Errors in a Stat Laboratory: Types and Frequencies 10 Years Later

Abstract Background: In view of increasing attention focused on patient safety and the need to reduce laboratory errors, it is important that clinical laboratories collect statistics on error occurrence rates over the whole testing cycle, including pre-, intra-, and postanalytical phases. Methods: The present study was conducted in 2006 according to the design we previously used in 1996 to monitor the error rates for laboratory testing in 4 different departments (internal medicine, nephrology, surgery, and intensive care). For 3 months, physicians and nurses were asked to pay careful attention to all test results. Any suspected laboratory error was recorded with associated pertinent clinical information. Every day, a laboratory physician visited the 4 departments and a critical appraisal was made of any suspect results. Results: Among a total of 51 746 analyses, clinicians notified us of 393 questionable findings, 160 of which were confirmed as laboratory errors. The overall frequency of errors, 3092 ppm, was significantly lower (P <0.05) than in 1996 (4700 ppm). Of the 160 confirmed errors, 61.9% were preanalytical errors, 15% were analytical, and 23.1% were postanalytical. Conclusions: During the last decade the error rates in our stat laboratory have been reduced significantly. As demonstrated by the distribution pattern, the pre- and postanalytical steps still have the highest error prevalences, but changes have occurred in the types and frequencies of errors in these phases of testing.

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The usefulness of quality indicators of preanalitical phase in medical labs, according to the Quality standards requirements, ISO 15189:2013 and WG-LEPS recommendation, Jan 2017

Diagnostyka Laboratoryjna ◽

10.5604/01.3001.0013.7453 ◽

2019 ◽

Vol 55 (2) ◽

pp. 113-120

Author(s):

Mirosława Pietruczuk ◽

Łukasz Kraszula ◽

Anna Jasińska ◽

Piotr Kuna ◽

Makandjou-Ola Eusebio

Keyword(s):

Clinical Information ◽

Information Management System ◽

Error Rates ◽

Iso 15189 ◽

Laboratory Errors ◽

Analytical Process ◽

Laboratory Error ◽

Medical Diagnostic ◽

The Mean ◽

One Year

This paper presents the usefulness of pre-analytical process in medical diagnostic laboratories, recommended by WG-LEPS, according to departmental requirements and ISO 15189, with regard to clinical hospital laboratory. It is known that the pre-analytical process generates over 70% of all laboratory errors. The tested materials are laboratory test referrals data for a period of one year (2017), mainly from the Laboratory Information Management System. The study includes the mean annual pre-laboratory error rates. The results showed low error rates in the areas related to the laboratory testing. The highest error rates were found in the field relevant to clinical information and data that are not related the laboratory processing.

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Errors in clinical laboratories or errors in laboratory medicine?

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm.2006.123 ◽

2006 ◽

Vol 44 (6) ◽

Cited By ~ 192

Author(s):

Mario Plebani

Keyword(s):

Laboratory Testing ◽

Laboratory Medicine ◽

Total Quality ◽

Modern Approach ◽

Laboratory Errors ◽

Phase Errors ◽

Clinical Laboratories ◽

Laboratory Services ◽

Analytical Phase ◽

Total Testing Process

AbstractLaboratory testing is a highly complex process and, although laboratory services are relatively safe, they are not as safe as they could or should be. Clinical laboratories have long focused their attention on quality control methods and quality assessment programs dealing with analytical aspects of testing. However, a growing body of evidence accumulated in recent decades demonstrates that quality in clinical laboratories cannot be assured by merely focusing on purely analytical aspects. The more recent surveys on errors in laboratory medicine conclude that in the delivery of laboratory testing, mistakes occur more frequently before (pre-analytical) and after (post-analytical) the test has been performed. Most errors are due to pre-analytical factors (46–68.2% of total errors), while a high error rate (18.5–47% of total errors) has also been found in the post-analytical phase. Errors due to analytical problems have been significantly reduced over time, but there is evidence that, particularly for immunoassays, interference may have a serious impact on patients. A description of the most frequent and risky pre-, intra- and post-analytical errors and advice on practical steps for measuring and reducing the risk of errors is therefore given in the present paper. Many mistakes in the Total Testing Process are called “laboratory errors”, although these may be due to poor communication, action taken by others involved in the testing process (e.g., physicians, nurses and phlebotomists), or poorly designed processes, all of which are beyond the laboratory's control. Likewise, there is evidence that laboratory information is only partially utilized. A recent document from the International Organization for Standardization (ISO) recommends a new, broader definition of the term “laboratory error” and a classification of errors according to different criteria. In a modern approach to total quality, centered on patients' needs and satisfaction, the risk of errors and mistakes in pre- and post-examination steps must be minimized to guarantee the total quality of laboratory services.

