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  4. Pro-Active Detection of Potentially Wrong Diagnoses Due to Substantial Changes of Laboratory Measurements
 

Pro-Active Detection of Potentially Wrong Diagnoses Due to Substantial Changes of Laboratory Measurements

URI
https://arbor.bfh.ch/handle/arbor/33714
Version
Published
Date Issued
2022-01-14
Author(s)
Abu Baker, Motaas
Sariyar, Murat  
Holm, Jürgen  
Calderara, Fabienne
Type
Article
Language
English
Abstract
For guiding decisions on medical diagnoses and diagnoses, it is crucial to receive valid laboratory test results. However, such results can be implausible for the physician, even if the measurements are within the range of known reference values. There are technical sources of implausible results that are related to the laboratory environment, which are frequently not detected through usual measures for ensuring technical validity. Here, we describe the development of a quality assurance tool that tackles this problem and replaces the current manual statistical analyses at the Center for Laboratory Medicine in St Gallen (ZLM). Further analysis of the factors responsible for shifts in laboratory test results requires to collect and analyze data related to reagents as well as calibration or reference probes. Due to a lack of standard operating procedures in many laboratories with respect to these processes, this remains one of the big challenges.
Subjects
QA75 Electronic computers. Computer science
ISBN
9781643682501
DOI
10.24451/arbor.18474
https://doi.org/10.24451/arbor.18474
Publisher DOI
10.3233/SHTI210856
Journal
Studies in Health Technology and Informatics
Series/Report No.
Studies in Health Technology and Informatics
ISSN
1879-8365
Publisher URL
https://ebooks.iospress.nl/doi/10.3233/SHTI210856
Organization
Institut für Medizininformatik I4MI  
Technik und Informatk  
Volume
289
Publisher
IOS Press
Submitter
Sariyar, Murat
Citation apa
Abu Baker, M., Sariyar, M., Holm, J., & Calderara, F. (2022). Pro-Active Detection of Potentially Wrong Diagnoses Due to Substantial Changes of Laboratory Measurements. In Studies in Health Technology and Informatics (Vol. 289). IOS Press. https://doi.org/10.24451/arbor.18474
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