Preanalytical Errors Research Articles

From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review.

This scoping review focuses on the evolution of pre-analytical errors (PAEs) in medical laboratories, a critical area with significant implications for patient care, healthcare costs, hospital length of stay, and operational efficiency. The Covidence Review tool was used to formulate the keywords, and then a comprehensive literature search was performed using several databases, importing the search results directly into Covidence (n=379). Title, abstract screening, duplicate removal, and full-text screening were done. The retrieved studies (n=232) were scanned for eligibility (n=228) and included in the review (n=83), and the results were summarised in a PRISMA flow chart. The review highlights the role of healthcare professionals in preventing PAEs in specimen collection and processing, as well as analyses. The review also discusses the use and advancements of artificial intelligence (AI) and machine learning in reducing PAEs and identifies inadequacies in standard definitions, measurement units, and education strategies. It demonstrates the need for further research to ensure model validation, address the regulatory validation of Risk Probability Indexation (RPI) models and consider regulatory, safety, and privacy concerns. The review suggests that comprehensive studies on the effectiveness of AI and software platforms in real-world settings and their implementation in healthcare are lacking, presenting opportunities for further research to advance patient care and improve the management of PAEs.

Improvement Plan for the Pre-Analytical Process of the SEMEDICLAB Laboratory Period 2022

Objective: SEMEDIC is a clinical laboratory that performs tests in the areas of hematology, biochemistry, urinalysis, immunology, coprology, and immunochemistry. This work aims to implement a continuous improvement plan for the pre-analytical process of the SEMEDICLAB laboratory in 2022. Theoretical Framework: The research focuses on pre-analytical errors in clinical laboratories and their impact on the quality of results. It is based on the premise that, despite technological advances and automation, the pre-analytical phase remains a weak link in the clinical analysis process. Method: The present study adopts an observational and descriptive methodology, as it allows for the visualization of the environment in which the research is carried out. It should be noted that no population or sample was considered; it was based on the identification, definition, and standardization of sub-processes of the SEMEDICLAB company process. Clause 5.4 of the ISO 15189:2012 checklist was used to identify the gap between the sub-processes currently completed. Results and Discussion: The causes of the problem in the pre-analytical phase of the workers in the SEMEDICLAB laboratory were described, which were caused by non-compliance or omission of the ISO 15189: 2012 standard, related to clauses 5.4.2. "Information for patients and users," 5.4.4.2. "Instructions for pre-analytical activities," and 5.4.6 "Sample reception," where irregularities were observed. Implications of the research: Research on pre-analytical errors has a direct impact on the quality of patient care, the efficiency of clinical laboratories, and the sustainability of health systems. By identifying the causes of these errors and developing strategies to prevent them, it contributes to improving patient safety and the reliability of laboratory results. Originality/Value: The value of this type of research is multifaceted. Firstly, it contributes to improving the quality of patient care by reducing the incidence of erroneous laboratory results, which in turn reduces the risk of misdiagnosis and inappropriate treatment. Secondly, it optimizes processes in clinical laboratories, increasing efficiency and reducing costs associated with the repetition of tests and error management. Thirdly, this research promotes the development of standards and clinical practice guidelines for the prevention and management of pre-analytical errors, which helps to ensure the quality and safety of laboratory services at the national and international level.

Potential of role play as an educational tool in biochemistry to facilitate medical education.

Commonly used traditional didactic lecture in biochemistry being non-interactive has several disadvantages which students find boring and difficult to retain. This study reviews the potential of role play to teach biochemistry effectively. Studies published till June 2024 on the topic role play in medical education and biochemistry were searched using 'Ovid Discovery' software showing studies available in PubMed, Embase, and Cochrane databases. Studies having matched keywords like 'role play, roleplay, role-play, education, medical, biochemistry and genetics' appearing in title or text article were included while studies that were irrelevant, in non-English language or duplicated studies were excluded. Literature search revealed 8 studies for reviewing the topic. Studies that have tested effectiveness of role play in biochemistry have shown that it can bridge the gap between theory and practice. Role play is dramatization of a theme simulating real-life scenarios evoking learner's critical thinking process, activation of cognitive, psychomotor, and affective domains. It creates lasting memory in retaining topics besides motivating student for self-directed learning. It also develops confidence, communication, and language skills among students. Role play can be a powerful tool to teach biochemistry for integrating knowledge of biochemistry with clinical concepts. The authors recommend that biochemistry lectures and practical sessions should be reinforced through role plays especially for topics having clinical relevance. The author proposes several applications of role play in biochemistry to demonstrate metabolic pathways, experimental skills, metabolic disorders, accidental emergencies in lab, do's and don'ts in labs, pre analytical errors affecting biochemistry lab results.