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Assessment of laboratory errors and best laboratory practices

International Journal of Bioassays ◽

10.21746/ijbio.2016.07.008 ◽

2016 ◽

Vol 5 (07) ◽

pp. 4704

Author(s):

Syed Riaz Mehdi* ◽

Sharique Ahmad ◽

Noorin Zaidi

Keyword(s):

External Quality Control ◽

External Quality ◽

Iso 15189 ◽

Laboratory Errors ◽

Control Programs ◽

Medical Laboratories ◽

Laboratory Error ◽

Active Communication ◽

Total Testing Process ◽

Five Phases

Laboratory error is defined by ISO 22367 as “Failure of planned actions to be completed as intended or use a wrong plan to achieve an aim”. Lundeberg in 1981 outlined the concept of Total Testing Process (TTP) and Plebani elaborated it further and classified the whole testing process into five phases of Pre-Pre Analytic, Pre Analytic, Analytic, Post Analytic and Post - Post Analytic. The errors have to be identified and resolved in each phase of the process. The medical laboratories have to run Internal and External Quality Control programs and abide by the guidelines of ISO 15189 in order to be accredited by bodies like JCI, CAP or NABL. Active communication and regular interaction between the clinicians and the laboratory is recommended during Pre Analytic and Post Analytic phases of TTP in order to achieve the target of Best Laboratory Practices.

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Potensi Nilai Kalor Biomassa Dari Ampas Tebu (Bagasse) Yang Bersumber Dari Penjual Minuman Sari Tebu Di Kota Pontianak

Jurnal Serambi Engineering ◽

10.32672/jse.v6i1.2654 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Reza Wahyudi ◽

Muhammad Ivanto ◽

Murti Juliandari

Keyword(s):

Laboratory Testing ◽

Energy Supply ◽

Alternative Fuels ◽

Fossil Fuels ◽

Calorific Value ◽

Ash Content ◽

Sugarcane Juice ◽

Test Results ◽

Supply Problem ◽

Direct Data

Dependence on the provision of electricity using fossil fuels is a major energy supply problem in Indonesia. Therefore, it is necessary to provide new and renewable alternative fuels that are effective, efficient, and environmentally friendly. One of the alternative fuels is bagasse biomass. The purpose of this study was to determine the amount of bagasse produced by sellers of sugarcane juice drink in Pontianak City, in order to determine the estimated value of bagasse. The research method used was direct data collection and laboratory testing . Based on the results of the study, the number of vendors of sugarcane juice beverages producing bagasse was 169. Of this amount, produce bagasse that can reach 1,030.9 kg/day. Based on the test results, the estimated moisture content of bagasse was 3.28%, ash content was 0.77%, and carbon remained at 7.65%. So, if converted with the test results of the calorific value of bagasse and made into briquettes bagasse (bio briquettes), which is 19,648 kJ/kg with a density of 0.416 kg/m3, then converted into a potential calorific value of 242,849,280 J/year.

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Accuracy of Send-Out Test Ordering: A College of American Pathologists Q-Probes Study of Ordering Accuracy in 97 Clinical Laboratories

Archives of Pathology & Laboratory Medicine ◽

10.5858/2008-132-206-aostoa ◽

2008 ◽

Vol 132 (2) ◽

pp. 206-210

Author(s):

Paul N. Valenstein ◽

Molly K. Walsh ◽

Ana K. Stankovic

Keyword(s):

Laboratory Tests ◽

Error Rates ◽

Reference Laboratory ◽

Patient Evaluation ◽

Order Entry ◽

Order Accuracy ◽

Specific Test ◽

Clinical Laboratories ◽

Test Order ◽

Test Ordering

Abstract Context.—Errors entering orders for send-out laboratory tests into computer systems waste health care resources and can delay patient evaluation and management. Objectives.—To determine (1) the accuracy of send-out test order entry under “real world” conditions and (2) whether any of several practices are associated with improved order accuracy. Design.—Representatives from 97 clinical laboratories provided information about the processes they use to send tests to reference facilities and their order entry and specimen routing error rates. Results.—In aggregate, 98% of send-out tests were correctly ordered and 99.4% of send-out tests were routed to the proper reference laboratory. There was wide variation among laboratories in the rate of send-out test order entry errors. In the bottom fourth of laboratories, more than 5% of send-out tests were ordered incorrectly, while in the top fourth of laboratories fewer than 0.3% of tests were ordered incorrectly. Order entry errors were less frequent when a miscellaneous test code was used than when a specific test code was used (3.9% vs 5.6%; P = .003). Conclusions.—Computer order entry errors for send-out tests occur approximately twice as frequently as order entry errors for other types of tests. Filing more specific test codes in a referring institution's information system is unlikely to reduce order entry errors and may make error rates worse.

