AI+ Nurse Practitioner™

Course code: NPAP1102

Formerly known as AI+ Nurse™

Blending Human Touch with AI Intelligence

  • Patient-Focused AI Integration: Tailored for nursing professionals to utilize AI for improved patient care results
  • Evidence-Based Choices: Delivers actionable knowledge for strategic clinical and administrative decision-making
  • Complete AI Proficiency: Spans AI essentials through practical healthcare implementations
  • Healthcare Excellence Through AI: Enables nurses to seamlessly incorporate AI into routine patient care activities

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date
Place
Type Course
duration
Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

AI Fundamentals for Nursing

Gain essential knowledge of artificial intelligence technologies and their application in nursing practice.

Enhancing Patient Care with AI

Learn how AI can optimize workflows and improve decision-making to enhance patient care.

Data Analytics and Machine Learning

Understand the role of data analytics and machine learning in clinical settings to drive better outcomes.

Ethical Considerations in AI

Explore ethical challenges and considerations when leveraging AI tools in nursing to ensure responsible use and patient well-being.

Course structure

Module 1: AI for Nurses

  • 1.1 Understanding AI Basics in a Nursing Context
  • 1.2 Where AI Shows Up in Nursing
  • 1.3 AI Risks Nurses Must Recognize
  • 1.4 AI as a Nursing Support Tool

Module 2: AI for Documentation, Workflow, and Data Literacy

  • 2.1 AI in Nursing Documentation
  • 2.2 Workflow Automation in Nursing Practice
  • 2.3 Beginner’s Guide to Data Literacy in Nursing
  • 2.4 Data Integrity and Documentation Safety
  • 2.5 Communication and Translation Support
  • 2.6 Real-World Case Studies: Documentation AI in Practice

Module 3: Predictive AI and Patient Safety

  • 3.1 Understanding Predictive AI in Healthcare
  • 3.2 Evaluating Alerts and Model Performance
  • 3.3 Human-in-the-Loop Clinical Decision-Making
  • 3.4 Interdisciplinary Response and Handoff Support
  • 3.5 Bias and Equity in Predictive Models
  • 3.6 Real-World Case Studies: Predictive AI in Practice
  • 3.7 Hands-on Activity: Interpreting Predictive Alerts with ChatGPT

Module 4: Generative AI and Nursing Education

  • 4.1 Introduction to Generative AI in Nursing
  • 4.2 Safe Use of Generative AI
  • 4.3 Patient Education and Communication Materials
  • 4.4 Multilingual and Accessible Communication
  • 4.5 Clinical Use Boundaries for Generative AI
  • 4.6 Real-World Case Studies: Generative AI in Practice

Module 5: Ethics, Safety, and Advocacy in AI Integration

  • 5.1 Bias, Fairness, and Inclusion
  • 5.2 Informed Consent and Transparency
  • 5.3 Privacy, Security, and Confidentiality
  • 5.4 Regulatory Literacy for Nurses
  • 5.5 Professional Responsibility and Accountability

Module 6: Evaluating and Selecting AI Tools

  • 6.1 Understanding Performance Metrics
  • 6.2 Predictive Tools vs. Generative Tools
  • 6.3 Vendor Red Flags
  • 6.4 The Nurse Practitioner’s Role in Tool Selection

Module 7: Implementing AI and Leading Change on the Unit

  • 7.1 Building Buy-In
  • 7.2 Change Management Essentials
  • 7.3 Creating an AI Playbook: A Comprehensive Roadmap for Sustainable Success
  • 7.4 Monitoring Quality Improvement
  • 7.5 Error Reporting and Safety Protocols
  • 7.6 Real-World Case Studies in AI Implementation and Change Leadership

Module 8: Capstone Project: Designing a Personal AI in Nursing Impact Plan

  • 1. Capstone Project – Designing a Personal AI-in-Nursing Impact Plan

Optional Module: AI Agents for AI+ Nurses

  • 1. What Are AI Agents?
  • 2. How Does an AI Agent Work in Healthcare?
  • 3. Core Characteristics of AI Agents
  • 4. Importance of AI Agents (General + Nursing)
  • 5. Significance of AI Agents in Nursing
  • 6. Types of AI Agents?
  • 7. Applications and Trends in Nursing
  • 8. Case Study – AI Agents for Nursing Workflow & Sepsis
  • 9. Hands-On Lab

Prerequisites

  • Nursing Essentials: Grasp of clinical procedures and patient management principles
  • Health Tech Experience: Exposure to EHR systems and clinical equipment.
  • Data Analysis Basics: Comprehension of data evaluation and interpretation within medical contexts
  • AI/ML Basics: Awareness of core algorithms and forecasting models.
  • Analytical Decision-Making: Competence in executing data-informed healthcare choices

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