Corrigendum to “Avoid Preanalytical Errors When Using Urine Biomarkers of Exposure” [Kidney International Reports Volume 10, Issue 1, January 2025, Page 281

Corrigendum to “Avoid Preanalytical Errors When Using Urine Biomarkers of Exposure” [Kidney International Reports Volume 10, Issue 1, January 2025, Page 281

Evaluation of performance in preanalytical phase EQA: can laboratories mitigate common pitfalls?

Preanalytical phase is an elemental part of laboratory diagnostics, but is prone to humane errors. The aim of this study was to evaluate performance in preanalytical phase external quality assessment (EQA) cases. We also suggest preventive actions for risk mitigation. We included 12 EQA rounds (Labquality Ltd.) with three patient cases (36 cases, 54-111 participants, 7-15 countries) published in 2018-2023. We graded performance according to percentage of correct responses in each case as≥900 % excellent, 70-89 % good, 50-69 % satisfactory, 30-49 % fair and <30 % poor. Performance was simultaneously failed with≥10 % of responses leading to harmful events. Overall performance was excellent in 7, good in 12, satisfactory in 10, fair in 4 and poor in 3 cases. Additionally, 7 cases showed failed performance. Routine requests with incorrect sample tubes or incorrect sample handling were detected with good performance. Lower performance was seen with sudden abnormal results, with rare requests, with false patient identification (never-events) and with incorrect test requests. Information technology (IT) solutions (preanalytical checklists, autoverification rules and patient specific notifications) could have prevented 33 of 36 preanalytical errors. While most common errors were detected with good performance, samples with rare requests or those requiring individualised consideration are vulnerable to human misinterpretation. In many instances, samples with preanalytical errors should have been identified and rejected before reaching the laboratory or being directed to analysis. Optimising IT solutions to effectively detect these preanalytical errors allows for focus on infrequent events demanding accessible professional consultation. EQA preanalytical cases may help in education of correct actions in these occasions.

Analysis of Preanalytical Errors in Clinical Biochemistry Laboratory of a Tertiary Care Hospital: A Retrospective Study

Introduction: Pre-analytical phase of laboratory testing is the most susceptible phase, as errors in this phase leads to more than 50% of erroneous results and often breaches the trust of the stakeholders on the quality of the laboratory results. Many pre-analytical errors occur during the pre-analytical phase, encompassing sample collection, labelling and transportationfactors often beyond the laboratory’s direct control. Aim: To determine the type and frequency of pre-analytical errors leading to sample rejection in clinical biochemistry laboratory. Materials and Methods: Being a retrospective descriptive study, convenient sampling was used to analyse sample rejection due to pre-analytical errors in clinical biochemistry laboratory of a tertiary care teaching hospital- PSG Institute of Medical Sciences and Research, Coimbatore, Tamil Nadu, India for a period of six months from May 2023 to October 2023. All the cases/blood samples from Outpatient Department (OPD) and Inpatient Department (IPD), received and rejected during this period were included under study. The data collection and analysis was done over a period of five months using the sample rejection and resample description from Laboratory Information System (LIS). Using Statistical Package for the Social Sciences (SPSS) version 28.0, data were summarised using descriptive statistics such as numbers and percentages. Results: During the six months period out of the total of 667454 samples, 1505 (0.23%) samples were rejected due to pre-analytical errors. The majority of the samples which were rejected were from IPD than OPD. Among the pre-analytical errors, haemolysis accounted for 806 (53.6%), clotted samples 256 (17%), delta check 217 (14.4%), insufficient sample 129 (8.6%), contamination 74 (4.9%), identification error 14 (0.9%), sample without request form 3 (0.2%) while missing samples, billing error, inappropriate tube, delay in transport and wrong test selection accounted for &lt;3 (0.1%). Conclusion: Haemolysis and clotted samples were the most common pre-analytical causes for sample rejection in the laboratory. The samples from IPD were rejected more often than OPD due to incorrect phlebotomy techniques. This accentuates the need for proper hands-on phlebotomy training sessions for novice nurses following their recruitment, as their competency will be instrumental in bringing down the errors in pre-analytical phase.

