytes of critical values chosen most frequently were potassium, glucose, sodium, calcium, pH, pCO2, pO2, white blood cell (WBC) count, hemoglobin (Hb), prothrombin time (PT), activated partial thromboplastin time, and fibrinogen. The analytes with most critical values were potassium, blood gas, and creatinine for clinical biochemistry, pCO2 for blood gas, and WBC, Hb, and PT for hematology testing. The medians of critical limits for potassium, sodium, calcium, and glucose were not significantly different from the results of the national survey conducted by Kost in 1990. Conclusions: Remarkable inter-laboratory difference in the development and implementation of critical values reporting procedure were found. Laboratories should communicate with clinicians to obtain consensus on the analytes and limits of critical values. [ABSTRACT FROM AUTHOR]

The endocrine laboratory must provide accurate and timely results for the critically ill patient. A number of pathophysiological factors affect assay systems for adrenal, thyroid and gonadal function tests. The effects are primarily on estimates of ‘free hormone’ concentration through abnormal binding protein concentrations and the effects of drugs and metabolites on hormone-protein binding. The limitations of the principal analytical techniques (immunoassay and chromatography-mass spectrometry) include drug effects, endogenous antibody interference and ion suppression. These effects are not always easily identified. Analytical specificity and standardisation result in differences in bias between assays and thus a requirement for assay specific decision limits and reference ranges. Good communication between clinician and laboratory is needed to minimise these effects. Developments in mass spectrometry should lead to greater sensitivity and wider applicability of the technique. International efforts to develop higher order reference materials and reference method procedures should lead to greater comparability of results. [Copyright &y& Elsevier]

Context: Implementation of quality management system (QMS) which encompasses various quality indicators (QIs), can serve as a stepping stone for continuous improvement & help in achieving globally accepted quality standards in a diagnostic laboratory., Aims: To generate preliminary data on trends of post-analytical QIs in Bacteriology section., Settings and Design: A pilot study was conducted at a tertiary care teaching hospital located in Rishikesh, Uttarakhand., Methods and Material: Data of the following four quality indicators pertaining to aerobic culture and sensitivity testing of various clinical samples received in Clinical Bacteriology laboratory was compiled and retrospectively analysed: (i) Rate of reporting errors; (ii) Rate of re-dos; (iii) Percentage of reports correlating with clinical diagnosis; (iv) Percentage of adherence to safety precautions by employees working in diagnostics., Statistical Analysis Used: Descriptive statistics like mean and frequency distribution plots., Results: The mean reporting error rate was 0.12 per 1000 tests. It was consistently low from July 2018 to May 2019, after which an overall increasing trend was observed. The mean rate of re-dos was 2.79 per 1000 tests. An overall decreasing trend was observed with maximum rates during the months of December 2017 and January 2018. On an average only 7.86% of the reports co-related with clinical diagnosis. Almost 100% adherence to safety precautions was observed with the exception of two instances of needle stick injuries (NSIs)., Conclusions: Commitment of laboratory personnel in adopting, maintaining and analysing QMS data will lead to further strengthening of our existing healthcare system., (Copyright © 2020 Indian Association of Medical Microbiologists. Published by Elsevier B.V. All rights reserved.)

We determined the relative strengths of association between 23 most commonly ordered laboratory tests and the adverse outcome as indicators of relative criticalness. The lowest and highest results for 23 most commonly ordered laboratory tests, 24 hours prior to death during critical care unit (CCU) stay or discharge from CCU were extracted from a publicly available CCU database (Medical Information Mart for Intensive Care-III). Following this, the Random Forest model was applied to assess the association between the laboratory results and the outcomes (death or discharge). The mean decrease in Gini coefficient for each laboratory test was then ranked as an indication of their relative importance to the outcome of a patient. In descending order, the 10 laboratory tests with the strongest association with death were: bicarbonate, phosphate, anion gap, white cell count (total), partial thromboplastin time, platelet, total calcium, chloride, glucose and INR; moreover, the strength of association was different for critically high versus low results., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Using a questionnaire, we have evaluated how VKA and INR are handled by medical doctors in Quercy-Rouergue. This evaluation is part of an international post-analytical quality assessment survey in laboratory medicine supervised by Noklus (http://www.noklus.no/). The original questionnaire designed by Noklus has been adapted to our local practices in replacing warfarin by fluindione. The « Centre de référence et d'éducation aux antithrombotiques d'Ile de France » (Creatif) also participated. Of 282 medical doctors who were sent the questionnaire 109 filled it in, 62% of them being general practitioners. For a target INR at 2.5, the thresholds used to change the dose of VKA range between 1.3 and 2.3 for low values, and between 2.8 and 4 for high values. The bleeding or ischemic risks of being under VKA, versus of not being under VKA, are largely overestimated. INR measurements also tend to be too frequent in stable, and even more so in overdosed, patients. In case of INR at 4.8 only 59% of the participants implement the recommendation of la Haute autorité de santé (HAS) and le Groupe d'étude sur l'hémostase et la thrombose (GEHT) which consists of skipping one dose of VKA, and the attitudes also diverge regarding the importance of the VKA dose reduction, and the number of days under reduced dose before the next INR measurement, the attitude of the Creatif being barely predominant among the participants, and slightly different from that recommended by the HAS and the GEHT. In conclusion, despite the limitations of our methods (the analysis of a questionnaire being less close to the truth than an analysis of actual practices), our evaluation points to the heterogeneity in the knowledge about, and in handling, VKA and INR regarding more particularly management of overdosing, and the estimation of bleeding or ischemic risks, despite the availability of supposedly clear and simple practice guidelines.