Evaluation of Nosocomial Infection Management Efficiency Based on the Data Envelopment Analysis Model

Area of Science:

• Healthcare Management
• Hospital Administration
• Infection Control

Background:

• Assessing the relative efficiency of infection control is crucial for hospital performance evaluation.
• Data Envelopment Analysis (DEA) provides a robust framework for evaluating efficiency in healthcare settings.

Purpose of the Study:

• To assess the relative efficiency of infection control practices across different clinical departments.
• To identify areas for improvement in infection prevention and control using performance evaluation.

Main Methods:

• Employed Data Envelopment Analysis (DEA) with five input and two output indicators for infection control.
• Utilized the Banker-Charnes-Cooper (BCC) model to evaluate pure technical efficiency.
• Selected all hospital wards and departments from January to December 2022 as decision-making units (DMUs).

Main Results:

• Significant variation observed in input-output indexes among 27 clinical departments.
• Average technical, pure technical, scale, and comprehensive efficiencies were high (0.987, 0.995, 0.992, 0.980).
• 44% of departments were highly efficient (DEA efficient), while 56% required improvement.

Conclusions:

• The BCC model identified specific areas for improving input-output indexes in non-DEA effective departments.
• Optimizing resource allocation and refining control measures can enhance inventory control and overall infection prevention efficiency.