Monitoring and Eliminating Pre-Analytic Laboratory Errors in an Acute Care Setup - A Case Study

Laboratory investigations are an integral part of patient management. The number and frequency of investigations are directly related to the clinical seriousness of a patient. Hence acute care setups observe a high volume as well as frequency of sampling for laboratory analyses. Many management plans are dependent on the results of these investigations. So, there is also pressure on the pathology laboratory to provide the results as early as possible. The whole process of lab investigation requires ordering an investigation, sending the requisition/system indenture, sampling, transporting sample to the lab, analysing, result approval and sending/uploading the report. Well-planned, tried, and tested standards/ protocols must be in place in order to eliminate the probability of errors in investigation reports. Laboratories must work according to some set specifications in order to process the samples in an error free manner. This paper will analyse the procedural steps, scope of errors and steps to identify, report as well as rectify the errors in the &amp;lt;i&amp;gt;pre-analytical phase&amp;lt;/i&amp;gt; of laboratory investigations in a highly demanding and accident-prone acute care setup. The aim of this exercise is to improve the quality of lab reporting process with an objective to eliminate pre analytic laboratory errors.

Screening for Fabry Disease-Related Mutations Among 829 Kidney Transplant Recipients.

Background/Objectives: Fabry disease (FD) is a genetic lysosomal storage disease caused by a pathogenic variant in GLA gene coding for a functional alpha-galactosidase A enzyme whose disfunction leads to globotriaosylceramide (Gb3) accumulation in cells, which results in multiple organ disorders. The aim of this study was to identify mutations associated with Fabry disease among 829 kidney transplant recipients and to investigate the correlation between the factors such as age, dialysis vintage, eGFR, proteinuria and corticosteroid dose and the deviations in alpha-galactosidase A and lyso-Gb3 levels. Methods: Dry blood spot samples were collected for genetic analysis. The GLA genetic variants were analysed by an amplicon-based next-generation sequencing approach in all female patients and in male patients with reduced alpha-galactosidase A levels. Alpha-galactosidase A and Lyso-Gb3 were not determined in female patients. Pearson's correlation coefficient was used to assess the relationship between the above-mentioned factors with the activity of alpha-galactosidase A and Lyso-Gb3. Results: Genetic testing was performed in 476 patients, all female patients (334), 69 male patients with decreased level of alpha-galactosidase A activity, one male patient with alpha-galactosidase A levels above the quantification limit and 72 male patients with no interpretable results of alpha-galactosidase A activity due to preanalytical error. In 3 (0.4%) male patients, hemizygous mutations associated with Fabry disease were found, and those were c.427G>A p.(Ala143Thr), c.1181T>C p.(Leu394Pro), and c.352C>T p.(Arg118Cys). The dose of corticosteroid therapy seemed to be positively correlated to alpha-galactosidase A activity and negatively to Lyso-Gb3 levels in blood. Conclusions: Genetic testing of individuals with chronic kidney disease and reporting of genetic variants associated with the Fabry phenotype are important to improve the overall knowledge of the disease. Further research is needed to define factors influencing levels of alpha-galactosidase A and Lyso-Gb3.

The hemolysis index as a tool for monitoring mild hemolysis in biochemical assays at the emergency laboratory

Hemolysis is a common pre-analytical error that can affect the accuracy of biochemical assay results. The aim of the study is to investigate the impact of hemolysis on the measurement of nine emergency biochemical parameters: glucose, creatinine, calcium, potassium, sodium, Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT),total bilirubin, and direct bilirubin. The study included blood samples collected from various units of the maternity hospital, including high-risk pregnancies follow-up, postpartum care, gynecology, neonatology, and intensive care. The study employs a Hemolysis Index (HI) to monitor and assess sample quality, determining their suitability for the analysis of the nine aforementioned biochemical parameters. The results reveal that hemolysis can significantly affect the accuracy of tests results for the studied parameters, particularly for potassium (increased 4-12 times) and AST (increased 1.47-48.55 times). Three of the studied substances showed a significant, negative, and moderate correlation with HI after the osmotic shock was induced, including AST (r = -0.501, p = 0.006), ALT (r = -0.516, p = 0.004), and sodium (r = -0.598, p = 0.001). Conversely, no significant association was found for the other parameters, which are: glucose (r = 0.079, p = 0.639); creatinine (r = 0.140, p = 0.402); direct bilirubin (r = 0.292, p = 0.075); total bilirubin (r = 0.272, p = 0.114); calcium (r = 0.215, p = 0.196); and potassium (r = -0.188, p = 0.258). Our findings indicate that HI may not be helpful for calculating a predicted value for samples with HI ranging between 87.30 and 295.9. Therefore, it is crucial to establish a threshold for the degree of hemolysis beyond which releasing the result would be considered potentially harmful to the patient especially new-borns and premature infants. In conclusion, the appropriate use of HI in clinical laboratories can enhance patient care quality by minimizing the risk of misdiagnosis leading to inappropriate treatment, particularly when requesting a second sample is not feasible.

