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Title page for ETD etd-04022006-161638


Type of Document Dissertation
Author Norris, Patrick Roger
URN etd-04022006-161638
Title Toward New Vital Signs: Tools and Methods for Dense Physiologic Data Capture, Analysis, and Decision Support in Critical Care
Degree PhD
Department Biomedical Engineering
Advisory Committee
Advisor Name Title
Benoit M. Dawant Committee Chair
John A. Morris, Jr. Committee Member
Paul H. King Committee Member
Richard G. Shiavi Committee Member
Robert J. Roselli Committee Member
Keywords
  • heart rate variability
  • patient monitoring
  • critical care
  • trauma
  • medical informatics
  • Vital signs -- Measurement
  • Decision support systems
Date of Defense 2006-03-30
Availability unrestricted
Abstract
Fundamental clinical approaches for assessing patient vital signs have changed little since the first invasive blood pressure measurements were made over 100 years ago. Interpreting patient physiology remains largely a manual, intermittent process, despite evidence suggesting that automated processing of continuously-captured physiologic data will yield new, important measurements. These “new vital signs” may predict patient improvement or deterioration, and signal specific opportunities for early therapeutic intervention in clinically meaningful, cost-effective ways. However, tools and methods to discover, refine, and validate new vital signs in working clinical settings, across large patient populations, have been lacking.

This work describes the SIMON (Signal Interpretation and Monitoring) system, and its application to the discovery, refinement, and validation of a prototype new vital sign, integer heart rate variability (HRV). SIMON’s modular architecture enables a high degree of reliability and scalability for dense physiologic data capture, processing, and decision support tasks. The system has been in use continuously since 1998 in the Vanderbilt trauma intensive care unit (ICU), provides physiologic data reporting, display, and alerting capabilities, and has archived physiologic data from over 3500 patients. Its alphanumeric pager alerting functionality has been evaluated in the domain of intracranial pressure management. Additionally, a new measurement of HRV has been developed, refined, and validated in a population of over 1000 trauma patients. The result is not only a new predictor of mortality but also represents proof of concept that a working intensive care unit can serve as a rich, “automatic” source of data to discover new predictive patterns in patient physiology.

Ultimately, study of HRV and other new vital signs may correlate failure of the autonomic nervous system or other neural and hormonal communication pathways with specific injuries, diseases, or patient characteristics. These studies could, in turn, illuminate regulatory mechanisms uniting systems, organs, cells, proteins, and genes. Such knowledge provides a basis for additional research, and informs design of the next generation of ICU monitors and decision support tools to improve quality and efficiency of medical care.

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