Integrated Quality-Control Escalation Models for High-Volume Infection Diagnostic Laboratories (Published)
High-volume infectious disease diagnostic laboratories play a pivotal role in guiding clinical management, antimicrobial stewardship, and public health surveillance, yet face unprecedented quality and operational pressures during surge testing, as vividly demonstrated by the massive scale-up of SARS-CoV-2 diagnostics during the COVID-19 pandemic. Traditional quality monitoring remains fragmented, with internal quality control (IQC), external quality assurance (EQA), equipment validation and preventive maintenance, and turnaround-time (TAT) oversight managed in independent silos, delaying recognition and response to systemic failures that can compromise diagnostic accuracy and throughput under extreme workloads.This study employed a mixed-methods, design-based research approach to develop and validate the Integrated Quality-Control Escalation Model (IQEM), a novel layered framework that continuously synthesizes real-time data from all four quality pillars into a unified, risk-based decision engine. IQEM implements dynamic combinatorial thresholds and proportionate escalation tiers—from intensified monitoring to targeted holds and full corrective action—enabling early detection and graduated intervention without unnecessary disruption of laboratory operations.Retrospective longitudinal analysis of de-identified data (IQC records, EQA results, equipment logs, and TAT distributions) from seven high-volume accredited laboratories spanning 2018–2024 was combined with a three-round modified Delphi consensus process involving 18 experienced laboratory directors and quality managers who had managed surge testing during the pandemic.Analysis showed that 68 % of validated serious quality incidents during surge periods were preceded by detectable cross-pillar signals (e.g., TAT prolongation preceding IQC violations) that remained unrecognized due to siloed monitoring. When applied retrospectively to surge datasets, IQEM detected emerging quality failures an average of 4.2 days earlier than actual interventions, with 89 % sensitivity for actionable breaches and only a 0.27 % increase in rejected runs. Expert consensus rated the model highly for clarity (8.7/9), feasibility (8.4/9), and utility in enhancing patient safety (9.0/9).The Integrated Quality-Control Escalation Model provides a practical, evidence-based framework to overcome traditional silos, delivering proactive, proportionate quality management that strengthens diagnostic reliability, preserves operational resilience, safeguards patient outcomes, and bolsters laboratory preparedness for future infectious disease surges and pandemics.
Keywords: External quality assurance, equipment validation, escalation model, high-volume laboratory, infectious disease diagnostics, integrated quality control, internal quality control, pandemic preparedness, surge testing, turnaround time monitoring