Medical Equipment Replacement Prioritisation: A Comparison Between Linear and Fuzzy System Models

Area of Science:

• Health Technology Assessment
• Hospital Management
• Medical Informatics

Background:

• Health technology assessment (HTA) techniques are crucial for effective hospital management.
• Evaluating medical equipment replacement is a key challenge in healthcare.
• Existing HTA models may lack nuanced discrimination for complex decisions.

Purpose of the Study:

• To compare the effectiveness of two distinct models for calculating equipment replacement priority values.
• To evaluate a Galliera Hospital-developed model against a fuzzy logic approach.
• To assess the discriminatory power of each model in a real-world hospital setting.

Main Methods:

• Development and application of a Galliera Hospital model based on Fennigkoh's approach, using a "yes-no" scheme for four criteria: service/support, function, cost benefits, and clinical efficacy.
• Implementation of a comparative analysis using a fuzzy logic-based model.
• Application of both models to assess the replacement priority of instrumentation at Galliera Hospital.

Main Results:

• The Galliera Hospital model demonstrated a conservative approach, recommending the retention of 77.4% of analyzed instrumentation.
• The fuzzy logic model provided superior discrimination among medical devices, differentiating their replacement priorities more effectively.
• The study highlights differences in decision-making outputs between rule-based and fuzzy logic HTA models.

Conclusions:

• Fuzzy logic models offer enhanced capabilities for nuanced health technology assessment and equipment replacement decisions in hospitals.
• The Galliera model, while systematic, may be less effective in identifying critical replacement needs compared to fuzzy logic.
• Optimizing HTA methodologies is essential for efficient hospital resource allocation and patient care improvement.