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- Title
Risk Analysis for Quality Control Part 1: The Impact of Transition Assumptions in the Parvin Model.
- Authors
Schmidt, Robert L; Moore, Ryleigh A; Walker, Brandon S; Rudolf, Joseph W
- Abstract
Background: Setting quality control (QC) limits involves balancing the risk of false-positive results and false-negative results. Recent approaches to QC have focused on the assessment of false-negative results. The Parvin model is the most-used model for risk analysis. The Parvin model assumes that the system makes a transition from an in-control to an out-of-control (OOC) state but makes no further transitions after moving to the OOC state. The implications of this assumption are unclear. Methods: We used simulation experiments to compare the performance of QC systems based on no OOC transitions allowed (NOOCTA) vs systems where OOC transitions were allowed (OOCTA). Results: The NOOCTA assumption leads to paradoxical tradeoff curves between false-positive results and false-negative results. Predictions of a false-negative result based on NOOCTA were about 10 times lower than models based on OOCTA. Conclusions: The most common models for QC risk analysis underestimate false-negative results. There is a need to develop better risk-based methods for QC analysis.
- Subjects
RISK assessment; QUALITY control; FALSE positive error
- Publication
Journal of Applied Laboratory Medicine, 2023, Vol 8, Issue 1, p14
- ISSN
2475-7241
- Publication type
Article
- DOI
10.1093/jalm/jfac117