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Quality-control (QC) performance measures and the QC planning process
Author(s) -
Curtis A. Parvin
Publication year - 1997
Publication title -
clinical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.705
H-Index - 218
eISSN - 1530-8561
pISSN - 0009-9147
DOI - 10.1093/clinchem/43.4.602
Subject(s) - measure (data warehouse) , quality (philosophy) , statistics , control (management) , computer science , process (computing) , error detection and correction , probability of error , reliability engineering , observational error , mathematics , algorithm , data mining , engineering , artificial intelligence , philosophy , epistemology , operating system
Numerous outcome measures can be used to characterize and compare the performance of alternative quality-control (QC) strategies. The performance measure traditionally used in the QC planning process is the probability of rejecting an analytical run when a critical out-of-control error condition exists. Another performance measure that naturally fits within the total allowable error paradigm is the probability that a reported test result contains an analytical error that exceeds the total allowable error specification. In general, the out-of-control error conditions associated with the greatest chance of reporting an unacceptable test result are unrelated to the traditionally defined "critical" error conditions. If the probability of reporting an unacceptable test result is used as the primary performance measure, worst-case QC performance can be determined irrespective of the magnitude of any out-of-control error condition that may exist, thus eliminating the need for the concept of a "critical" out-of-control error.

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