scholarly journals Evaluation of the Atellica COAG 360 coagulation analyzer in a central laboratory of a maximum care hospital

2019 ◽  
Vol 42 (1) ◽  
pp. 28-36
Author(s):  
Sebastian Hörber ◽  
Rainer Lehmann ◽  
Andreas Peter
PLoS ONE ◽  
2016 ◽  
Vol 11 (11) ◽  
pp. e0166521 ◽  
Author(s):  
Ramona C. Dolscheid-Pommerich ◽  
Sarah Dolscheid ◽  
Daniel Grigutsch ◽  
Birgit Stoffel-Wagner ◽  
Ingo Graeff

Author(s):  
Kavita Aggarwal ◽  
Sumit Jhajharia ◽  
Tapaswini Pradhan ◽  
Viyatprajna Acharya ◽  
Saurav Patra ◽  
...  

Introduction: Medical and laboratory errors can be caused due to many reasons, including communication problem, inadequate training of the staff members, improper identification. Quality indicators can help in objective measurement of errors in various crucial steps. Aim: To determine the nature and frequency of preanalytical, some of the analytical and postanalytical errors in the clinical laboratory with the help of quality indicators. Materials and Methods: This was a retrospective study and data was collected for preanalytical, some of analytical and postanalytical errors from December 2020 to May 2021, from the central laboratory and were classified under various quality indicators. MS Excel was used to analyse the data and descriptive statistics such as number and percentage were used to present the data. Results: Out of the total 677,887 samples received from both Outpatient Department (OPD) and Inpatient Department (IPD) in the central laboratory for clinical chemistry, preanalytical error was found in 482 samples (0.071%) and most common was haemolysis and billing errors. Out of total 677,887 samples received repeat testing was done in 287 samples (0.042%), Turnaround Time (TAT) exceeded in total 2,29,629 samples (33.87%) and transcription errors/amended report were seen in 41 (0.006%). Conclusion: Sample haemolysis, billing errors, insufficient sample and clotted sample are the most common preanalytical errors encountered in clinical laboratory. The TAT was exceeded in one third of the samples. These errors can be minimised by repeated training, annual competency assessment and more automation in preanalytical phase.


Author(s):  
Dr Nirali V Shah ◽  
Vidhi Shah ◽  
Dr. Falguni Goswami ◽  
Dr. Roopam Gidwani ◽  
Dr. Shobhana Prajapati ◽  
...  

2018 ◽  
Vol 5 (1) ◽  
pp. 22-40
Author(s):  
Ramona Dolscheid-Pommerich ◽  
◽  
Sarah Dolscheid ◽  
Lars Eichhorn ◽  
Birgit Stoffel-Wagner ◽  
...  

Vacunas ◽  
2020 ◽  
Vol 21 (2) ◽  
pp. 95-104 ◽  
Author(s):  
Y.M. AlGoraini ◽  
N.N. AlDujayn ◽  
M.A. AlRasheed ◽  
Y.E. Bashawri ◽  
S.S. Alsubaie ◽  
...  

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