A Novel Hybrid PFMEA-HFMEA Framework for Risk Assessment in Medical Imaging: Insights from Developing Healthcare Systems

Mahdi Alinia  Ahandani; Mehdi  Raei; Mahboubeh  Rouhollahei; Firouz  Valipour; Milad  Derakhshanjazari

doi:10.18502/jhsw.v16i1.21889

Mahdi Alinia Ahandani Student Research Committee, Baqiyatallah University of Medical Sciences, Tehran, Iran
Mehdi Raei Department of Occupational Health Engineering, Faculty of Health, Baqiyatallah University of Medical Sciences, Tehran, Iran
Mahboubeh Rouhollahei Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
Firouz Valipour Department of Occupational Health Engineering, Faculty of Health, Baqiyatallah University of Medical Sciences, Tehran, Iran
Milad Derakhshanjazari Department of Occupational Health Engineering, Faculty of Health, Baqiyatallah University of Medical Sciences, Tehran, Iran

DOI: https://doi.org/10.18502/jhsw.v16i1.21889

Keywords: Medical Imaging, MRI, CT Scan, Risk Assessment, PFMEA, HFMEA

Abstract

Introduction: Medical imaging modalities such as MRI and CT scans are indispensable for accurate diagnosis, yet they pose substantial operational and patient safety risks—particularly in resource-limited healthcare systems.

Material and Methods: This applied methodological study, conducted from July 2024 to April 2025, used a four-phase methodology: scoping, data collection, framework development, and risk analysis. Data were gathered through FGDs involving radiologists, technicians and HSE experts and also with semi-structured interviews and process mapping, which identified 125 failure modes across nine workflow stages. PFMEA assessed operational risks, whereas HFMEA focused on patient-centric hazards. A composite risk indicator that comprising 40% PFMEA RPN and 60% HFMEA hazard score, prioritized risks. Statistical analyses, including Shapiro-Wilk, Spearman’s correlation and Kruskal-Wallis tests, were used to evaluate risk distributions and inter-stage variability.

Results: The framework identified critical risks, such as insufficient operator training and staff fatigue, with post-process management and image reconstruction as high-risk phases. MRI and CT units showed distinct yet overlapping risk profiles that show significant inter-stage variability (p<0.001). The hybrid model integrated operational and clinical perspectives, which outperformed standalone FMEA methods.

Conclusion: This hybrid PFMEA-HFMEA framework offers a scalable and context-sensitive approach to enhance patient safety with operational resilience in medical imaging. Further studies should authenticate the framework in different settings and investigate long-term mitigation strategies to enhance radiology risk management.