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Knowledge management system for benchmarking performance indicators using statistical process control (SPC) and
Satheesh B Parachoor1, Eric Rosow, John D Enderle
1University of Connecticut, Storrs, Connecticut 06269-2157, USA.
Summary
Clinical engineering departments can leverage knowledge management systems for data-driven decision-making. These systems facilitate performance comparisons, enhancing quality improvement initiatives and operational efficiency in healthcare.
Area of Science:
- Healthcare Management
- Information Science
- Clinical Engineering
Background:
- The healthcare landscape is dynamic, with increasing emphasis on quality improvement and cost containment.
- Benchmarking, both internally and against peers/competitors, has gained prominence.
- The Joint Commission for the Accreditation of Hospital Organization (JCAHO) mandates participation in the ORYX program for accredited acute care organizations.
Purpose of the Study:
- To introduce a knowledge management system designed for clinical engineering departments.
- To facilitate the transformation of data into actionable knowledge for improved decision-making.
- To support performance comparison and sharing of best practices among healthcare institutions.
Main Methods:
- Development of a knowledge management system tailored for clinical engineering.
- Integration of data analysis tools for internal and peer benchmarking.
- Creation of a platform for sharing departmental procedures, data, and methodologies.
Main Results:
- The system enables clinical engineering managers to access financial and quality metrics efficiently.
- Facilitates sophisticated analysis, accurate modeling, and forecasting.
- Supports timely, data-driven decisions for enhanced operational performance.
Conclusions:
- Knowledge management systems empower clinical engineering departments to optimize performance through data utilization.
- These systems are crucial for navigating the evolving healthcare environment and meeting accreditation requirements.
- Enhanced data accessibility and analytical capabilities lead to improved decision-making and inter-institutional collaboration.