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ICU Staffing, Models, and Outcomes

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Oncologic Critical Care

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Abstract

As one of the most expensive resources in the healthcare system, the intensive care units (ICUs) are closely monitored for appropriate utilization and adequate staffing. The latter, considered one of the most challenging and controversial is extensively discussed in this chapter. Optimal staffing of an ICU is highly dependent on multiple factors including, but not limited to availability of trained personnel, educational trainees, acuity of patients, size of ICU, and economic constraints. Therefore, staffing models need to be carefully selected and implemented based on the local setting. The key commodity in ICU staffing is the availability of specialty trained personnel, namely the intensivists and ICU nurses. Thus, in order to efficiently staff the ICU, attracting and retaining the intensivists, requires creative models which may focus on time off and lifestyle factors. The benefits of open versus closed units, high-intensity versus low-intensity models, and the classic academic and 24-h models are explored to provide the reader with a clear understanding of the benefits of these complex options and associated outcomes.

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Authors and Affiliations

  1. Department of Critical Care and Respiratory Care, University of Texas MD Anderson, Houston, TX, USA

    Karen Chen & Joseph L. Nates

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  1. Karen Chen
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  2. Joseph L. Nates
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Correspondence to Joseph L. Nates .

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Editors and Affiliations

  1. Department of Critical Care, University of Texas MD Anderson Cancer C Department of Critical Care, Houston, TX, USA

    Joseph L. Nates

  2. Department of Critical Care, University of Texas MD Anderson Cancer C Department of Critical Care, Houston, TX, USA

    Kristen J. Price

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Chen, K., Nates, J.L. (2019). ICU Staffing, Models, and Outcomes. In: Nates, J., Price, K. (eds) Oncologic Critical Care. Springer, Cham. https://doi.org/10.1007/978-3-319-74698-2_2-1

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  • DOI: https://doi.org/10.1007/978-3-319-74698-2_2-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74698-2

  • Online ISBN: 978-3-319-74698-2

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