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Nursing Clinical Information System (NCIS)
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Related Experiment Video

Updated: Aug 29, 2025

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
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End-user evaluation of an interface for clinical decision support using predictive algorithms.

Iain E Kehoe, Jeremy A Pepino, Jarone Lee

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |September 10, 2022
    PubMed
    Summary

    Nurses found a new clinical decision support system (CDSS) potentially useful for hemodynamic monitoring in the ICU. However, user perceptions varied, highlighting challenges in integrating advanced algorithms into clinical workflows.

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    Area of Science:

    • Medical Informatics
    • Critical Care Medicine
    • Human-Computer Interaction

    Background:

    • Advanced computational algorithms for clinical decision support systems (CDSS) show promise but face implementation barriers.
    • A user-friendly interface integrated into clinical workflows is crucial for CDSS adoption.
    • Non-intuitive displays can confuse users and potentially lead to patient management errors.

    Purpose of the Study:

    • To evaluate user perceptions of a novel graphical user interface (GUI) designed to integrate a predictive hemodynamic model into intensive care unit (ICU) nursing workflows.
    • To assess the perceived safety and usefulness of the CDSS by end-users (nurses).

    Main Methods:

    • A GUI integrating a predictive hemodynamic model was installed in an ICU patient room.
    • Nurses reviewed video recordings of the software in use and completed surveys on usability, safety, and usefulness.
    • Data were collected from nine patients over a minimum of 4 hours per session.

    Main Results:

    • Nurses generally expressed enthusiasm for the software's potential usefulness and perceived no serious safety concerns.
    • Significant diversity in opinions regarding specific useful and confusing aspects of the GUI was observed.
    • Identical GUI elements were perceived as both most useful and most confusing by different nurses.

    Conclusions:

    • Novel CDSS GUIs can be developed to be perceived as useful and safe for critical care settings.
    • End-user experience and workflow integration are critical factors for the successful adoption of advanced computational algorithms in CDSS.
    • Diverse user perceptions underscore the complexity of implementing new decision support technologies in clinical practice.