Discussion on the Quality Control of Microbiological Test on Clinical Application

2021 ◽  
2009 ◽  
Vol 128 (1-3) ◽  
pp. 16-23 ◽  
Author(s):  
Falko Steinbach ◽  
Sabine Bischoff ◽  
Hannah Freund ◽  
Simone Metzner-Flemisch ◽  
Sherif Ibrahim ◽  
...  

1992 ◽  
Vol 31 (02) ◽  
pp. 126-134 ◽  
Author(s):  
K. Kotzke ◽  
D.-P. Pretschner

Abstract:The assessment of the results of a “knowledge-based system” (KBS) for quality control is a basic requirement for clinical application: Large numbers of test studies are necessary in order to cover as widely as possible the spectrum of cases to be analyzed by the KBS. The use of original patient data as test data is one possibility, but real data are provided unevenly. This is due to the set of characteristics which are relevant to the analysis. Data are available in a limited quantity only. This implies a remaining set of unvalidated cases which are not represented in the data pool. The software phantom is an approach towards systematically guided validation. It permits the generation of test data adjusted to the demands of the validation.


2020 ◽  
Vol 5 (6) ◽  
pp. 1184-1193 ◽  
Author(s):  
Huub H van Rossum ◽  
Daan van den Broek

Abstract Background In recent years there has been renewed interest in patient-based real-time quality control (PBRTQC) techniques. This interest has been stimulated by the availability of new optimization and validation methods. Only a limited amount of research has focused on investigating the true operational value of PBRTQC. Therefore, we have evaluated the performance and value of recently implemented patient moving average quality control (MA QC) procedures. Methods The MA QC settings and protocols were as previously described (Clin Chem Lab Med 2019;57:1329–38) and included MA QCs for 10 chemistry and 6 hematological tests, all performed on duplicate analyzer systems. All MA QC alarms that occurred during the first 10 months of routine clinical application were investigated for assay-specific alarm rate and occurrence in time. Furthermore, the causes of these MA QC alarms were investigated, and alarm relevance was determined on the basis of total allowable bias (TBa) and error (TEa) derived from biological variations. Results During the 10-month period, 202 individual MA QC alarms occurred, resulting in an overall MA QC alarm rate of 0.030% and a frequency of 4.67 per week. Most alarms were triggered by sodium MA QC. Based on all available fully executed and documented MA QC alarm work-ups, MA QC detected errors that in 26.0% of the alarms exceeded the TBa and in 13.7% the TEa. In 9.2% of the alarms, MA QC alarming triggered instant (technical) corrections. Conclusions Routine clinical application of MA QC is feasible with maintaining a manageable number of alarms and enabling detection of relevant analytical errors.


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