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Published on: May 11, 2014
Automated Risk Control in Medical Imaging Equipment Management Using Cloud Application
Sally M Ghanem1, Manal Abdel Wahed1, Neven Saleh2
1Systems and Biomedical Engineering Department, Faculty of Engineering, Cairo University, Giza, Egypt.
This study introduces a new methodology for managing risks associated with medical imaging equipment (MIE). It uses key performance indicators (KPIs) and undesired events (UDEs) to control risks effectively in healthcare settings.
Area of Science:
- Healthcare technology management
- Risk assessment and control
- Medical device safety
Background:
- Medical imaging equipment (MIE) is crucial for patient diagnosis but poses significant risks to patients, operators, and the environment.
- Risk management in MIE is underrepresented in existing literature.
- Current practices often overlook comprehensive risk assessment for MIE.
Purpose of the Study:
- To propose a novel methodology for controlling risks associated with medical imaging equipment management.
- To develop a framework for identifying and evaluating risks in MIE.
- To enhance the safety and efficiency of MIE in healthcare facilities.
Main Methods:
- Development of a risk management methodology based on key performance indicators (KPIs) and undesired events (UDEs).
- Utilizing a risk matrix to evaluate risk levels.
- Implementation of cloud computing software for risk control.
- Validation using a dataset of 204 MIE units across 104 hospitals.
Main Results:
- The proposed KPIs and UDEs were found appropriate for risk evaluation and control.
- The methodology effectively identified and managed risks associated with MIE.
- Cloud computing facilitated manageable risk control.
Conclusions:
- The study validates the proposed methodology for MIE risk management.
- Optimizing risk control, considering costs, significantly impacts MIE management.
- Implementing this framework can improve patient safety and operational efficiency in healthcare.
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