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Blood Bank Safety Practices: Mislabeled Samples and Wrong Blood in Tube—A Q-Probes Analysis of 122 Clinical Laboratories

Archives of Pathology & Laboratory Medicine ◽

10.5858/2009-0674-cp.1 ◽

2010 ◽

Vol 134 (8) ◽

pp. 1108-1115 ◽

Cited By ~ 3

Author(s):

Erin Grimm ◽

Richard C. Friedberg ◽

David S. Wilkinson ◽

James P. AuBuchon ◽

Rhona J. Souers ◽

...

Keyword(s):

Error Rates ◽

Rare Occurrence ◽

Patient Identification ◽

Institutional Policies ◽

Safety Practices ◽

Clinical Laboratories ◽

Patient Morbidity ◽

Labeling Requirements ◽

Significant Opportunity ◽

Variable Information

Abstract Context.—Although a rare occurrence, ABO incompatible transfusions can cause patient morbidity and mortality. Up to 20% of all mistransfusions are traced to patient misidentification and/or sample mislabeling errors that occur before a sample arrives in the laboratory. Laboratories play a significant role in preventing mistransfusion by identifying wrong blood in tube and rejecting mislabeled samples. Objectives.—To determine the rates of mislabeled samples and wrong blood in tube for samples submitted for ABO typing and to survey patient identification and sample labeling practices and sample acceptance policies for ABO typing samples across a variety of US institutions. Design.—One hundred twenty-two institutions prospectively reviewed inpatient and outpatient samples submitted for ABO typing for 30 days. Labeling error rates were calculated for each participant and tested for associations with institutional demographic and practice variable information. Wrong-blood-in-tube rates were calculated for the 30-day period and for a retrospective 12-month period. A concurrent survey collected institution-specific sample labeling requirements and institutional policies regarding the fate of mislabeled samples. Results.—For all institutions combined, the aggregate mislabeled sample rate was 1.12%. The annual and 30-day wrong-blood-in-tube aggregate rates were both 0.04%. Patient first name, last name, and unique identification number were required on the sample by more than 90% of participating institutions; however, other requirements varied more widely. Conclusions.—The rates of mislabeled samples and wrong blood in tube for US participants in this study were comparable to those reported for most European countries. The survey of patient identification and sample labeling practices and sample acceptance policies for ABO typing samples revealed both practice uniformity and variability as well as significant opportunity for improvement.

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Multicenter Evaluation of Ceftazidime-Avibactam Susceptibility Testing of Enterobacterales and Pseudomonas aeruginosa on the VITEK® 2 System

Journal of Clinical Microbiology ◽

10.1128/jcm.01870-20 ◽

2020 ◽

Author(s):

Romney Humphries ◽

Shelley Campeau ◽

Thomas E. Davis ◽

Kristin J. Nagaro ◽

Vincent J. LaBombardi ◽

...

Keyword(s):

Pseudomonas Aeruginosa ◽

Error Rate ◽

Susceptibility Testing ◽

Reference Method ◽

Error Rates ◽

Performance Criteria ◽

Test Results ◽

Major Error ◽

Overall Performance ◽

Vitek 2

In this multisite study, VITEK® 2 AST-Gram-Negative Ceftazidime-Avibactam (CZA) test results for 1073 isolates (866 Enterobacterales and 207 Pseudomonas aeruginosa) were compared to the Clinical & Laboratory Standards Institute (CLSI) broth microdilution (BMD) reference method. The results were analyzed for essential agreement (EA), category agreement (CA), major error rates, and very major error rates following FDA/ISO performance criteria using the FDA-recognized CLSI/EUCAST breakpoints (S ≤8/4 μg/ml and R ≥16/4 μg/ml). The overall EA was 94.5% (1014/1073) and CA was 98.7% (1059/1073). No very major errors were reported. The major error rate was 1.4% (14/998). Out of 14 major errors, 9 were within EA. Based on the EA and lack of an intermediate category for CZA, the adjusted major error rate for FDA criteria was 0.5% (5/998). The performance for ISO criteria after error resolutions included EA 94.5% (1014/1073), CA 98.9% (1061/1073), major error 1.2% (12/998), and no very major error. Vitek 2 met the ISO and FDA criteria of ≥95% reproducibility and ≥95% quality control (QC) results within acceptable ranges for QC organisms. Vitek 2 overall performance for Enterobacterales and P. aeruginosa met or exceeded the FDA and ISO performance criteria and thus is a reliable alternative to BMD reference method for routine CZA susceptibility testing.

