Minimizing the Risk of Biological Specimen Mix-Up in the Mammography Unit: A Failure Mode and Effect Analysis (FMEA) Methodology in Oncology Setting
Rawan Ibrahim, Badriya Al Qassabi, Zaid Al-Ishaq, Rashid Al-Sukaiti, Adil Al-Ajmi, Shima Alajmi, Ahmed Sheikh Omar, Mohamad Majed 等 15 位
Sultan Qaboos Comprehensive Cancer Care & Research Center Sultan Qaboos University Sultan Qaboos University Hospital Hashemite University
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Background: Effective cancer management relies heavily on early diagnosis, which significantly improves patient outcomes by enabling timely and accurate treatment decisions. Despite advancements in diagnostic tools, the risk of specimen mix-ups remains a critical challenge, particularly in the pre-analytic phase of specimen collection.Purpose: This study aimed to minimize the risk of biological specimen mix-ups in the mammography unit in Oncology center through the implementation of the Failure Mode and Effect Analysis (FMEA) methodology. Methods: A proactive FMEA was conducted in the mammography unit, targeting the pre-analytic phase of specimen collection. A multidisciplinary team identified potential failure modes, assessed their severity, occurrence, and detection, and calculated the Risk Priority Numbers (RPNs). Interventions were developed and implemented to address high-risk areas, with post-intervention RPNs evaluated to measure the effectiveness of the changes. Results: The analysis revealed high-risk failure modes, including patient misidentification, labeling errors, and inadequate specimen tracking, with initial RPNs ranging from 280 to 360. Interventions such as standardizing patient identification, improving consent processes, and enhancing specimen labeling systems led to significant RPN reductions across all categories, with the most notable improvement observed in site marking (67% reduction). Conclusion: The proactive use of FMEA effectively identified, mitigated the risks, and enhanced the safety and reliability of specimen collection in the mammography unit. This approach highlights the importance of applying systematic risk management processes in improving diagnostic accuracy and patient safety, providing a model for other healthcare settings.
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