AI+ Nurse™

Target group

Registered Nurses (RNs): Professionals seeking to integrate AI into daily patient care and clinical decision-making.

Nursing Students: Learners aiming to build future-ready skills in AI-driven healthcare practices.

Healthcare Administrators: Individuals looking to optimize nursing workflows and enhance patient care outcomes.

Clinical Informatics Specialists: Experts interested in applying AI to electronic health records and patient data analysis.

Nurse Educators & Trainers: Professionals preparing the next generation of nurses with AI-powered healthcare knowledge.

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

• 8.1 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

Certification

50 questions, 70% passing, 90 minutes, online proctored exam