Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/9767
Title: Ανίχνευση συστηματικών σφαλμάτων σε αυτόματους αναλυτές με την χρήση της μέσης τιμής των αναλύσεων
Authors: Καρκαλούσος, Πέτρος
Item type: Journal article
Keywords: Έλεγχος ποιότητας;Συστηματικά σφάλματα;Ημερήσια φυσιολογική μέση τιμή;Κινητός μέσος;Quality control;Systematic errors;Average of patients;Moving average
Subjects: Medicine
Technology
Ιατρική
Τεχνολογία
Issue Date: 5-May-2015
Jan-2005
Date of availability: 5-May-2015
Language: Greek
Citation: Καρκαλούσος, Π. (2005) Ανίχνευση συστηματικών σφαλμάτων σε αυτόματους αναλυτές με την χρήση της μέσης τιμής των αναλύσεων. "Εφαρμοσμένη Κλινική Μικροβιολογία και Εργαστηριακή Διαγνωστική", 10 (1), σ. 18-25. Διαθέσιμο στο: http://users.teiath.gr/petef/Web_CV/Articles/Articles_pdf/QC_%20by_%20using_%20many_%20patients%20results_Karkalousos.pdf [Έγινε Πρόσβαση: 05/05/2015].
Journal: Εφαρμοσμένη Κλινική Μικροβιολογία και Εργαστηριακή Διαγνωστική
Type of Journal: With a review process (peer review)
Table of contents: The quality control methods which based on the patients’ results have been proposed as secondary methods for the detection of systematic errors. They are quite useful for the continuously watching of the patients’s results through out the day without the use of control specimens. Τhey are irreplaceable when there are no control specimen for a specific analyte. These methods are the average of patients, the moving average and the Bull’s algorithm. The most known method is Bull ’s algorithm which is a kind of moving average method. Bull ’s algorithm is valid since even the number of patients is small and the results are not all normal. It is used in hematological analyzers and specifically for the erythrocyte indexes (MCV, MCH, MCHC). Despite their importance they have not be enused extensively because of their complicated calculations and the daily hard work they demand. Nowadays, the new software systems which are used in Hellenic medical laboratories have special routines for the daily application of average of patients. The user of these software systems has to define the minimum number of normal values ( Ν ) which are demanding daily in order the method to be reliable. The most successful way for the estimation of the minimum number of normal values is the normogram of Cembrowski et al. This normogram correlates the number N with the ratio of the variance of normal results by the analytical variation of the method.
Access scheme: Publicly accessible
License: An error occurred on the license name.
URI: http://hdl.handle.net/11400/9767
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