Dynamic Error Signatures in Routine Medical Laboratory Tests: A Predictive Framework for Pre-Analytical and Analytical Failure Detection
DOI:
https://doi.org/10.47352/jmans.2774-3047.232Keywords:
Dynamic error signatures, medical laboratory tests, pre-analytical errors, analytical failure detection, predictive framework, laboratory quality control, diagnostic accuracy.Abstract
Routine medical laboratory tests are critical for clinical decision-making, yet their reliability can be compromised by pre-analytical and analytical errors. This paper proposes a predictive framework based on dynamic error signatures to detect and anticipate failures in laboratory test processes. By analyzing temporal patterns and variations in test results alongside operational metadata, the framework aims to improve early detection of errors and reduce diagnostic inaccuracies. We incorporate case studies from hematology and biochemistry laboratories to demonstrate the framework's applicability. Our results indicate significant improvements in error detection sensitivity and specificity, supporting enhanced system resilience and patient safety. This study provides a foundation for integrating dynamic monitoring tools into laboratory quality management systems. [1]
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Alaa Alsefri, Rakan Turkey ALhujairy , Magdi Saleh Saad Albalawi , Ibrahim Mohammed Alsaid, Sumayyah Hamoud Alsurayyie, Rakan Saeed Alatawi, Shuaa Mohammed Gaud, Abrar Jameel Shadly Sahlah, Hind Saud Abdulaziz Alhomaidi , Nuaralden Ibrahim Abdulellah (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
- Authors retain copyright and acknowledge that the Journal of Multidisciplinary Applied Natural Science is the first publisher, licensed under a Creative Commons Attribution 4.0 International License.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges and earlier and greater citation of published work.