Ascorbic acid and glucose can cause significant interference on quantitative measurement of biochemistry analytes in urine.

Preanalytical errors due to interferences can lead to inaccurate results, necessitating an understanding of potential interferences for each test. This study explores the impact of elevated concentrations of ascorbic acid and glucose on urine analysis, a pivotal diagnostic tool. Conducted at the Clinical Institute of Chemistry, KBC Sestre milosrdnice, the research utilized a 24-hour urine sample. Parameters assessed included total proteins, albumin, amylase, sodium, potassium, chlorides, calcium, phosphates, magnesium, creatinine, urea, and uric acid. Various concentrations of added interferents were prepared for duplicate measurements using statistical analysis in Microsoft Excel. No statistically significant interferences were found in albumin, amylase, sodium, potassium, or phosphate concentrations. However, ascorbic acid interfered with chloride, calcium, and magnesium determinations. Conversely, elevated glucose affected total protein, calcium, magnesium, creatinine, urea, and uric acid determinations. Interference of ascorbic acid with chloride and interference of glucose with total proteins and uric acid displayed a linear relationship. Results suggest cautious analysis interpretation from certain parameters in patients with elevated glucose and/or ascorbic acid in urine. Whereas ascorbic acid interference may go unnoticed due to its infrequent measurement, routine determination of glucose in urine is crucial, especially for diabetes patients.

From the Operating Theater to the Pathology Laboratory: Failure Mode, Effects, and Criticality Analysis of the Biological Samples Transfer.

Introduction: The frozen section intra-operative consultation is a pathology procedure that provides real-time evaluations of tissue samples during surgery, enabling quick and informed decisions. In the pre-analytical phase, errors related to sample collection, transport, and identification are common, and tools like failure mode, effects, and criticality analysis help identify and prevent risks. This study aims to enhance patient safety and diagnostic quality by analyzing risks and optimizing sample management. Materials and Methods: The failure mode, effects, and criticality analysis was conducted by a multidisciplinary team to analyze the workflow of frozen section sample handling from collection in the operating theater to acceptance at the pathology lab. Six steps were identified, each assigned tasks and responsibilities, with risks assessed through the risk priority number, calculated from severity, occurrence, and detectability. Severity was classified based on the WHO framework, ranging from "No Harm" to "Death", to prioritize risks effectively. Results: The study identified 12 failure modes across 11 sub-processes, prioritized by risk. Key failures included missing patient identification, incorrect sample retrieval, missing labels, misdirected samples, and samples sent to the wrong lab. Discussion: Pre-analytical errors in pathology pose risks to diagnosis and patient care, with most errors occurring in this phase. A multidisciplinary team identified key issues, such as sample mislabeling and delays due to staff unavailability, and implemented corrective actions, including improved signage, staff re-training, and sample tracking systems. Monitoring and regular checks ensured ongoing adherence to protocols and reduced the risks of misidentification, transport delays, and procedural errors. Conclusions: The frozen section intra-operative consultation is vital in surgical pathology, with the pre-analytical phase posing significant risks due to potential errors in sample handling and labeling. Failure mode, effects, and criticality analysis has proven effective in identifying and prioritizing these failures, despite resource demands, by allowing corrective actions that enhance patient safety and healthcare quality.

