Failure Mode and Effects Analysis (FMEA) integrating quality indicators for risk assessment of the total testing process in human papillomavirus genotyping testing: a proactive risk analysis model for molecular diagnosticsTingting Lion August 29, 2025 at 10:00 am

Clin Chem Lab Med. 2025 Aug 29. doi: 10.1515/cclm-2025-0598. Online ahead of print.

ABSTRACT

OBJECTIVES: To develop a proactive risk assessment model for human papillomavirus (HPV) genotyping testing by integrating Failure Mode and Effects Analysis (FMEA) with quality indicators (QIs), ensuring compliance with ISO 15189:2022 and improving diagnostic accuracy.

METHODS: A multidisciplinary team designed and performed detailed FMEA across pre-analytical, analytical, and post-analytical phases of HPV genotyping testing. To improve objectivity, we integrated Sigma metrics into the FMEA framework through a molecular diagnostics-specific model of QIs (MQI). The FMEA model systematically identified testing phases, potential failure modes, their effects, root causes, and existing controls. Risk was quantified using Severity, Occurrence (from 1-year QI data), and Detection scores (1-5 scale). Risk Priority Numbers (RPNs) were calculated (Severity × Occurrence × Detection) to prioritize failure modes, with mandatory interventions implemented for high-risk items (RPN≥40).

RESULTS: Five high-risk failure modes (e.g., sample misidentification, data analysis errors) were identified and successfully mitigated to acceptable levels (RPN<40) through process optimization and standardization, achieving RPN reductions of 20-80 %. We established a molecular diagnostics-specific MQI, comprising 14 pre-analytical, 25 analytical, and three post-analytical phase QIs. QI-based risk assessment of 35 evaluable QIs for HPV genotyping testing revealed one high-risk QI (“Incorrect results due to information system failures”) and three medium-risk QIs, all of which were addressed through corrective actions.

CONCLUSIONS: This study developed an integrated FMEA-QI model for HPV genotyping testing, establishing both a traditional FMEA framework and a molecular diagnostics-specific MQI. The combined approach improves risk assessment objectivity and enables multidimensional analysis compared to conventional methods.

PMID:40879430 | DOI:10.1515/cclm-2025-0598

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