scholarly journals Control of Clinical Laboratory Errors by FMEA Model

2021 ◽  
Author(s):  
Hoda Sabati ◽  
Amin Mohsenzadeh ◽  
Nooshin Khelghati
Keyword(s):  
Patient Safety ◽  
Error Detection ◽  
Clinical Laboratory ◽  
Technical Specification ◽  
Fundamental Principle ◽  
Management Plan ◽  
Technical Committee ◽  
Effect Analysis ◽  
Medical Laboratories ◽  
Prospective Risk

Patient safety is an aim for clinical applications and is a fundamental principle of healthcare and quality management. The main global health organizations have incorporated patient safety in their review of work practices. The data provided by the medical laboratories have a direct impact on patient safety and a fault in any of processes such as strategic, operational and support, could affect it. To provide appreciate and reliable data to the physicians, it is important to emphasize the need to design risk management plan in the laboratory. Failure Mode and Effect Analysis (FMEA) is an efficient technique for error detection and reduction. Technical Committee of the International Organization for Standardization (ISO) licensed a technical specification for medical laboratories suggesting FMEA as a method for prospective risk analysis of high-risk processes. FMEA model helps to identify quality failures, their effects and risks with their reduction/elimination, which depends on severity, probability and detection. Applying FMEA in clinical approaches can lead to a significant reduction of the risk priority number (RPN).

Corrections of Clinical Chemistry Test Results in a Laboratory Information System

2004 ◽  
Vol 128 (8) ◽  
pp. 890-892
Author(s):  
Sihe Wang ◽  
Virginia Ho
Keyword(s):  
Information System ◽  
Patient Safety ◽  
Error Detection ◽  
Clinical Laboratory ◽  
Improve Patient Safety ◽  
Clinical Chemistry ◽  
Laboratory Information System ◽  
Test Volume ◽  
Laboratory Errors ◽  
Made In

Abstract Context.—The recently released reports by the Institute of Medicine, To Err Is Human and Patient Safety, have received national attention because of their focus on the problem of medical errors. Although a small number of studies have reported on errors in general clinical laboratories, there are, to our knowledge, no reported studies that focus on errors in pediatric clinical laboratory testing. Objective.—To characterize the errors that have caused corrections to have to be made in pediatric clinical chemistry results in the laboratory information system, Misys. To provide initial data on the errors detected in pediatric clinical chemistry laboratories in order to improve patient safety in pediatric health care. Design.—All clinical chemistry staff members were informed of the study and were requested to report in writing when a correction was made in the laboratory information system, Misys. Errors were detected either by the clinicians (the results did not fit the patients' clinical conditions) or by the laboratory technologists (the results were double-checked, and the worksheets were carefully examined twice a day). No incident that was discovered before or during the final validation was included. On each Monday of the study, we generated a report from Misys that listed all of the corrections made during the previous week. We then categorized the corrections according to the types and stages of the incidents that led to the corrections. Results.—A total of 187 incidents were detected during the 10-month study, representing a 0.26% error detection rate per requisition. The distribution of the detected incidents included 31 (17%) preanalytic incidents, 46 (25%) analytic incidents, and 110 (59%) postanalytic incidents. The errors related to noninterfaced tests accounted for 50% of the total incidents and for 37% of the affected tests and orderable panels, while the noninterfaced tests and panels accounted for 17% of the total test volume in our laboratory. Conclusion.—This pilot study provided the rate and categories of errors detected in a pediatric clinical chemistry laboratory based on the corrections of results in the laboratory information system. A direct interface of the instruments to the laboratory information system showed that it had favorable effects on reducing laboratory errors.

Prospective risk analysis adjusted to the reality of clinical and fertility laboratory processes

Diagnosis ◽  
2015 ◽  
Vol 2 (4) ◽  
pp. 235-243 ◽  
Author(s):  
Pim M.W. Janssens ◽  
Anja Scholten ◽  
Harm De Waard ◽  
Natascha Tiemens ◽  
Monique Van Uum ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Laboratory Testing ◽  
Clinical Laboratory ◽  
Practical Application ◽  
Laboratory Practice ◽  
Effect Analysis ◽  
Clinical Laboratories ◽  
Prospective Risk ◽  
Fmea Method ◽  
Clinical Laboratory Testing

