scholarly journals Pre-analytical errors in clinical chemistry laboratory of a tertiary care hospital

2019 ◽  
Vol 7 (10) ◽  
pp. 3815
Author(s):  
Priyanka Prasad ◽  
Rakesh Kumar ◽  
Rekha Kumari
Keyword(s):  
Clinical Chemistry ◽  
Total Error ◽  
Tertiary Care ◽  
Chemistry Laboratory ◽  
Blood Collection ◽  
Laboratory Diagnostics ◽  
Care Hospital ◽  
Sample Collection ◽  
Repeated Testing ◽  
Analytical Errors

Background: Pre-analytical errors account for up to 70% of all mistakes made in laboratory diagnostics, most of which arise from problems in patient preparation, sample collection, transportation, and preparation for analysis and storage. Pre-analytical errors influence the total error thus hindering TQM in laboratory, consequently decreasing the accuracy and reliability of the results generated. This study was conducted with the aim to determine nature and frequency of the occurrence of pre-analytical errors.Methods: This prospective analytical study was designed to evaluate the pre-analytical errors observed in a total of 13,892 out-patient and inpatient samples. Samples received for routine clinical chemistry analysis were screened for pre-analytical errors. Samples received for other investigations were excluded. We recorded all nonconformities and errors occurring over a 3-month period and corrective measures were suggested to minimise them. Laboratory personnel were asked to register rejections, and pre-analytical causes for rejection of ward as well as out-patient samples collected in the laboratory. Types of inappropriateness were evaluated as follows: hemolyzed, blood collection in wrong tubes, clotted blood, inappropriate timing of collection, improperly labelled samples, insufficient volume of specimen and lipemic samples.Results: A total of 13,892 samples from the outpatient department and in-house patients were received by our clinical biochemistry laboratory during the period from April 2019 to June 2019. Out of these 404 samples were found unsuitable for further processing. This accounted for 2.9% of all samples collected in the laboratory and pre-analytical errors were responsible for these samples to be rejected over a period of 3 months. Rejections arose as a result of the following reasons: 0.92% were rejected due to hemolysis; 0.58% were blood collected in wrong tubes; 0.55% were clotted blood; 0.26% had inappropriate timing of collection; 0.24% were mislabeled samples; 0.20% had insufficient sample quantity and 0.14% were lipemic samples.Conclusions: Of all the samples received in the lab, the overall percentage of rejection is 2.9%. Substantial number of samples undergo repeated testing because of rejection owing to pre-analytical errors. The efforts should be aimed to reduce the rates of rejected samples can provide to improve the quality of laboratory based health care processes.

scholarly journals Quality Indicators for Evaluating Errors in the Preanalytical Phase

2021 ◽  
Author(s):  
Mohit Mehndiratta ◽  
Eram Hussain Pasha ◽  
Nilesh Chandra ◽  
Edelbert Anthonio Almeida
Keyword(s):  
Quality Indicators ◽  
Clinical Laboratory ◽  
Clinical Chemistry ◽  
Tertiary Care ◽  
Chemistry Laboratory ◽  
Blood Collection ◽  
Care Hospital ◽  
Preanalytical Phase ◽  
Tertiary Center ◽  
Clinical Chemistry Laboratory

Abstract Objective The aim of this study was to study the incidence of preanalytical errors in the clinical chemistry laboratory attached to a tertiary care hospital. Design and Methods The study was conducted in a clinical chemistry laboratory using the samples and forms received for analysis. Five hundred random samples were analyzed using a predefined set of quality indicators (QIs) over a period of 3 months. The incidence of each preanalytical error was described as a percentage of the total samples analyzed in the study. Statistical Analysis Individual QIs were assigned values as 0 and 1 and were used to assess each sample; 0 if the error was present, and 1 if absent. The incidence of each preanalytical error was described as a percentage of the total samples analyzed in the study. Result Out of the 500 samples observed, 138 samples were error free, while 21 samples had the maximum number of errors, that is, 6. The error committed most often was the omission of provisional diagnosis being mentioned on the requisition form. No preanalytical error was observed for QIs: selecting the appropriate blood collection vial or storage of sample. Conclusion This study confirms that error rate in the preanalytical phase is high and vastly ignored. Errors committed here may be overlooked, given the large number of samples received in the clinical laboratory of a tertiary center. To reduce these errors, the laboratory should provide training to all workers involved in the preanalytical phase. Daily or weekly QI scores should be recorded to assess and rectify shortcomings, thereby improving patient care.

