scholarly journals Study on "Pre-analytical Errors in a Clinical Biochemistry Laboratory:" The Hidden Flaws in Total Testing

2019 ◽  
Vol 08 (01) ◽  
Author(s):  
Sushma BJ ◽  
Shrikant C
Keyword(s):  
Clinical Biochemistry ◽  
Clinical Biochemistry Laboratory ◽  
Analytical Errors

scholarly journals A study of pre-analytical errors in the clinical biochemistry laboratory at Victoria hospital, BMCRI, Bangalore

2022 ◽  
Vol 8 (4) ◽  
pp. 278-280
Author(s):  
Sreeja Shanker J ◽  
H L Vishwanath ◽  
Vibha C ◽  
Muralidhara Krishna
Keyword(s):  
Observational Study ◽  
Prospective Observational Study ◽  
Clinical Biochemistry ◽  
Phase Error ◽  
Percentage Error ◽  
Corrective Measures ◽  
Analytical Phase ◽  
Clinical Biochemistry Laboratory ◽  
Phase Evaluation ◽  
Analytical Errors

To categorize and calculate the percentage error of pre-analytical variables in the clinical biochemistry laboratory. Prospective observational study conducted for two months with documenting the frequency and type of pre-analytical errors occurring in venous samples. The total errors recorded were 1.31%. Insufficient volume followed by haemolysis amounted to a major proportion of errors. Continuous pre-analytical phase evaluation and taking corrective measures to make this phase error-free, have to be done.

scholarly journals RETROSPECTIVE EVALUATION OF PRE-ANALYTICAL ERRORS IN CLINICAL BIOCHEMISTRY LABORATORY AT A TERTIARY CARE CENTRE IN RAJSAMAND, RAJASTHAN.

2020 ◽  
Vol 4 (7) ◽  
Author(s):  
Richa K. Lath ◽  
Umeshkumar Pareek ◽  
Renu Sharma ◽  
Aniruddha N. Jibhkate ◽  
Ashish A. Jadhav ◽  
...  
Keyword(s):  
Clinical Biochemistry ◽  
Tertiary Care ◽  
Tertiary Care Centre ◽  
Percentage Occurrence ◽  
Preventive Actions ◽  
Ensure Patient Safety ◽  
Different Types ◽  
Analytical Phase ◽  
Clinical Biochemistry Laboratory ◽  
Analytical Errors

Background: This study was carried out to identify the causes of pre-analytical errors in the clinical biochemistry laboratory and their percentage occurrence so as to formulate the strategy for necessary corrective and preventive actions. Methods: A retrospective quantitative study was conducted in the department of biochemistry to identify the different causes of pre-analytical errors in the outpatient and inpatient samples. The sample rejection register and test requisition forms for the period of May 2018 to April 2019 were analysed and the percentage occurrence of the different types of errors was calculated. Results: Data analysis revealed that the occurrence of different errors was as follows: hemolysis (46.43%), sample not received (28.32%), insufficient quantity (8.16%), improper collection technique (7.14%), delayed transport (5.87%), wrong container (1.79%), sample clotted (1.28%), lipemic sample (0.77%) and sample exchanged during separation in lab (0.26%). Conclusion: The decline in the errors during the analytical phase of sample processing has shifted the focus towards reducing errors occurring in the pre-analytical phase. This is necessary to ensure patient safety. Keywords: Pre-analytical errors, Biochemistry, hemolysis.

scholarly journals High preanalytical non-compliance and samples rejection rate in clinical biochemistry laboratory are decreased by nurse staff training in phlebotomy and sample handling

2020 ◽  
Vol 13 (3) ◽  
pp. 113-118
Author(s):  
Modibo Coulibaly ◽  
Abdelaye Keita ◽  
Moussa Diawara ◽  
Valentin Sagara ◽  
Brehima Traoré ◽  
...  
Keyword(s):  
Staff Training ◽  
Clinical Biochemistry ◽  
Statistical Significance ◽  
Venous Blood ◽  
Diagnostic Errors ◽  
Hospital Staff ◽  
Clinical Samples ◽  
Sample Handling ◽  
Significant Difference ◽  
Clinical Biochemistry Laboratory

