Medical Device Risk Assessment Based on Ordered Weighted Averaging Aggregation Operator

Area of Science:

• Biomedical Engineering
• Healthcare Management
• Risk Management

Background:

• Medical devices require precise functioning, necessitating robust maintenance programs.
• Current maintenance strategies often overlook critical factors like equipment type, risk, and expert input.
• Effective medical device maintenance is crucial for patient safety and operational efficiency.

Purpose of the Study:

• To present a novel fuzzy logic-based method for assessing medical device risks.
• To enable data-driven prioritization of maintenance operations considering budget constraints.
• To develop a framework for optimizing medical device maintenance strategies.

Main Methods:

• Utilized the Ordered-Weighted Average (OWA) operator for aggregating diverse risk parameters.
• Developed a fuzzy multi-criteria decision-making (MCDM) model.
• Applied a risk maintenance framework for medical device prioritization.

Main Results:

• The proposed framework offers a reliable method for selecting optimal maintenance strategies within budget limitations.
• Defibrillators were identified as having the highest maintenance priority, while surgical suction devices had the lowest in the example.
• The fuzzy risk assessment effectively addresses budget constraints in medical centers.

Conclusions:

• Prioritizing medical device maintenance enhances operational efficiency and safety.
• The proposed fuzzy method facilitates strategic maintenance planning and resource allocation.
• Implementing this maintenance program can lead to significant cost savings in healthcare settings.