scholarly journals Turn Around Time for Clinical Biochemistry Laboratory: A Vital and Effective Parameter for Patient Care

2021 ◽  
Author(s):  
Mitul Navinchandra Chhatriwala ◽  
Dharmik Savjibhai Patel ◽  
Divyal Patel ◽  
Hitesh N Shah
Keyword(s):  
Clinical Biochemistry ◽  
Tertiary Care ◽  
Cross Sectional Study ◽  
Care Hospital ◽  
Sample Collection ◽  
Diagnostic Laboratory ◽  
Cross Sectional ◽  
Entire Interval ◽  
Turn Around Time ◽  
Analytical Errors

Introduction: Clinical laboratories are judged by its validity, reliability, genuineness or authenticity and its timeliness in reports generating. Repetitively, patients and physicians complain about the time taken by the laboratory for the investigation. The total Turn Around Time (TAT) for laboratory tests includes the entire interval from the order of the test to the awareness of the result by the clinicians. The evaluation and improvement of TAT is crucial for the management of laboratory quality and the satisfaction of patients. Aim: To observe the TAT of common biochemical investigations, to identify reasons for increased TAT and to formulate a plan to rectify increased TAT. Materials and Methods: A hospital based cross-sectional study was conducted at the Clinical Biochemistry Section of the Central Diagnostic Laboratory of Tertiary Care Hospital. TAT data from April 2014 to September 2015 were included in the study. The laboratory technicians and the resident doctors of biochemistry recorded the reasons for the delay of those specimens exceeding the TAT. Data were analysed with the help of statistical software Epi Info 7. Results: The total number of samples received in the biochemistry laboratory were 1,85,658. Out of this, Out Patient Department (OPD) samples were 1,35,022 and Intensive Care Unit (ICU) samples were 50,636. Pre-analytical errors were observed in 670 of ICU samples, which was 1.32% of total samples received and it was higher than the post-analytical errors. In the pre-analytical phase, the most common cause was inaccurate procedures of sample collection. Conclusion: This study demonstrates that the main culprit of increased TAT was delay in the sample transportation and Haemolysed samples. TAT minimisation is a constant procedure for any facility. Every laboratory needs to develop a decent approach for reducing the TAT.

scholarly journals Comparison of knowledge, attitude and practices in routine blood and urine collection among final year laboratory technician students, nursing students and house surgeons

2020 ◽  
Vol 7 (9) ◽  
pp. 3559
Author(s):  
Johns John ◽  
Kavitarati Dharwadkar ◽  
Jini M. P.
Keyword(s):  
Nursing Students ◽  
Tertiary Care ◽  
Blood Collection ◽  
Care Hospital ◽  
Urine Collection ◽  
Sample Collection ◽  
Cross Sectional ◽  
Routine Blood ◽  
Validated Questionnaire ◽  
Student’S T

Background: Laboratory services are the backbone of the modern health care sector. In spite of rapid advances in laboratory science, it is still susceptible to various manual and systemic errors. Pre-analytical phase includes specimen collection, storage, separation and transport. Errors in this phase are majorly due to human mistakes and the majority of these errors are preventable. Laboratory technicians and nursing staff from in-patient care are most commonly and directly involved in sample collection. There are many studies done using them as study population. However, the role of physician in sample collection techniques is often ignored. Ideally a doctor should also be aware of the sample collection techniques and anticipate possible lab errors due to pre-analytical error.Methods: A quantitative cross sectional comparative study with 60 participants comprising 20 each from house surgeons, final year lab technicians and nursing students in a tertiary care hospital. A pre-tested, self-administered and validated questionnaire was used to assess knowledge, attitude and practices in routine blood and urine collection with total 27 questions. Statistical analysis: ANOVA, student’s t- test and qualitative analysis was done.Results: In the area of sample collection techniques house surgeons lacked the required knowledge compared to nursing and lab technician students and it was also reflected in sample collection practices.Conclusions: Based on the study, we strongly opine to train MBBS students in routine blood collection techniques and sensitize them to pre analytical errors which will help in reducing lab reporting errors.

scholarly journals Application of six sigma metrics and method decision charts in improvising clinical Chemistry laboratory performance enhancement