Appraisal of six sigma in pre-analytical phase of clinical biochemistry laboratory

Objectives: The aim of the study is to measure the performance of pre-analytical phase of a clinical biochemistry laboratory using sigma metrics and the six sigma scale. Materials and Methods: The study included documented data of blood sample rejection from March 2023 to February 2024 and follow-up data from March 2024 to August 2024. International Federation of Clinical Chemistry and Laboratory Medicine developed Quality Indicators (QIs) used are QI-9 Wrong tubes; QI-10 Hemolyzed samples; QI-11 Clotted samples; QI-12 Insufficient samples; QI-14 Damaged samples in transport; and QI-15 Mislabeled samples. Based on “Six Sigma Quality Design and Control” established by Dr. Westgard, the sigma metric was calculated for the above-mentioned QIs. Statistical analysis: Obtained data were entered and analyzed using Microsoft Excel 2021. Results: Out of 162,380 received samples, 547 samples were rejected as not satisfied with the sample acceptance criteria. The most common pre-analytical error in the observed QIs is hemolyzed samples (458), followed by insufficient sample volume (55). The Sigma score of QI-10 was determined to be 4.81, whereas QI-9, QI-11, QI-12, and QI-15 were well maintained and graded excellent. Following training sessions, the follow-up month revealed a sigma score of 4.98 for QI-10. Conclusions: Six sigma metrics are a competent means to measure the performance of pre-analytical QIs in a clinical biochemistry laboratory. The observed QIs were effectively managed (&gt;4 σ).

Strategies to Overcome Erroneous Outcomes in Reverse Transcription-Polymerase Chain Reaction (RT-PCR) Testing: Insights From the COVID-19 Pandemic.

The reverse transcription-polymerase chain reaction (RT-PCR) test to detect SARS-CoV-2, the virus causing COVID-19, has been regarded as the diagnostic gold standard. However, the excessive sensitivity of RT-PCR may cause false-positive outcomes from contamination. Again, its technical complexity increases the chances of false-negatives due to pre-analytical and analytical errors. This narrative review explores the elements contributing to inaccurate results during the COVID-19 pandemic and offers strategies to minimize these errors. False-positive results may occur due to specimen contamination, non-specific primer binding, residual viral RNA, and false-negatives, which may arise from improper sampling, timing, labeling, storage, low viral loads, mutations, and faulty test kits. Proposed mitigation strategies to enhance the accuracy of RT-PCR testing include comprehensive staff training in specimen collection, optimizing the timing of tests, analyzing multiple gene targets, incorporating clinical findings, workflow automation, and implementing stringent contamination control measures. Identifying and rectifying sources of error in RT-PCR diagnosis through quality control and standardized protocols is imperative for ensuring quality patient care and effective epidemic control.

Identifying and Addressing Errors in Anatomical Pathology: A Survey Analysis

Abstract Introduction/Objective To get an update on potential sources of pre-analytical, analytical, post-analytical and other sources of errors in anatomic pathology and strategies to mitigate such errors. Methods/Case Report The authors designed a 5-question survey in Google software and shared it widely on social media platforms. Results (if a Case Study enter NA) The survey, which garnered 43 responses from staff across various areas of the anatomic pathology laboratory, revealed significant insights. Labeling and fixation/preservation errors emerged as the most prevalent pre-analytical errors, while discrepancies between gross and microscopic examinations were common analytical errors. Specimen handling, inadequate clinical information, and transportation were the most frequently perceived other potential sources of errors. The implications of these findings are clear: robust protocols with multiple identifiers, staff training, and barcode labeling can significantly reduce patient identification errors. Similarly, standardized collection instructions, pre-labeled containers, and meticulous verification processes can effectively minimize such errors. Validated tests, standardized scoring systems, and proper investigation of quality control discrepancies are key to reducing analytical errors. Documented procedures, staff training, regular equipment calibration, and reagent testing are also crucial. Conclusion This study contributes to the literature on the current state of potential sources of errors in anatomic pathology. The study findings and recommendations on strategies to address such errors would improve the performance of the anatomic pathology laboratory and eventually improve patient care.

A-209 Preanalytical Phase Errors Constitute the Vast Majority of Errors in Clinical Laboratory Testing

