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Association Between Nurse Copatient Illness Severity and Mortality in the ICU.
Crit Care Med
February 2024
Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Objectives: In the context of traditional nurse-to-patient ratios, ICU patients are typically paired with one or more copatients, creating interdependencies that may affect clinical outcomes. We aimed to examine the effect of copatient illness severity on ICU mortality.
Design: We conducted a retrospective cohort study using electronic health records from a multihospital health system from 2018 to 2020.
The Use of Electronic Health Record Metadata to Identify Nurse-Patient Assignments in the Intensive Care Unit: Algorithm Development and Validation.
JMIR Med Inform
November 2022
Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.
Background: Nursing care is a critical determinant of patient outcomes in the intensive care unit (ICU). Most studies of nursing care have focused on nursing characteristics aggregated across the ICU (eg, unit-wide nurse-to-patient ratios, education, and working environment). In contrast, relatively little work has focused on the influence of individual nurses and their characteristics on patient outcomes.
View Article and Find Full Text PDFBackground: Operational failures, defined as the inability of the work system to reliably provide information, services, and supplies needed when, where, and to who, are a pervasive problem in U.S. hospitals that disrupt nurses' ability to provide safe and effective care.
View Article and Find Full Text PDFCharacterizing intensive care unit rounding teams using meta-data from the electronic health record.
J Crit Care
December 2022
CRISMA Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Purpose: Teamwork is an important determinant of outcomes in the intensive care unit (ICU), yet the nature of individual ICU teams remains poorly understood. We examined whether meta-data in the form of digital signatures in the electronic health record (EHR) could be used to identify and characterize ICU teams.
Methods: We analyzed EHR data from 27 ICUs over one year.
A response to a correspondence letter by Buckleton et al. on: Riman et al. (2021) Examining performance and likelihood ratios for two likelihood ratio systems using the PROVEDIt dataset, PLoS One 16(9):e0256714.
Forensic Sci Int Genet
July 2022
National Institute of Standards and Technology, Applied Genetics Group, Gaithersburg, MD 20899, USA.
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