2019 ◽  
Vol 6 (5) ◽  
pp. 1524
Author(s):  
Kavita Aggarwal ◽  
Saurav Patra ◽  
Viyatprajna Acharya ◽  
Mahesh Agrawal ◽  
Sri Krushna Mahapatra
Keyword(s):  
Quality Control ◽  
Six Sigma ◽  
Performance Enhancement ◽  
Clinical Chemistry ◽  
Tertiary Care ◽  
Alternative Methods ◽  
Chemistry Laboratory ◽  
Care Hospital ◽  
Quality Performance ◽  
Clinical Chemistry Laboratory

Background: Six sigma is a powerful tool which can be used by laboratories for assessing the method quality, optimizing Quality Control (QC) procedure, change the number of rules applied, and frequency of controls run .The aim of this study was to quantify the defects or errors in the analytical phase of laboratory testing by sigma metrics and then represent the sigma value in Method Decision Chart.Methods: A retrospective study was conducted in a tertiary care hospital in Bhubaneswar, India. The clinical chemistry laboratory has been NABL accredited for the past 5 years and strictly quality checked.  Internal and external quality control data was collected for a period of six months from January - June 2018 for 20 biochemical analytes. Sigma metrics for each parameter was calculated and plotted on method decision chart.Results: The sigma metrics for level 2 indicated that 6 out of the 20 analytes qualified Six Sigma quality performance. Of these seven analytes failed to meet minimum sigma quality performance with metrics less than three and another seven analytes performance with sigma metrics was between three and six. For level 3, the data collected indicated that seven out of 20 analytes qualified Six Sigma quality performance, six analytes had sigma metrics less than 3 and seven analytes had sigma metrics between 3 and 6.Conclusion: In our study Sigma value was highest for amylase and lowest for potassium. Use of alternative methods and/ or change of reagents can be done for potassium to bring the sigma value within an acceptable range.

scholarly journals Clinical Evaluation of the Torq Zero Delay Centrifuge System for Decentralized Blood Collection and Stabilization

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1019
Author(s):  
Kyungjin Hong ◽  
Gabriella Iacovetti ◽  
Ali Rahimian ◽  
Sean Hong ◽  
Jon Epperson ◽  
...  
Keyword(s):  
Clinical Chemistry ◽  
Blood Collection ◽  
Test Results ◽  
Sample Collection ◽  
Rapid Separation ◽  
Cell Counts ◽  
Collection Device ◽  
Precision Study ◽  
Clinically Significant ◽  
Blood Specimens

Blood sample collection and rapid separation—critical preanalytical steps in clinical chemistry—can be challenging in decentralized collection settings. To address this gap, the Torq™ zero delay centrifuge system includes a lightweight, hand-portable centrifuge (ZDrive™) and a disc-shaped blood collection device (ZDisc™) enabling immediate sample centrifugation at the point of collection. Here, we report results from clinical validation studies comparing performance of the Torq System with a conventional plasma separation tube (PST). Blood specimens from 134 subjects were collected and processed across three independent sites to compare ZDisc and PST performance in the assessment of 14 analytes (K, Na, Cl, Ca, BUN, creatinine, AST, ALT, ALP, total bilirubin, albumin, total protein, cholesterol, and triglycerides). A 31-subject precision study was performed to evaluate reproducibility of plasma test results from ZDiscs, and plasma quality was assessed by measuring hemolysis and blood cells from 10 subject specimens. The ZDisc successfully collected and processed samples from 134 subjects. ZDisc results agreed with reference PSTs for all 14 analytes with mean % biases well below clinically significant levels. Results were reproducible across different operators and ZDisc production lots, and plasma blood cell counts and hemolysis levels fell well below clinical acceptance thresholds. ZDiscs produce plasma samples equivalent to reference PSTs. Results support the suitability of the Torq System for remotely collecting and processing blood samples in decentralized settings.

