Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Current Trends in Nursing II

Current Trends in Nursing II

Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...

Nursing Clinical Information System

Nursing Clinical Information System

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:

Documentation of Nursing Diagnosis

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...

Issues And Trends In Healthcare Delivery System

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

Current Trends in Nursing I

Current Trends in Nursing I

Current trends in nursing include:

Ethical Issues

Ethical Issues

Nurses are essential in patient care, upholding the ethical principles of their profession and effectively navigating ethical dilemmas. Neglecting ethical issues can lead to inadequate patient care, compromised therapeutic relationships, and moral distress among healthcare workers.
Ethical Concerns in Healthcare:

You might also read

Related Articles

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

Sort by

Same author

Preparing the nursing workforce for the health AI era: Insights from the Macy Foundation Conference on AI in Medical Education.

Journal of professional nursing : official journal of the American Association of Colleges of Nursing·2026

Same author

Strategies for mitigating artificial intelligence bias in healthcare: a systematic review.

JAMIA open·2026

Same author

The Historical Evolution of Microlearning in Health Professions Education: Bibliometric Analysis.

JMIR medical education·2026

Same author

Collaborative Multidisciplinary Teamwork in the Care of Adolescent and Young Adult Patients with Cancer: A Systematic Review.

Journal of adolescent and young adult oncology·2026

Same author

AI disclosure uncertainty in nursing education: A pedagogical scaffold for professional learning.

Nurse education today·2026

Same author

Generative AI Ethics Toolkit for Clinical Prioritization in Nursing Education.

Nursing ethics·2026

Search research articles

Related Experiment Video

Updated: Mar 15, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Nurses confront artificial intelligence-generated health information at the bedside: A case study.

Samantha Cueto¹, Jennie C De Gagne², Thomas Merrill²

¹Penn Medicine Princeton Medical Center, Plainsboro Township, NJ.

Nursing Outlook

|March 13, 2026

Summary

This summary is machine-generated.

Nurses face challenges when patients misinterpret artificial intelligence (AI) health information. This study proposes nurse-led protocols to manage AI-generated data conflicts, ensuring ethical patient care and promoting AI literacy in nursing.

Keywords:

Artificial intelligence Biomedical ethics Digital technologies Generative oncological nursing Leadership Nursing shared governance

Related Experiment Videos

Last Updated: Mar 15, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Area of Science:

Nursing Informatics
Bioethics
Artificial Intelligence in Healthcare

Background:

Artificial intelligence (AI) tools are transforming patient access to health information.
Conflicting interpretations of AI-generated health data between patients and clinicians create bedside tensions.
Nurses require frameworks to address ethical dilemmas arising from AI in patient care.

Purpose of the Study:

To examine a nurse's experience with a patient misinterpreting AI-generated lab results.
To explore how nurses can uphold bioethical principles (autonomy, beneficence, justice) amidst AI influence.
To propose nurse-led protocols for managing discrepancies between AI data and clinical standards.

Main Methods:

Case study methodology.
Application of theoretical frameworks grounded in bioethical principles.
Development of nurse-led protocols: Patient level (Ask, Balance, Clarify, Document) and Team level (AI Situation, Background, Assessment, Recommendation).

Main Results:

Identified nurse's role as a mediator in AI-influenced patient decision-making.
Highlighted the critical need for AI literacy, transparency, and bias mitigation in nursing.
Demonstrated the potential for structured protocols to guide communication when AI contradicts care standards.

Conclusions:

Nurses play a vital role in navigating AI-related ethical challenges at the bedside.
Proposed protocols can support nurses in managing patient interactions involving AI-generated health information.
Institutional integration of AI ethics into nursing education and practice is essential for future healthcare.