AbstractProspective risk analysis (PRA) is a valuable instrument in quality assurance. The practical application of PRA in clinical laboratories according to the method we have described elsewhere leaves room for a number of adaptations to make it more applicable to and consistent with actual laboratory processes.We distinguished between more and less critical tests and products in the laboratory processes and scored the consequences of failures at different steps in line with the previously described failure type and effect analysis (FMEA) method. PRA was carried out for two typical laboratory processes: standard clinical laboratory testing and the cryopreservation of semen.Tests in standard clinical laboratory in processes were labeled critical, semi-critical or non-critical. Consequence scoring (C) and assessed risk (R) were significantly higher for processes containing tests considered to be critical (C=6.6±1.5, R=19.3±13.5) as compared to processes containing tests considered semi- or non-critical (C=3.0±1.4, R=8.2±5.3 and C=3.2±1.8, R=8.6±5.9, respectively). There were no differences in the C and R scores for processes with tests considered semi- or non-critical. In the semen cryopreservation process, a distinction between the processes involving private semen and generally accessible semen was made. The C scores for these were significantly different (C=5.9±2.2 and 5.0±2.0, respectively), the R scores did not differ.Introduction of a test criticality classification for the purpose of consequence scoring led to an improved PRA methodology, better reflecting the reality of clinical laboratory practice. We found that two levels of criticality, critical and less critical, were sufficient to achieve this improvement.

A highly accurate delta check method using deep learning for detection of sample mix-up in the clinical laboratory

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Rui Zhou ◽  
Yu-fang Liang ◽  
Hua-Li Cheng ◽  
Wei Wang ◽  
Da-wei Huang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Statistical Methods ◽  
Real World ◽  
Error Detection ◽  
Clinical Laboratory ◽  
Characteristic Curve ◽  
False Positive Rate ◽  
Absolute Difference ◽  
Test Items ◽  
Test Sets

Abstract Objectives Delta check (DC) is widely used for detecting sample mix-up. Owing to the inadequate error detection and high false-positive rate, the implementation of DC in real-world settings is labor-intensive and rarely capable of absolute detection of sample mix-ups. The aim of the study was to develop a highly accurate DC method based on designed deep learning to detect sample mix-up. Methods A total of 22 routine hematology test items were adopted for the study. The hematology test results, collected from two hospital laboratories, were independently divided into training, validation, and test sets. By selecting six mainstream algorithms, the Deep Belief Network (DBN) was able to learn error-free and artificially (intentionally) mixed sample results. The model’s analytical performance was evaluated using training and test sets. The model’s clinical validity was evaluated by comparing it with three well-recognized statistical methods. Results When the accuracy of our model in the training set reached 0.931 at the 22nd epoch, the corresponding accuracy in the validation set was equal to 0.922. The loss values for the training and validation sets showed a similar (change) trend over time. The accuracy in the test set was 0.931 and the area under the receiver operating characteristic curve was 0.977. DBN demonstrated better performance than the three comparator statistical methods. The accuracy of DBN and revised weighted delta check (RwCDI) was 0.931 and 0.909, respectively. DBN performed significantly better than RCV and EDC. Of all test items, the absolute difference of DC yielded higher accuracy than the relative difference for all methods. Conclusions The findings indicate that input of a group of hematology test items provides more comprehensive information for the accurate detection of sample mix-up by machine learning (ML) when compared with a single test item input method. The DC method based on DBN demonstrated highly effective sample mix-up identification performance in real-world clinical settings.

Organization of the work of the medical laboratory service in accordance with the requirements of the standard GOST ISO 15189–2015 «Medical laboratories. Particular requirements for quality and competence»

2020 ◽  
pp. 15-22
Author(s):  
Elena Vitalievna Perminova
Keyword(s):  
Clinical Laboratory ◽  
Medical Laboratory ◽  
Laboratory Research ◽  
Laboratory Diagnostics ◽  
Clinical Diagnostic Laboratory ◽  
Diagnostic Laboratory ◽  
Iso 15189 ◽  
Laboratory Service ◽  
Medical Laboratories

Clinical laboratory diagnostics is a medical specialty, which is based on in vitro diagnostic studies of biomaterial obtained from an individual. At the present stage, there are three main types of organization of the laboratory research process — a laboratory service as part of a medical and preventive institution, a centralized laboratory where biomaterials are delivered for research from various healthcare institutions, as well as mobile laboratories that allow conducting the research directly at the patient’s bedside. This discipline involves the use of a wide variety of diagnostic research methods and the use of a huge number of specific techniques. Their list should include carrying out hematological, microbiological, virological, immunological, serological, parasitic, and biochemical studies. Also, when organizing laboratory diagnostic activities, a number of other studies (cytological, histological, toxicological, genetic, molecular biological, etc.) are provided. A laboratory report is formulated after obtaining clinical data and comparing them with the obtained test results. The quality of laboratory tests is ensured through the systematic implementation of internal laboratory control, as well as participation in a national program for external quality assessment. The activities of the clinical diagnostic laboratory should be organized in accordance with the requirements of the standard GOST R ISO 15189–2015 «Medical laboratories. Particular requirements for quality and competence», which is based on the provisions of two more fundamental standards — ISO 9001 and ISO 17025, and adds a number of special requirements related to medical laboratories.