A qualitative assessment of the diagnosis and management of ventilator-associated pneumonia among critical care clinicians exploring opportunities for diagnostic stewardship

2021 ◽  
pp. 1-7
Author(s):  
Blaine Kenaa ◽  
Lyndsay M. O’Hara ◽  
Mary Elizabeth Richert ◽  
Jessica P. Brown ◽  
Carl Shanholtz ◽  
...  
Keyword(s):  
Tertiary Care ◽  
Qualitative Assessment ◽  
Ventilator Associated Pneumonia ◽  
Care Hospital ◽  
Sample Collection ◽  
Respiratory Sample ◽  
Identification Of Bacteria ◽  
Attending Physicians ◽  
Work Up ◽  
Radiographic Changes

Abstract Background: Prompt diagnosis and intervention for ventilator-associated pneumonia (VAP) is critical but can lead to overdiagnosis and overtreatment. Objectives: We investigated healthcare provider (HCP) perceptions and challenges associated with VAP diagnosis, and we sought to identify opportunities for diagnostic stewardship. Methods: We conducted a qualitative study of 30 HCPs at a tertiary-care hospital. Participants included attending physicians, residents and fellows (trainees), advanced practice providers (APPs), and pharmacists. Interviews were composed of open-ended questions in 4 sections: (1) clinical suspicion and thresholds for respiratory culture ordering, (2) preferences for respiratory sample collection, (3) culture report interpretation, and (4) VAP diagnosis and treatment. Interviews transcripts were analyzed using Nvivo 12 software, and responses were organized into themes. Results: Overall, 10 attending physicians (75%) and 16 trainees (75%) trainees and APPs believed they were overdiagnosing VAP; this response was frequent among HCPs in practice 5–10 years (91%, n = 12). Increased identification of bacteria as a result of frequent respiratory culturing, misinterpretation of culture data, and fear of missing diagnosis were recognized as drivers of overdiagnosis and overtreatment. Although most HCPs rely on clinical and radiographic changes to initiate work-up, the fear of missing a diagnosis leads to sending cultures even in the absence of those changes. Conclusions: HCPs believe that VAP overdiagnosis and overtreatment are common due to fear of missing diagnosis, overculturing, and difficulty distinguishing colonization from infection. Although we identified opportunities for diagnostic stewardship, interventions influencing the ordering of cultures and starting antimicrobials will need to account for strongly held beliefs and ICU practices.

scholarly journals Ecology of Bloodstream Infections and Temporal Trends of Their Antibiograms with Respect to Source and Duration of Incubation: A 5-Year Retrospective Observational Analysis

2020 ◽  
Vol 12 (01) ◽  
pp. 56-67
Author(s):  
Amit Banik ◽  
Valarie W. Lyngdoh ◽  
Elantamilan Durairaj ◽  
Anil C. Phukan ◽  
Raghavendra Kotal
Keyword(s):  
Tertiary Care ◽  
Temporal Trends ◽  
Bloodstream Infections ◽  
Diffusion Method ◽  
Blood Collection ◽  
Care Hospital ◽  
Biochemical Tests ◽  
Sensitivity Testing ◽  
Disk Diffusion Method ◽  
Significant Difference

Abstract Purpose Blood is one of the most important connective tissues of human body. Bloodstream infection can range from inapparent bacteremia till fulminant septic shock with high mortality. Presence of microbes in blood whether continuously, intermittently, or transiently is a grave risk to every organ of body. Culture of blood is a vital tool to diagnose such infections. Drug susceptibility patterns help in rationalizing therapy. Objective The aim of the study is to perform bacteriological analysis and assess drug sensitivity patterns of blood culture isolates and compare in light of other associated variables. Design Retrospective observational study was conducted from January 2009 to December 2013 at a tertiary care hospital at Shillong, India. Blood samples were collected with aseptic guidelines and cultured for 7 days. Growths were identified by standard biochemical tests and subjected to sensitivity testing according to Modified Kirby Bauer disk diffusion method. Data for source of blood collection and duration of incubation were noted and compared. Results A total of 658 (11.2%) pathogens were isolated from 5,867 bacteremia-suspected patient blood specimens. Contamination was observed at the rate of 1.21%. Gram-negative organisms were the predominant pathogens recovered, Klebsiella pneumoniae being the most common. No significant difference was observed between the number of organisms isolated within or beyond 48 hours. Acinetobacter baumannii and K. pneumoniae have significantly higher chances (p < 0.05) of isolation from central line catheters compared with peripheral venipuncture. Conclusion Successful treatment of sepsis depends on early diagnosis and proper antimicrobial therapy. Local knowledge of bacteriological profile and antimicrobial sensitivity patterns helps rationalize empiric treatment strategies.

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