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Autonomic care platform for optimizing query performance.

Kristof Steurbaut, Steven Latré1, Johan Decruyenaere

  • 1Department of Mathematics and Computer Science, University of Antwerp - iMinds, Middelheimlaan 1, 2020 Antwerp, Belgium. steven.latre@uantwerpen.be.

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Summary

Automated control loops improve data retrieval performance in intensive care units by reducing query execution times. This enhances timely patient data visualization for healthcare professionals.

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Area of Science:

  • Health Informatics
  • Database Systems
  • Autonomic Computing

Background:

  • Increasing data in electronic health records complicates operations and slows data retrieval in Intensive Care Units (ICUs).
  • Manual query optimization is challenging due to high query volumes, necessitating automated solutions for database performance.
  • Autonomic computing offers self-managing systems, but its application in health information systems is unexplored.

Purpose of the Study:

  • To enhance the COSARA (Care Observation, Surveillance, and Antibiotic Resistance Analysis) architecture with self-managed components.
  • To improve data retrieval performance and reduce query execution times in an ICU setting.
  • To investigate the impact of autonomic control loops on microbiology query performance for patient data visualization.

Main Methods:

  • Extended the COSARA architecture with autonomic control loops (reactive, deliberative, reflective).
  • Analyzed real-life ICU COSARA queries, processing over 2 million daily queries.
  • Focused on optimizing microbiology queries critical for bedside patient data displays.

Main Results:

  • Autonomic control loops significantly optimize data execution in ICUs.
  • Reactive control loop reduced average execution time by 8.61%.
  • Combined reactive and deliberative loops reduced time by 10.92%; all three loops reduced it by 13.04%.

Conclusions:

  • Controlled reduction of query executions improves end-user performance.
  • Implementing autonomic control loops in the COSARA platform positively impacts timely data visualization.
  • This approach enhances decision-making for physicians and nurses by ensuring up-to-date patient information.