scholarly journals Development of the technical specifications and changes to the TSs for refractories by JSC “The Ukrainian research institute of refractories named after A. S. Berezhnoy” in 2018

2019 ◽  
Vol 119 ◽  
pp. 107-121
Author(s):  
V. V. Martynenko ◽  
L. V. Belyaeva ◽  
I. Yu. Kostyrko ◽  
T. F. Pahomova ◽  
T. P. Lytvynenko
Keyword(s):  
Technical Specification ◽  
Technical Committee ◽  
The State ◽  
Global Level ◽  
Regulatory Documents ◽  
State Standardization ◽  
Modern System ◽  
Technical Specifications ◽  
Continue Work ◽  
Technical Regulations

This article includes information about development of technical specifications (TS) and changes to the TSs for refractories by institute in 2018. In 2018, the following standards were developed, agreed with enterprises in accordance with the requirements of the state standardization system and approved: one new technical specification and 14 change to TS for serial refractory products, produced by Ukrainian enterprises; 3 new TS for serial refractory products developed PrJSC “KDZ” were checked and agreed; 6 new technical specification and 11 change to the current specifications for the pilot batches of refractories manufactured by JSC “The URIR named after A. S. Berezhnoy”. Changes to technical specifications and new technical specifications have been developed in concordance with requirements of the modern system standardizations of the Ukraine (СОУ КЗПС 74.9­02568182­003:2016, ДСТУ 1.5:2015, СОУ МПП 01.120­090:2005), endorsed by manufacturers and enterprise consumers, tested for compliance with current legislation, technical regulations and regulatory documents and entered into the database «Technical conditions of Ukraine» — SE “Kharkivstandartmetrology”, and approved by the technical committee TC 7 “Refractories”. Institute plans to continue work on the development of TS and changes to the TSs for refractory products, study and analysis of the global level of standardization in the field of refractories.

Performance Characteristics of Several Rules for Self-interpretation of Proficiency Testing Data

2005 ◽  
Vol 129 (8) ◽  
pp. 997-1003 ◽  
Author(s):  
R. Neill Carey ◽  
George S. Cembrowski ◽  
Carl C. Garber ◽  
Zohreh Zaki
Keyword(s):  
Proficiency Testing ◽  
Error Detection ◽  
Clinical Laboratory ◽  
Peer Group ◽  
Simulation Techniques ◽  
Allowable Error ◽  
Detection Capabilities ◽  
The Mean ◽  
The Difference

Abstract Context.—Proficiency testing (PT) participants can interpret their results to detect errors even when their performance is acceptable according to the limits set by the PT provider. Objective.—To determine which rules for interpreting PT data provide optimal performance for PT with 5 samples per event. Design.—We used Monte Carlo computer simulation techniques to study the performance of several rules, relating their error detection capabilities to (1) the analytic quality of the method, (2) the probability of failing PT, and (3) the ratio of the peer group SD to the mean intralaboratory SD. Analytic quality is indicated by the ratio of the PT allowable error to the intralaboratory SD. Failure of PT was defined (Clinical Laboratory Improvement Amendments of 1988) as an event when 2 or more results out of 5 exceeded acceptable limits. We investigated rules with limits based on the SD index, the mean SD index, and percentages of allowable error. Results.—No single rule performs optimally across the range of method quality. Conclusions.—We recommend further investigation when PT data cause rejection by any of the following 3 rules: any result exceeds 75% of allowable error, the difference between any 2 results exceeds 4 times the peer group SD, or the mean SD index of all 5 results exceeds 1.5. As method quality increases from marginal to high, false rejections range from 16% to nearly zero, and the probability of detecting a shift equal to 2 times the intralaboratory SD ranges from 94% to 69%.

Clinical assessments

2019 ◽  
pp. 867-872
Keyword(s):  
Patient Safety ◽  
Medical School ◽  
Clinical Evaluation ◽  
Management Plan ◽  
Multisource Feedback ◽  
Differential Diagnoses ◽  
Practical Advice ◽  
Objective Structured Clinical Examinations ◽  
Case Presentations ◽  
Case Based

This chapter focuses on a number of different assessments that occur during clinical medical years and at the end of medical school, which may be formative or summative. The chapter reviews case presentations, and how best to structure them to reach a proposed management plan and summary. It provides students with an opportunity to explore differential diagnoses. It also discusses objective structured clinical examinations including examples of stations and practical advice with a focus on patient safety. This chapter includes examples of work-based assessments such as mini clinical evaluation exercises, case-based discussions, direct observation of procedural skills, and multisource feedback. It is written for both those looking to apply for medicine, and those in medical school.

