MRI workflow efficiency: Economic constraints, operational bottlenecks, and technological innovation.
Authors
Affiliations (5)
Affiliations (5)
- University of the Incarnate Word School of Osteopathic Medicine, San Antonio, TX, United States of America.
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States of America.
- Department of Radiology, Sina Hospital and Heart Center, Isfahan, Iran.
- Department of Biomedical Sciences, Baptist University College of Osteopathic Medicine, Memphis, TN, United States of America.
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States of America. Electronic address: [email protected].
Abstract
Magnetic Resonance Imaging (MRI) is an essential diagnostic modality valued for its superior soft tissue characterization, yet it remains among the most resource-intensive in clinical radiology. Financial sustainability is increasingly challenged by high capital and fixed operational costs, rising labor and maintenance expenses, workflow inefficiencies, and constrained reimbursements amid growing demand. This review synthesizes recent literature to highlight key strategies for optimizing MRI workflow efficiency across economic, operational, and technological domains. Critical approaches include workflow redesign (up to ∼20% improvement in scanning throughput over baseline), targeted staff training (∼30%), scheduling improvements (∼15%), and selective integration of artificial intelligence tools including protocol optimization (∼35%); these individual estimates are derived from studies of isolated interventions and are not expected to add linearly. An exploratory model based on reported improvements from individual studies suggests that combining multiple workflow optimization strategies could conservatively yield revenue gains on the order of 40-60%/scanner (approximately $780,000/year, assuming a middle-range baseline of ∼$1,560,000/year). These projections are hypothetical, are not derived from integrated real-world data, and should be interpreted as conceptual estimates. Broader development and implementation of efficiency strategies may help support the financial sustainability of MRI capable practices, although real-world outcomes will vary depending on local operational context and implementation fidelity.