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A Detailed Protocol for Physiological Parameters Acquisition and Analysis in Neurosurgical Critical Patients
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Process Mining-Supported Emergency Room Process Performance Indicators.

Minsu Cho1, Minseok Song2, Junhyun Park2

  • 1Research Institute of Industry & SME Strategy, Korea Institute of Industrial Technology, Seoul 06211, Korea.

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|September 3, 2020
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Summary
This summary is machine-generated.

This study introduces a framework with key performance indicators for analyzing emergency room processes. It helps measure emergency department performance using clinical data, improving care quality.

Keywords:
emergency roomhealthcareperformance measurementsprocess miningprocess performance indicators

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Area of Science:

  • Healthcare Management
  • Process Analysis
  • Clinical Informatics

Background:

  • Emergency room (ER) processes face unpredictable challenges impacting patient care quality.
  • Effective process management requires robust performance measurement systems.

Purpose of the Study:

  • To propose a novel framework for developing process performance indicators (PPIs) specifically for emergency departments.
  • To enhance the analysis of ER operational efficiency and patient care quality.

Main Methods:

  • Developed a framework for ER PPIs based on the 'devil's quadrangle' (time, cost, quality, flexibility).
  • Identified and validated PPIs through expert consultation with emergency department clinicians.
  • Utilized clinical event logs for data analysis.

Main Results:

  • A set of actionable PPIs for emergency room processes was proposed.
  • The framework successfully applied PPIs using real-world clinical data from a Korean tertiary hospital.
  • The case study confirmed the framework's ability to analyze ER performance.

Conclusions:

  • The proposed framework provides a structured approach to measuring and understanding emergency room performance.
  • The developed PPIs are practical and can be implemented using existing clinical data.
  • This work contributes to improving the quality of care in emergency departments through data-driven insights.