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CC BY-NC-ND 4.0 · Appl Clin Inform 2022; 13(05): 1207-1213
DOI: 10.1055/s-0042-1758735
Research Article

Information and Data Visualization Needs among Direct Care Nurses in the Intensive Care Unit

Authors

  • Heidi L. Lindroth

    1   Department of Nursing, Mayo Clinic, Rochester, Minnesota, United States
    2   Center for Aging Research, Regenstrief Institute, School of Medicine, Indiana University, Indianapolis, Indiana, United States

  • Yuliya Pinevich

    3   Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, United States
    4   Department of Anesthesiology and Intensive Care for Cardiac Surgery, Republican Clinical Medical Center, Belarus

  • Amelia K. Barwise

    5   Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States

  • Sawsan Fathma

    3   Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, United States

  • Daniel Diedrich

    3   Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, United States

  • Brian W. Pickering

    3   Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, United States

  • Vitaly Herasevich

    3   Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, United States

Funding None.
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Abstract

Objectives Intensive care unit (ICU) direct care nurses spend 22% of their shift completing tasks within the electronic health record (EHR). Miscommunications and inefficiencies occur, particularly during patient hand-off, placing patient safety at risk. Redesigning how direct care nurses visualize and interact with patient information during hand-off is one opportunity to improve EHR use. A web-based survey was deployed to better understand the information and visualization needs at patient hand-off to inform redesign.

Methods A multicenter anonymous web-based survey of direct care ICU nurses was conducted (9–12/2021). Semi-structured interviews with stakeholders informed survey development. The primary outcome was identifying primary EHR data needs at patient hand-off for inclusion in future EHR visualization and interface development. Secondary outcomes included current use of the EHR at patient hand-off, EHR satisfaction, and visualization preferences. Frequencies, means, and medians were calculated for each data item then ranked in descending order to generate proportional quarters using SAS v9.4.

Results In total, 107 direct care ICU nurses completed the survey. The majority (46%, n = 49/107) use the EHR at patient hand-off to verify exchanged verbal information. Sixty-four percent (n = 68/107) indicated that current EHR visualization was insufficient. At the start of an ICU shift, primary EHR data needs included hemodynamics (mean 4.89 ± 0.37, 98%, n = 105), continuous IV medications (4.55 ± 0.73, 93%, n = 99), laboratory results (4.60 ± 0.56, 96%, n = 103), mechanical circulatory support devices (4.62 ± 0.72, 90%, n = 97), code status (4.40 ± 0.85, 59%, n = 108), and ventilation status (4.35 + 0.79, 51%, n = 108). Secondary outcomes included mean EHR satisfaction of 65 (0–100 scale, standard deviation = ± 21) and preferred future EHR user-interfaces to be organized by organ system (53%, n = 57/107) and visualized by tasks/schedule (61%, n = 65/107).

Conclusion We identified information and visualization needs of direct care ICU nurses. The study findings could serve as a baseline toward redesigning an EHR interface.

Keywords

data visualization - intensive care unit - nurse - electronic health record

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by the Mayo Clinic Institutional Review Board.


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Publikationsverlauf

Eingereicht: 13. Juli 2022

Angenommen: 30. September 2022

Artikel online veröffentlicht:
28. Dezember 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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