Background: Preanalytical phase of biomedical analysis remains an important source of diagnostic errors that deserves special attention. This study aims to evaluate the training in phlebotomy and sample handling impact on the preanalytical non-compliances. Material and Methods: we performed a prospective study before and after staff training in phlebotomy and sample handling by systematically recording all clinical samples non-compliances. First, we assessed and describe the non-compliance baseline rate from January to December 2017 in the clinical biochemistry laboratory of Hôpital Sominé DOLO de Mopti. After two sessions of one week staff training in January 2018, we performed the same study from January to December 2018. We compared the proportions of non-compliances between the two assessments. Data were collected on the case report forms, captured in Excel and analyzed by R software for (Mac) OS X version 4.0.3. Pearson Ch2 or Fisher exact tests were used for the comparison of proportions. The statistical significance was set at p < 5%. Results: a total of 27,810 venous blood samples were received during the study period; 48% was for biochemistry, 41% for immuno-serology, 9% for blood cell count and 2% for coagulation tests. There were 3,826 instances of preanalytical non-compliances (13.76%) identified that led to sample rejection. Out of the 11 types of non-compliances investigated, 5 (45.4%) accounted for nearly 91% of the problems: insufficient sample volume (28.9%), hemolyzed samples (20.5%), inappropriate collection time (17.8%), sample clot (12.9%), and inappropriate sample collection tube (10.8%). We observed a significant difference in rates of non-compliance between inpatients and outpatients samples (44.4% vs 7.3%; p < 0.001). The proportion of non-compliance have significatively decreased after the two training sessions of hospital staff in phlebotomy and sample handling 3,826/27,810 (13.8%) vs 3,009/32,476 (9.3%); p < 0.001. Conclusion: we report a significantly higher rate of non-compliance in inpatients. Hospital staff training in phlebotomy and sample handling reduce the proportion of preanalytical non-compliance and thereby improve patient management and safety.

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 Application of Sigma Metrics for Evaluating the Analytical Performance of Thyroid Profile and Cortisol in Clinical Biochemistry Laboratory

2020 ◽  
Author(s):  
Smita Natvarbhai Vasava ◽  
Roshni Gokaldas Sadaria
Keyword(s):  
Quality Control ◽  
Six Sigma ◽  
Clinical Laboratory ◽  
Clinical Biochemistry ◽  
Poor Performance ◽  
Analytical Performance ◽  
Internal Quality ◽  
Six Sigma Methodology ◽  
Clinical Biochemistry Laboratory ◽  
Thyroid Profile

Introduction: Now-a-days quality is the key aspect of clinical laboratory services. The six sigma metrics is an important quality measurement method for evaluating the performance of the clinical laboratory. Aim: To assess the analytical performance of clinical biochemistry laboratory by utilising thyroid profile and cortisol parameters from Internal Quality Control (IQC) data and to calculate sigma values. Materials and Methods: Study was conducted at Clinical Biochemistry Laboratory, Dhiraj General Hospital, Piparia, Gujarat, India. Retrospectively, IQC data of thyroid profile and cortisol were utilised for six subsequent months (July to December 2019). Coefficient of Variation (CV%) and bias were calculated from IQC data, from that the sigma values were calculated. The sigma values <3, >3 and >6 were indicated by poor performance procedure, good performance and world class performance, respectively. Results: The sigma values were estimated by calculating mean of six months. The mean sigma value of Thyroid Stimulating Hormone (TSH) and Cortisol were >3 for six months which indicated the good performance. However, sigma value of Triiodothyronine (T3), Tetraiodothyronine (T4) were found to be <3 which indicated poor performance. Conclusion: Six sigma methodology applications for thyroid profile and cortisol was evaluated, it was generally found as good. While T3 and T4 parameters showed low sigma values which requires detailed root cause analysis of analytical process. With the help of six sigma methodology, in clinical biochemistry laboratories, an appropriate Quality Control (QC) programming should be done for each parameter. To maintain six sigma levels is challenging to quality management personnel of laboratory, but it will be helpful to improve quality level in the clinical laboratories.

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