Understanding and managing interferences in clinical laboratory assays: the role of laboratory professionals

2020 ◽  
Vol 58 (3) ◽  
pp. 350-356 ◽  
Author(s):  
Martina Zaninotto ◽  
Mario Plebani
Keyword(s):  
Patient Safety ◽  
Laboratory Testing ◽  
Clinical Laboratory ◽  
Careful Evaluation ◽  
The Matrix ◽  
Analytical Phase

AbstractThe recently raised concerns regarding biotin interference in immunoassays have increased the awareness of laboratory professionals and clinicians of the evidence that the analytical phase is still vulnerable to errors, particularly as analytical interferences may lead to erroneous results and risks for patient safety. The issue of interference in laboratory testing, which is not new, continues to be a challenge deserving the concern and interest of laboratory professionals and clinicians. Analytical interferences should be subdivided into two types on the basis of the possibility of their detection before the analytical process. The first (type 1) is represented by lipemia, hemolysis and icterus, and the second (type 2), by unusual constituents that are not undetectable before analysis, and may affect the matrix of serum/plasma of individual subjects. Type 2 cannot be identified with current techniques when performing the pre-analytical phase. Therefore, in addition to a more careful evaluation and validation of the method to be used in clinical practice, the awareness of laboratory professionals should be raised as to the importance of evaluating the quality of biological samples before analysis and to adopt algorithms and approaches in the attempt to reduce problems related to erroneous results due to specific or non-specific interferences.

scholarly journals P13 Optimising paediatric intravenous fluid management plans: a quality improvement project

2020 ◽  
Vol 105 (9) ◽  
pp. e12.2-e13
Author(s):  
Jenny Gray ◽  
Susie Gage
Keyword(s):  
Patient Safety ◽  
Nursing Staff ◽  
Fluid Balance ◽  
Medical Staff ◽  
Fluid Management ◽  
Management Plan ◽  
Intravenous Fluid ◽  
Safety Alert ◽  
Management Plans ◽  
National Patient

IntroductionIntravenous (IV) maintenance fluids are often prescribed post-surgery when enteral routes are contraindicated. Serious consequences have been documented when poor fluid management has occurred, as highlighted in the National Patient Safety Alert (NPSA) 22; reducing the risk of hyponatraemia; when administering IV fluids to children.1 In response to this, the National Institute for Health and Care Excellence (NICE) published their guidance in December 2015 regarding IV fluids in children.2 Based on NICE recommendations, a pan hospital fluid guidance was produced. Within the NICE and hospital’s own guideline it states that there should be a daily fluid management plan documented. It has been well recognised that this daily fluid management plan was not routinely been completed; hence showing non-adherence to our hospital policy and NICE recommendations.AimsPrimary aim was to improve the documentation of the daily fluid management plan; aimed at the medical staff and the secondary aim was to improve the monitoring requirements of IV fluids and documentation of these; largely aimed at the nursing staff.MethodsA simple sticker was designed and attached to continuous sheets for medical notes which had a checklist of monitoring requirements and a section for fluid balance. Additionally, 2 posters were produced; one aimed at medical staff for documenting a fluid management plan and one aimed at the nursing staff with the monitoring requirements. These posters were displayed on the paediatric surgical ward.ResultsA total of 22 patients who were prescribed IV fluids were identified for a baseline measurement, an equal number of patients were compared after the intervention. Neonates and children receiving total parenteral nutrition were excluded from the data collection. There were 41% of daily fluid management plans completed pre intervention and post intervention there were 56% completed; showing a 15% increase in completion. As regards the monitoring indications; there were increases for nursing fluid balance completed from 19% to 46%, blood glucose taken and recorded from 64% to 83% and the daily weight documented from 10% to 49%.ConclusionsThis short QI project shows that implementation of an intervention did improve outcomes across all indications investigated. The results are not as dramatic as first hoped, but this is largely due to the short time scale of 4 weeks to introduce our change and it coincided with the change-over month of junior medical staff. With further education and champions within the medical and nursing teams; further improvement is very much possible, with the main aim in reducing risk and improving patient safety.ReferencesNational Patient Safety Alert: Reducing the risk of hyponatraemia when administering intravenous infusions to neonates 2007. Available at https://www.sps.nhs.uk/articles/npsa-alert-reducing-the-risk-of-hyponatraemia-when-administering-intraveneous-infusions-to-neonates/ [Accessed 12th June 2019]NICE guidance: Intravenous fluid therapy in children and young people in hospital. Available at https://www.nice.org.uk/guidance/ng29 [Accessed 12th June 2019]

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