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Discrete Heart Rate Values or Continuous Streams? Representation, Variability, and Meaningful Use of Vital Sign Data
Keith Feldman1, Annie J Rohan, Nitesh V Chawla
1Author Affiliations: Department of Computer Science and Engineering and iCeNSA, University of Notre Dame, IN (Drs Feldman and Chawla); SUNY Downstate Health Sciences University, College of Nursing, Brooklyn, NY (Dr Rohan).
Automated patient heart rate monitoring reveals variability differences compared to manual charting. Analyzing these temporal differences can personalize patient care and improve clinical outcome predictions.
Area of Science:
- Biomedical Engineering
- Clinical Informatics
- Physiological Monitoring
Background:
- Manual documentation of patient heart rate is standard practice, despite continuous data from bedside monitors.
- Current charting methods capture only snapshots, leading to discrepancies with real-time streaming data.
- Previous research identified differences between charted vitals and continuous monitoring data.
Purpose of the Study:
- To investigate the temporal properties of differences between manual charting and continuous heart rate monitoring data.
- To explore how these differences in variability manifest and relate to clinical applications.
- To demonstrate the utility of variability metrics for personalized patient care.
Main Methods:
- Analysis of temporal properties of heart rate variability metrics derived from continuous monitoring data.
- Comparison of variability measures between discrete charted data and complete streaming data.
- Association of variability metrics with clinical measures, including severity scores.
Main Results:
- Differences in charting techniques significantly impact measures of heart rate variability.
- Variability metrics demonstrate a relationship with temporal elements of charting timing.
- Personalized care can be facilitated by contextualizing deviations in magnitude using variability metrics.
Conclusions:
- Charting techniques influence the assessment of patient heart rate variability.
- Variability metrics derived from complete monitoring data offer valuable clinical insights.
- This approach can enhance personalized care and improve the association with clinical severity scores.
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