Abstract Background Laboratory errors can occur during the preanalytical, analytic, or post-analytic phase of testing and may pose a considerable threat to patient safety. Studies have estimated that pre-analytical error encapsulates ∼45-68% of laboratory errors and occurs in up to 1.52% of specimens. However, limitations of previously published studies include the use of manual error detection, reliance on manual transcription, small study sizes, and exclusion of common errors. Herein, we aim to identify the types and frequency of errors occurring in each phase of clinical laboratory testing using a large retrospective dataset across a broad range of errors detected in clinical laboratories. Methods This study was performed in the Barnes-Jewish Hospital core laboratory which provides testing for a 1,400-bed tertiary care hospital and included all tests performed for clinical chemistry, special chemistry, toxicology, automated hematology, blood gas testing, coagulation, non-infectious serology, infectious disease serology, urinalysis, and send out testing between January 2022 and May 2023. Errors were compiled from two separate sources. The first source of errors was captured from the laboratory information system (LIS, Cerner). These errors were flagged manually by laboratory staff in real time. The second source of error was a daily report manually curated by a trained medial laboratory scientist as part of routine, laboratory operating procedures and standard workflow. Results There were ∼40,000,000 individual results from ∼11,000,000 specimens during the study period and 87,317 errors observed (∼0.8% of specimens). Of these errors, specimens that were hemolyzed sufficiently to impact result but still reportable were the majority (41,047, 47.2%). When excluding minimal hemolysis, there were 46,270 errors documented. Among these, 44,847 (97.0%) were in the preanalytical phase, 451 (1.0%) were in the analytical phase, and 972 (2.0%) occurred in the postanalytical phase. Subcategorization of preanalytical errors revealed that most of the errors were related to hemolyzed samples requiring results to be suppressed (n=19,701), quantity not sufficient samples (n=8,068), clotted specimens (n=5,840), collection errors (e.g., wrong tube type, n=5,780), not on ice (n=1,369) and IV fluid contamination (n=1,122). In the analytical phase, the causes of error were interfering substances (n=279), QC out of range (n=65), instrument problems (n=58) and reagent issues (n=49). Among the postanalytical errors, 581 were comment errors, 216 were results entry errors, 131 were comments errors with potential impact on patient care, and 44 were dilution errors. Conclusions This study demonstrates that the vast majority of lab errors (∼97.0%) occurring during the preanalytical phase. The high incidence of preanalytical errors, especially errors related to sample integrity implies a need for enhanced tools and training to minimizing errors from specimen collections, maintenance of sample stability, transportation, and processing.

A-057 Assessing Direct Renin Stability in EDTA Plasma Prior to Separation from Cells and Post-thaw

Abstract Background Renin is an enzyme secreted by the kidneys responsible for blood pressure regulation through the renin-angiotensin-aldosterone axis. Direct renin measurements are frequently used to investigate underlying causes of hypertension, including primary aldosteronism (PA), which is screened for using an aldosterone:renin ratio (ARR). Appropriate handling of renin samples in the preanalytical phase is critical, as cryoactivation of prorenin can occur when samples are refrigerated or cooled for extended periods of time, falsely elevating results. Manufacturer instructions for renin handling are often poorly defined and there is currently no consensus as to best handling practices. Two variables that frequently lead to renin sample rejections in our laboratory are time to centrifugation after collection and time kept at room temperature (RT). The objective of this study was to evaluate the stability of direct renin under ambient and freeze-thaw conditions in an effort to reduce test cancellations due to improper handling. Methods Plasma samples collected from five volunteers with consent in K2EDTA tubes were used for renin stability studies. Baseline renin samples were kept at RT for two hours after collection, centrifuged, measured, and subsequently frozen for post-thaw studies. To assess stability before separation from cells, samples kept at RT for two and four hours prior to centrifugation were assayed in triplicate for direct renin. For post-thaw stability studies, plasma samples were split into two aliquots each and frozen at -20⁰C for at least 24 hours, but no longer than 30 days. After removal from -20⁰C, one set of aliquots was thawed on the benchtop at RT and the second set was thawed in an RT water bath for up to one hour. Samples were centrifuged and assayed for direct renin in triplicate at baseline and six hours post-thaw. Direct renin was measured using the LIAISON XL chemiluminescent immunoassay (Diasorin). Bias was assessed after each treatment. The total allowable error (TEa) was ±2 pg/mL or ±20%. Results Measured renin concentrations ranged from 6.8-29.7 pg/mL. The percent bias in direct renin concentrations when comparing samples stored for two-hour and four-hour timepoints before centrifugation was 2.0% on average. Post-thaw studies comparing renin concentrations at the baseline and six-hour timepoints revealed an average percent bias of 13.1% and 12.2% for RT and water bath thawing methods, respectively. All samples tested were within the TEa. Conclusions Direct renin is stable in lavender K2EDTA tubes at RT for up to four hours, prior to centrifugation and separation from cells. Renin concentrations remained stable after storage at -20⁰C and thawing at RT for up to six hours, regardless of thawing method. By expanding direct renin stability criteria, we hope to reduce the number of cancellations due to preanalytical handling errors and prevent redundant phlebotomy for patients.

