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). SIMONs 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.
| Identifer | oai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-04022006-161638 |
| Date | 14 April 2006 |
| Creators | Norris, Patrick Roger |
| Contributors | Benoit M. Dawant, John A. Morris, Jr., Paul H. King, Richard G. Shiavi, Robert J. Roselli |
| Publisher | VANDERBILT |
| Source Sets | Vanderbilt University Theses |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.vanderbilt.edu/available/etd-04022006-161638/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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