Model-based data integration in clinical environments
As a result of improved hospital information-technology infrastructure and declining costs of storage media, vast amounts of physiological waveform and trend data can now be continuously collected and archived from bedside monitors in operating rooms, intensive care units, or even regular hospital r...
Main Authors: | , |
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Other Authors: | , , , |
Format: | Article |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers (IEEE),
2012-02-03T18:50:02Z.
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Subjects: | |
Online Access: | Get fulltext |
Summary: | As a result of improved hospital information-technology infrastructure and declining costs of storage media, vast amounts of physiological waveform and trend data can now be continuously collected and archived from bedside monitors in operating rooms, intensive care units, or even regular hospital rooms. The real-time or off-line processing of such volumes of high-resolution data, in attempts to turn raw data into clinically actionable information, poses significant challenges. However, it also presents researchers - and eventually clinicians - with unprecedented opportunities to move beyond the traditional individual-channel analysis of waveform data, and towards an integrative patient-monitoring framework, with likely improvements in patient care and safety. We outline some of the challenges and opportunities, and propose strategies for model-based integration of physiological data to improve patient monitoring. National Institute of Biomedical Imaging and Bioengineering (U.S.) (grant R01 EB001659) |
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