B-108 Delta Check Performance Assessment by Using Real-WorldData at the Temple University Health System​

Abstract Background Delta check is a post-analytic tool focusing on pre-analytical, analytical and post-analytical errors. It can be sensitive in detecting isolated errors affecting a single patient, as opposed to moving patient averages, which is another QC tool for detecting errors that affect a cohort/population of patients. As a computer-based system on selected tests, delta checks are to detect excessive changes from prior value in the patient test result and to detect possible specimen errors such as misidentified or compromised samples before results are reported. It may also play a role in detecting examination(analytical) issues and clinically significant results. If delta checks exceed established limits, the result is flagged. There is a common agreement that measurands with low indices of individuality (&amp;lt;0.6) make good candidates for the identification of cases of sample misidentification than higher indices of individuality (&amp;gt;1.4). CLSI EP33 Use of Delta Checks in the Medical Laboratory guidelines recommends that laboratories assess the validity of current delta check parameters by reviewing retrospective data on flagged results to determine if errors are being identified efficiently. At Temple University Health System, delta check limits were established historically by using published data, however, its performance characteristics have not been verified previously. Verification of clinical performance of predefined delta check limits can be performed either through mathematical calculations or via clinical audits. Clinical audits are achieved by documenting the follow-up actions and outcomes of the samples flagged by a delta check rule(s). It has been suggested that this should be performed using a protocolized follow-up procedure to ensure uniformity in the investigation and management. Corey M. et al. shared an excel template, a mathematical model that can be adopted easily by replacing the example data with retrospectively extracted data and modifying the parameters to suit their laboratory’s requirements. Methods We collected up to 30,000 data points for each 12 measurand in the clinical chemistry lab retrospectively. By using the excel template, clinical sensitivity and clinical specificity has been calculated. Furthermore, we created ROC curves and evaluated them using the (YI) Youden Index and AUC (Area Under the Curve). Results In general, YI values were found to be very low, less than 0.6. Highest YI was used to establish new delta check limits for each analyte; only the current creatinine delta check limit was found as effective, and no change required. 11 out of 12 measurand were required a revision of delta check limits and were proposed to replace with lower delta checks. AUC values were found between 0.56-0.794. Na showed the highest AUC, which correlates its low individuality index (0.5) and its effects on effectiveness of the delta check system. Conclusions It is of vital importance to establish a solid follow-up evaluation for delta check alerts and distinguish between integrity issues and clinically significant changes. Conclusively, this endeavor can develop into extensive information for the application, evaluation, and follow-up of delta checks whilst improving diagnostic accuracy and quality assurance.

A-182 Applications of artificial intelligence optical character recognition in laboratory clerical functions offsetting staffing shortages and error reduction

Abstract Background The clinical laboratory profession has been dealing with a decade long, and now critical retention and staffing problem. The average national turnover rate for laboratory technicians is 17%, and the highest turnover rate exhibited for phlebotomists is 36%. While turnover rates have an impact on a laboratory, or hospitals budget, more importantly they have a substantial impact on quality and error rates, particularly in the pre-analytical stage of testing; with studies showing up to 65.09% of errors impacting the pre-analytical phase. Methods In an effort to remedy this high error rate, a meta-analysis was performed on paper order entry and clerical pre-analytical error, in parallel with performance and accuracy data of advanced optical character recognition driven by artificial intelligence and machine learning (AI OCR). Results AI OCR studies demonstrated an untrained accuracy percentage, to include handwriting of 91.08%, and when trained utilizing both relational and hierarchal logic data bases accuracy increased to 98.4%. The rate at which AI OCR processed and classified medical information was 3-4 pages per second. It is estimated that 99.9%-100% accuracy can be achieved with additional form field training and mapping. The level of accuracy and efficiency for laboratory paper order-entry utilizing AI OCR can also be increased with the addition of natural language processing and data recognition algorithms when combined with logic databases containing information such as medical record numbers, ICD-10 codes, and laboratory test compendiums. Conclusions The performance of this technology demonstrates a strong application to reduce the burden of clerical paper order entry, while addressing the 30.8% dissatisfaction rate regarding manual entry processes among lab professionals surveyed. Moreover, AI OCR clerical data classification, extraction and entry processes augmented with human verification steps examined, demonstrated overall accuracy of 99.99%. The application of AI OCR in laboratory pre-analytical processes has the potential to improve test order accuracy and efficiency, ultimately impacting the quality of patient care and operational costs for healthcare facilities. When examined through the lens of staff retention, studies show that 80% of laboratory employees feel that a workplace with the necessary tools and technology positively impacts their job satisfaction. While organizations investing in technologies that drive both job efficiency and satisfaction see a 125% return on investment through productivity. Demonstrating that the application of sophisticated technologies that both increase productivity and decrease error rates have a substantial impact on job satisfaction and ultimately retention. Although laboratory clerical data and order entry processes were examined for this meta-analysis, the aggregate data compiled showed that the application of AI OCR in clerical processes could also have a substantial impact on the 25.9% annual turnover rate for hospitals as a whole in the United States.

