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A new method based on fuzzy logic to evaluate the contract service provider performance.
C A Miguel1, C Barr, M J L Moreno
1Rosario University, School of Medicine, Bogota, DC, Colombia.
Journal of Medical Engineering & Technology
|July 31, 2008
Summary
This study introduces a fuzzy inference system to assess service quality for contract providers. The system improved service cost reduction and system availability while maintaining repair quality in hospitals.
Area of Science:
- Engineering
- Computer Science
- Healthcare Management
Background:
- Evaluating service quality in maintenance contracts is crucial for operational efficiency.
- Existing methods may lack the precision to capture complex service performance dynamics.
- The application service provider (ASP) model offers a framework for managing computerized maintenance.
Purpose of the Study:
- To develop and evaluate a fuzzy inference system (FIS) for assessing the service quality performance of contract providers.
- To apply the FIS within a computerized maintenance management context in hospital settings.
- To quantify the impact of the FIS on key performance indicators.
Main Methods:
- A fuzzy inference system was designed to evaluate service quality.
- An application service provider (ASP) model for computerized maintenance management was utilized.
- Performance indicators were established and monitored in 10 hospitals over a 14-month period.
Main Results:
- The fuzzy inference system led to a significant reduction in the service cost/acquisition cost (SC/AC) ratio, decreasing from 16.14% to 6.09%.
- System availability increased by 20.9% following the implementation of the FIS.
- Repair quality, measured by the normalized repair rate (NRR), was maintained throughout the study period.
Conclusions:
- Fuzzy inference systems provide an effective tool for evaluating and improving service quality in maintenance contracts.
- The ASP model, integrated with FIS, demonstrates tangible benefits in healthcare settings, including cost savings and enhanced operational availability.
- This approach offers a robust method for performance monitoring and quality assurance in service contract management.
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