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COVID-19 related challenges faced by Medical Laboratory Staff: A Review of Literature

World Journal of Advanced Research and Reviews ◽

10.30574/wjarr.2021.12.2.0589 ◽

2021 ◽

Vol 12 (2) ◽

pp. 232-237

Author(s):

Jignesh Sharma ◽

Richard D. Nair

Keyword(s):

Human Resources ◽

Laboratory Testing ◽

English Language ◽

Turnaround Time ◽

Medical Laboratory ◽

Test Results ◽

Review Of Literature ◽

Medical Laboratory Science ◽

Laboratory Staff ◽

Laboratory Science

Laboratory testing on the confirmation of COVID-19 results is an essential component and without the expertise of trained laboratory technicians this is not possible. The aim of this study was to review the impacts of COVID-19 on medical laboratory staff. The literature search was done using Medline, Embase, Scopus, and Proquest databases, and relevant keywords were applied to find studies which have been conducted in the field of Medical Laboratory Science specifically looking at the impacts on staff caused by the Covid-19 pandemic. All the studies pertaining to the topic published in 2020 and 2021 in English language were reviewed and the main themes were identified. The results showed that impacts of COVID-19 were felt by the staff, as they were pushed to their limits causing stress and burnout. Apart from this laboratory staff were faced with issues such as; shortage in terms of human resources, consumables, testing kits and reagents. This was an added factor to delays in testing and disruption to the testing Turnaround time (TATs) and also contributed to the stress and burnout of staff. Laboratory professionals and other health care staffs were pushed to the limits to ensure patient care was not affected and each patient was attended too without delay. Laboratory personnel’s were pushed to their limits to ensure that test results were given on time.

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Specimen Labeling Errors: A Q-Probes Analysis of 147 Clinical Laboratories

Archives of Pathology & Laboratory Medicine ◽

10.5858/2008-132-1617-sleaqa ◽

2008 ◽

Vol 132 (10) ◽

pp. 1617-1622 ◽

Cited By ~ 8

Author(s):

Elizabeth A. Wagar ◽

Ana K. Stankovic ◽

Stephen Raab ◽

Raouf E. Nakhleh ◽

Molly K. Walsh

Keyword(s):

Clinical Laboratory ◽

Delayed Diagnosis ◽

Error Rates ◽

Quality Patient Care ◽

Clinical Laboratories ◽

Coagulation Testing ◽

Blood Specimens ◽

Specimen Identification ◽

Transfusion Reactions ◽

Variable Information

Abstract Context.—Accurate specimen identification is critical for quality patient care. Improperly identified specimens can result in delayed diagnosis, additional laboratory testing, treatment of the wrong patient for the wrong disease, and severe transfusion reactions. Specimen identification errors have been reported to occur at rates of 0.1% to 5%. Objective.—To determine the frequency of labeling errors in a multi-institutional survey. Design.—Labeling errors were categorized as: (1) mislabeled, (2) unlabeled, (3) partially labeled, (4) incompletely labeled, and (5) illegible label. Blood specimens for routine or stat chemistry, hematology, and coagulation testing were included. Labeling error rates were calculated for each participant and tested for associations with institutional demographic and practice variable information. Results.—More than 3.3 million specimen labels were reviewed by 147 laboratories. Labeling errors were identified at a rate of 0.92 per 1000 labels. Two variables were statistically associated with lower labeling error rates: (1) laboratories with current, ongoing quality monitors for specimen identification (P = .008) and (2) institutions with 24/7 phlebotomy services for inpatients (P = .02). Most institutions had written policies for specimen labeling at the bedside or in outpatient phlebotomy areas (96% and 98%, respectively). Allowance of relabeling of blood specimens by primary collecting personnel was reported by 42% of institutions. Conclusions.—Laboratories actively engaged in ongoing specimen labeling quality monitors had fewer specimen labeling errors. Also, 24/7 phlebotomy services were associated with lower specimen error rates. Establishing quality metrics for specimen labeling and deploying 24/7 phlebotomy operations may contribute to improving the accuracy of specimen labeling for the clinical laboratory.

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