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Open Access
Peer-reviewed
Research Article
Sensor-based measurement of critical care nursing workload: Unobtrusive measures of nursing activity complement traditional task and patient level indicators of workload to predict perceived exertion
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Michael A. Rosen ,
Roles Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Supervision, Writing – original draft
* E-mail: mrosen44@jhmi.edu
Affiliations Armstrong Institute for Patient Safety and Quality, Baltimore, MD, United States of America, Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America, Bloomberg School of Public Health, Department of Health, Policy, and Management; Johns Hopkins University, Baltimore, MD, United States of America, School of Nursing, The Johns Hopkins University, Baltimore, MD, United States of America
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Aaron S. Dietz,
Roles Conceptualization, Methodology, Writing – original draft, Writing – review & editing
Affiliations Armstrong Institute for Patient Safety and Quality, Baltimore, MD, United States of America, Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
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Nam Lee,
Roles Formal analysis, Methodology, Validation, Writing – review & editing
Affiliation Armstrong Institute for Patient Safety and Quality, Baltimore, MD, United States of America
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I-Jeng Wang,
Roles Conceptualization, Methodology, Writing – review & editing
Affiliation The Johns Hopkins University Applied Physics Laboratory, Baltimore, MD, United States of America
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Jared Markowitz,
Roles Conceptualization, Formal analysis, Methodology, Validation
Affiliation The Johns Hopkins University Applied Physics Laboratory, Baltimore, MD, United States of America
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Rhonda M. Wyskiel,
Roles Conceptualization, Methodology, Writing – review & editing
Affiliations Armstrong Institute for Patient Safety and Quality, Baltimore, MD, United States of America, The Johns Hopkins Health System, Baltimore, MD, United States of America
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Ting Yang,
Roles Formal analysis, Methodology, Writing – review & editing
Affiliation Armstrong Institute for Patient Safety and Quality, Baltimore, MD, United States of America
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Carey E. Priebe,
Roles Methodology, Supervision, Validation, Writing – review & editing
Affiliation Department of Applied Mathematics and Statistics, The Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD, United States of America
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Adam Sapirstein,
Roles Conceptualization, Validation, Writing – review & editing
Affiliations Armstrong Institute for Patient Safety and Quality, Baltimore, MD, United States of America, Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
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Ayse P. Gurses,
Roles Conceptualization, Methodology, Writing – review & editing
Affiliations Armstrong Institute for Patient Safety and Quality, Baltimore, MD, United States of America, Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America, Bloomberg School of Public Health, Department of Health, Policy, and Management; Johns Hopkins University, Baltimore, MD, United States of America, Malone Center for Engineering in Healthcare, The Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD, United States of America
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Peter J. Pronovost
Roles Conceptualization, Funding acquisition, Resources, Supervision, Writing – review & editing
Affiliations Armstrong Institute for Patient Safety and Quality, Baltimore, MD, United States of America, Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America, Bloomberg School of Public Health, Department of Health, Policy, and Management; Johns Hopkins University, Baltimore, MD, United States of America, School of Nursing, The Johns Hopkins University, Baltimore, MD, United States of America, The Johns Hopkins Health System, Baltimore, MD, United States of America
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Sensor-based measurement of critical care nursing workload: Unobtrusive measures of nursing activity complement traditional task and patient level indicators of workload to predict perceived exertion
- Michael A. Rosen,
- Aaron S. Dietz,
- Nam Lee,
- I-Jeng Wang,
- Jared Markowitz,
- Rhonda M. Wyskiel,
- Ting Yang,
- Carey E. Priebe,
- Adam Sapirstein,
- Ayse P. Gurses
- Published: October 12, 2018
- https://doi.org/10.1371/journal.pone.0204819