Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Guidelines and Strategies for Safe Computer Charting01:18

Guidelines and Strategies for Safe Computer Charting

817
The guidelines and strategies provided by the American Nurses Association (ANA) and the Canadian Nurses Association (CNA) offer essential principles for ensuring safe and secure computer charting systems in healthcare settings. Let's break down each recommendation:
Maintain Confidentiality and Security:
817
Nursing Clinical Information System01:27

Nursing Clinical Information System

792
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
792
SBAR II: Application of SBAR01:14

SBAR II: Application of SBAR

4.5K
SBAR is an effective communication tool used by healthcare professionals to communicate patient information accurately. SBAR stands for Situation, Background, Assessment, and Recommendation. For a better understanding, an example is given below.
SBAR Report from a Nurse to a Health Care Provider
S: "Hello, Dr. Smith. This is Jane, RN, from the Med Surg unit. I am calling to tell you about Ms. White in Room 210, who is experiencing increased pain and redness at her incision site. Her recent...
4.5K
Integrated Healthcare System01:20

Integrated Healthcare System

1.6K
An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
1.6K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

113
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
113
Design Consideration01:22

Design Consideration

193
Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
193

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Differential Diagnoses in a Patient With Palpitations and Global Electrocardiographic Changes.

American journal of critical care : an official publication, American Association of Critical-Care Nurses·2026
Same author

Trustworthy artificial intelligence in predictive medicine: cancer survival analysis using ethical-by-design and explainable artificial intelligence models.

JAMIA open·2026
Same author

Detecting and Mitigating Bias for Inclusive and Trustworthy Clinical Research: A Scientific Statement From the American Heart Association.

Circulation. Genomic and precision medicine·2026
Same author

Cardiovascular and Autonomic Phenotypes Reveal Distinct Mechanisms of Sepsis Decompensation via Deep Learning.

Research square·2026
Same author

A comprehensive cross-sectional study of bedside monitor alarm characteristics and alarm load across hospital units.

Scientific reports·2026
Same author

Diagnostic Utility of an Intra-Atrial Electrocardiography Lead After Cardiac Surgery.

American journal of critical care : an official publication, American Association of Critical-Care Nurses·2026

Related Experiment Video

Updated: Jul 15, 2025

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies
07:12

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

Published on: November 19, 2020

2.2K

Engaging Multidisciplinary Clinical Users in the Design of an Artificial Intelligence-Powered Graphical User

Stephanie Helman1, Martha Ann Terry2, Tiffany Pellathy3

  • 1Department of Acute and Tertiary Care Nursing, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.

Applied Clinical Informatics
|October 4, 2023
PubMed
Summary

Artificial intelligence (AI) clinical decision support requires user-centered design for optimal bedside care. Multidisciplinary input is crucial for developing transparent, interpretable AI graphical user interfaces (GUIs) that support, not replace, clinical judgment.

More Related Videos

Improving IV Insulin Administration in a Community Hospital
12:08

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

18.9K
Author Spotlight: Introducing the Tile/SED/Array Interface for Rapid Field of View Positioning in Tissue Imaging
06:15

Author Spotlight: Introducing the Tile/SED/Array Interface for Rapid Field of View Positioning in Tissue Imaging

Published on: September 15, 2023

488

Related Experiment Videos

Last Updated: Jul 15, 2025

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies
07:12

Real-Time Monitoring of Neurocritical Patients with Diffuse Optical Spectroscopies

Published on: November 19, 2020

2.2K
Improving IV Insulin Administration in a Community Hospital
12:08

Improving IV Insulin Administration in a Community Hospital

Published on: June 11, 2012

18.9K
Author Spotlight: Introducing the Tile/SED/Array Interface for Rapid Field of View Positioning in Tissue Imaging
06:15

Author Spotlight: Introducing the Tile/SED/Array Interface for Rapid Field of View Positioning in Tissue Imaging

Published on: September 15, 2023

488

Area of Science:

  • Clinical Informatics
  • Artificial Intelligence in Healthcare
  • Human-Computer Interaction

Background:

  • Artificial intelligence (AI) can enhance critical instability forecasting and treatment through clinical decision support.
  • User-facing displays of AI output must facilitate clinical thinking and workflow for all bedside care disciplines.

Purpose of the Study:

  • To engage multidisciplinary users, including physicians, nurse practitioners, and physician assistants, in developing a graphical user interface (GUI).
  • To optimize the presentation of AI-derived risk scores within a user-friendly GUI.

Main Methods:

  • Focus groups with 23 intensive care unit (ICU) clinicians (nurses and medical providers) were conducted in two rounds.
  • Input on a prototype AI risk score GUI was gathered, with design changes implemented between rounds.
  • Transcripts were coded to identify emerging themes regarding GUI design and usability.

Main Results:

  • Six key themes emerged: analytics transparency, graphical interpretability, impact on practice, trend synthesis, decisional weight, and display location.
  • Nurses prioritized objective information and GUI location, while providers focused on interpretability and avoiding impairment of trainee critical thinking.
  • All clinicians valued synthesized data but expressed skepticism about AI decisional weight until trustworthiness is established.

Conclusions:

  • Multidisciplinary user input is essential for designing effective AI-derived GUIs in healthcare.
  • AI decision support systems must be transparent, interpretable, minimally disruptive, and serve as an adjunct to human decision-making.