biostudies-literatureZhaxi BPeking Union Medical College Hospital Youth Category-D ProgramBeijing Natural Science Foundation - Daxing Innovation Joint Fund288https://www.ebi.ac.uk/biostudies/studies/S-EPMC12839619biostudies-literatureUnknown16(2)<b>Background:</b> Patient-based real-time quality control (PBRTQC) enables continuous analytical monitoring using routine patient results; however, the performance of classical statistical process control (SPC) algorithms varies across analytes, and standardized evaluation and optimization strategies remain limited. To address this gap, this study compared three SPC algorithms-moving average (MA), moving quantile (MQ), and exponentially weighted moving average (EWMA)-within a unified preprocessing framework and proposed a composite performance metric for parameter optimization. <b>Methods:</b> Routine patient results from six laboratory analytes were analyzed using a standardized "transform-truncate-alarm" PBRTQC workflow. Simulated systematic biases were introduced for model training, anDiagnostics (Basel, Switzerland)Comparison of EWMA, MA, and MQ Under a Unified PBRTQC Framework for Thyroid and Coagulation Tests.PMC12839619L256080UHB12728Zhaxi BDing WLi XChen QMa CHu YQiu LfalseComparison of EWMA, MA, and MQ Under a Unified PBRTQC Framework for Thyroid and Coagulation Tests.<b>Background:</b> Patient-based real-time quality control (PBRTQC) enables continuous analytical monitoring using routine patient results; however, the performance of classical statistical process control (SPC) algorithms varies across analytes, and standardized evaluation and optimization strategies remain limited. To address this gap, this study compared three SPC algorithms-moving average (MA), moving quantile (MQ), and exponentially weighted moving average (EWMA)-within a unified preprocessing framework and proposed a composite performance metric for parameter optimization. <b>Methods:</b> Routine patient results from six laboratory analytes were analyzed using a standardized "transform-truncate-alarm" PBRTQC workflow. Simulated systematic biases were introduced for model training, an2026-01-01T00:00:00Z2026 Jan2026-06-17T03:22:32.167Z2026-06-17T03:10:39.891ZS-EPMC128396194159426610.3390/diagnostics16020288