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Nursing Clinical Information System (NCIS)
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Integrating Physiological Data Artifacts Detection With Clinical Decision Support Systems: Observational Study.

Shermeen Nizami1, Carolyn McGregor Am2, James Robert Green1

  • 1Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada.

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|June 22, 2024
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Summary
This summary is machine-generated.

This study introduces a novel framework for artifact detection (AD) algorithms to improve clinical decision support systems (CDSS) by reducing false alarms and alarm fatigue in critical care settings.

Keywords:
alarm fatiguebiomedical data analyticsclinical decision supportpatient monitoringphysiological data artifactssystems architecture

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Area of Science:

  • Biomedical Engineering
  • Clinical Informatics

Background:

  • Clinical decision support systems (CDSS) can improve patient outcomes but are hindered by signal artifacts in physiological data.
  • Artifacts lead to false alarms, causing alarm fatigue, disrupting care, and reducing its quality in critical environments.

Purpose of the Study:

  • To evaluate a new artifact detection (AD) framework designed for real-time integration with CDSS in critical care.
  • To assess the framework's features in a study focused on reducing false alarms.

Main Methods:

  • Developed four static AD components with standardized interfaces for interoperability.
  • Created four AD compositions and integrated them with a clinical event detection component to form dynamic CDSS for SpO2 alarm generation.
  • Collected and analyzed data from 11 neonatal intensive care unit patients.

Main Results:

  • Evaluated 119 SpO2 alarms, achieving a 39% false alarm rate with 80% sensitivity.
  • Demonstrated the framework's effectiveness in identifying optimal dynamic compositions for reducing false SpO2 alarms and alarm fatigue.

Conclusions:

  • Framework features like reusability, standardization, scalability, and customizability enable the evaluation of CDSS formulations.
  • The framework supports real-time clinical implementation of AD by allowing optimal CDSS solutions to be integrated into workflows.