Optimized, Person-Centered Workflow Design for a High-Throughput Breast MRI Screening Facility-A Simulation Study
- PMID: 38193779
- DOI: 10.1097/RLI.0000000000001059
Optimized, Person-Centered Workflow Design for a High-Throughput Breast MRI Screening Facility-A Simulation Study
Abstract
Objectives: This project aims to model an optimal scanning environment for breast magnetic resonance imaging (MRI) screening based on real-life data to identify to what extent the logistics of breast MRI can be optimized.
Materials and methods: A novel concept for a breast MRI screening facility was developed considering layout of the building, workflow steps, used resources, and MRI protocols. The envisioned screening facility is person centered and aims for an efficient workflow-oriented design. Real-life data, collected from existing breast MRI screening workflows, during 62 scans in 3 different hospitals, were imported into a 3D simulation software for designing and testing new concepts. The model provided several realistic, virtual, logistical pathways for MRI screening and their outcome measures: throughput, waiting times, and other relevant variables.
Results: The total average appointment time in the baseline scenario was 25:54 minutes, with 19:06 minutes of MRI room occupation. Simulated improvements consisted of optimizing processes and resources, facility layout, and scanning protocol. In the simulation, time spent in the MRI room was reduced by introducing an optimized facility layout, dockable tables, and adoption of an abbreviated MRI scanning protocol. The total average appointment time was reduced to 19:36 minutes, and in this scenario, the MRI room was occupied for 06:21 minutes. In the most promising scenario, screening of about 68 people per day (10 hours) on a single MRI scanner could be feasible, compared with 36 people per day in the baseline scenario.
Conclusions: This study suggests that by optimizing workflow MRI for breast screening total appointment duration and MRI occupation can be reduced. A throughput of up to 6 people per hour may be achieved, compared with 3 people per hour in the current setup.
Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.
Conflict of interest statement
Conflicts of interest and sources of funding: This work was financed by a grant from ZonMW and supported by Siemens Healthineers, Erlangen, Germany. M.P. reports grants and personal fees from Siemens Healthineers during the conduct of the study; grants and personal fees from Canon Medical Systems; and personal fees from Bracco, outside the submitted work. R.M.M. reports grants, personal fees, and nonfinancial support from Siemens; grants and personal fees from Bayer; grants and nonfinancial support from Screenpoint; grants, personal fees, and nonfinancial support from BD; grants and nonfinancial support from Koning; and grants and nonfinancial support from PA Imaging, outside the submitted work. A.S. and M.S. are employees of Siemens Healthineers and declare that they have no further conflict of interest. The remaining authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.
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