A-116 Pleural Fluid pH - Are We Collecting and Measuring It Correctly?

Abstract Background Pleural fluid pH has diagnostic, therapeutic, and prognostic implications in the management of pleural space infections and malignancy. Pleural fluid sample collection, transportation and processing are known for source of pre-analytical error which contribute to inaccuracy of measured pH with clinical implication to patient care. Some clinical practices observed locally include pleural fluid collection in sterile container for ease of other biochemistry analytes measurement in addition to pH. This study aimed to compare the differences in pleural fluid pH and other commonly ordered biochemistry analytes collected using sterile container against heparinized blood gas syringe. Methods Total 20 Pleural fluid samples were collected from patient using a procedure called thoracentesis from, with approximately 2 to 3ml of fluid directly transferred into heparinized blood gas syringe as well as in a sterile container. Both samples were then transported to Clinical Biochemistry Laboratory within an hour. Both samples were analyzed on 3 analytical systems; 1) pH on Roche COBAS b221 blood gas analyzer, 2) Glucose, Total Protein, LDH on Beckman AU System and 3) Specific Gravity on Reflectometer. Statistical analysis was performed using Analyze-It software. Results pH fluid collected in sterile container demonstrates significant high bias (absolute of 0.4 units or 5%) as compared to sample collected in heparinizes blood gas syringe. Other commonly ordered tests in fluid profile (Glucose, Total Protein, LDH and SG) demonstrate good correlation (Altman-Bland Difference Plot &amp;lt;5%) for pleural fluid collected in sterile container as compared to heparinized syringe. Conclusions This positive bias observed is likely attributed to air exposure in pleural fluid collection in sterile container as compared to heparinized syringe. The accuracy of measured pleural pH is critically dependent on the method of sample collection. This study highlights the need for a standardized protocol for pleural pH collection for accurate measurement.

Novel In-Line Hemolysis Detection on a Blood Gas Analyzer and Impact on Whole Blood Potassium Results.

Preanalytical error due to hemolyzed blood samples is a common challenge in laboratory and point-of-care (POC) settings. Whole blood potassium (K+) measurements routinely measured on blood gas analyzers are particularly susceptible to hemolysis, which poses a risk for incorrect K+ results. The GEM Premier 7000 with IQM3 (GEM 7000) blood gas analyzer provides novel integrated hemolysis detection within the sample measurement process. Therefore, the GEM 7000 can detect and flag hemolyzed whole blood samples at the POC, warning the operator of potentially erroneous results. Heparinized venous or arterial whole blood samples were used for K+ interference studies and assessed for hemolysis agreement utilizing either a traditional volumetric method or chemistry analyzer serum index measurements with the Roche cobas c311 or Abbott Alinity c. Hemolysis interference studies performed at 2 different K+ concentrations (3.8 and 5.3 mmol/L) identified that a plasma free hemoglobin ≥116 mg/dL can impact K+ results on the GEM 7000. Hemolysis agreement studies demonstrated an excellent agreement of >99% with the volumetric method, 98.8% with cobas H index, and 96.4% with Alinity H index. GEM 7000 K+ results were correctly flagged for both native and spiked samples. GEM 7000 hemolysis detection provides a novel technology to detect hemolysis in whole blood samples. Moreover, the GEM 7000 demonstrates excellent agreement with traditional laboratory hemolysis detection methods and offers an integrated technological solution for assuring the quality of whole blood K+ results in POC settings.