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Data Collection and Analysis in the ICU

  • Jaspreet Kaur Mann
  • Farhad Kaffashi
  • Benjamin Vandendriessche
  • Frank J. Jacono
  • Kenneth LoparoEmail author
Chapter

Abstract

Data in the intensive care unit (ICU) can be broadly categorized as “phenotypic” and “physiologic.” Examples of “phenotypic” data include demographics, age, sex, laboratory values, and physician and nursing notes. Examples of “physiologic” data include common vital signs (blood pressure, heart rate, respiratory rate, core temperature) and other parameters generated from bedside monitoring devices (intracranial pressure, electroencephalogram). Most ICUs offer continuous 24/7 monitoring of these physiologic data (both numeric and waveforms) but lack the capability for data collection, integration, and analysis. The ability to do all of this in real time is virtually impossible. Analytical tools are also typically limited to averages and trends, while recent studies have demonstrated that complex systems analysis may provide greater insight into the dynamics of critical illness. This chapter will review various types of data in the ICU and methods of analysis including complex systems analysis and “patient state” tracking in the ICU.

Keywords

Data Analysis Alarms Waveform Patient state Complex systems 

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Copyright information

© Springer-Verlag GmbH Germany 2020

Authors and Affiliations

  • Jaspreet Kaur Mann
    • 1
  • Farhad Kaffashi
    • 2
  • Benjamin Vandendriessche
    • 3
  • Frank J. Jacono
    • 4
    • 5
  • Kenneth Loparo
    • 6
    • 7
    Email author
  1. 1.Neurology and Neurocritical Care, San FranciscoUSA
  2. 2.Department of Electrical Engineering and Computer ScienceCase Western Reserve UniversityClevelandUSA
  3. 3.BytefliesAntwerpBelgium
  4. 4.Pulmonary, Critical Care, and Sleep Medicine, Department of MedicineCase Western Reserve University School of MedicineClevelandUSA
  5. 5.Division of PulmonaryLouis Stoke VA Medical CenterClevelandUSA
  6. 6.ISSACS: Institute for Smart, Secure and Connected SystemsClevelandUSA
  7. 7.Department of Electrical Engineering and Computer Science, IoT CollaborativeCase Western Reserve UniversityClevelandUSA

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