AI+ Nurse Practitioner™

$195.00
Formerly known as AI+ Nurse™ Blending Human Touch with AI Intelligence
  • Patient-Centric AI Care: Designed for nurses to leverage AI for enhanced patient outcomes
  • Data-Driven Decisions: Provides practical insights for informed clinical and operational choices
  • Comprehensive AI Understanding: Covers AI fundamentals to real-world healthcare applications
  • Clinical Excellence with AI: Empowers nurses to confidently integrate AI into daily healthcare practice
Learning Modules

Module 1: What is AI for Nurses?

  1. 1.1 What is AI for Nurses?
  2. 1.2 Where AI Shows Up in Nursing
  3. 1.3 Case Study: Improving Patient Safety and Nursing Efficiency with AI at Riverside Medical Center
  4. 1.4 Hands-on: Using Nurse AI for Clinical Data Visualization in Postoperative Nursing Care

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

  1. 2.1 Introduction to Natural Language Processing
  2. 2.2 Workflow Automation: Transforming Nursing Practice
  3. 2.3 Beginneru2019s Guide to Data Literacy in Nursing
  4. 2.4 Legal & Compliance Basics in Nursing AI Documentation
  5. 2.5 Case Study: Integrating AI and Workflow Automation at Massachusetts General Hospital (MGH)
  6. 2.6 Hands-On Exercise: Using the ChatGPT Registered Nurse Tool in Clinical Documentation and Patient Education

Module 3: Predictive AI and Patient Safety

  1. 3.1 Understanding Predictive Models
  2. 3.2 Alert Fatigue and Trust
  3. 3.3 Simulation Activity: Responding to Real-Time Deterioration Alerts
  4. 3.4 Collaborating Across Teams
  5. 3.5 Bias in Predictions
  6. 3.6 Case Study
  7. 3.7 Hands-on Activity: Interpreting Predictive Alerts with ChatGPT

Module 4: Generative AI in Nursing

  1. 4.1 Introduction to Generative AI in Nursing
  2. 4.2 Large Language Models (LLMs) for Nurses
  3. 4.3 Creating Patient Education Materials with AI
  4. 4.4 Ensuring Safe and Ethical Use of AI
  5. 4.5 Case Study
  6. 4.6 Hands-On Activity: Exploring AI-Powered Differential Diagnosis with Symptoma

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

  1. 5.1 Bias, Fairness, and Inclusion
  2. 5.2 Informed Consent and Transparency
  3. 5.3 Nurse Advocacy and Professional Responsibilities
  4. 5.4 Creating an Ethics Checklist
  5. 5.5 Stakeholder Feedback Techniques
  6. 5.6 Legal and Regulatory Considerations
  7. 5.7 Psychological and Social Implications
  8. 5.8 Case Study: Addressing Racial Bias in Healthcare Algorithms (Optum Algorithm Case).
  9. 5.9 Hands-on: Uncovering Bias in Diabetes Risk Prediction: A Fairness Audit Using Aequitas

Module 6: Evaluating and Selecting AI Tools

  1. 6.1 Understanding Performance Metrics
  2. 6.2 Vendor Red Flags
  3. 6.3 Nurse Role in Selection
  4. 6.4 Evaluation Templates and Checklists
  5. 6.5 Use Cases: AI in Clinical Decision-Making
  6. 6.6 Case Study: Using AI to Enhance Real-Time Clinical Decision-Making at UAB Medicine with MIC Sickbay
  7. 6.7 Hands-on: Evaluating AI Diagnostic Model Performance Using Confusion Matrix Metrics

Module 7: Implementing AI and Leading Change on the Unit

  1. 7.1 Building Buy-In: Promoting AI as an Ally, Not a Competitor
  2. 7.2 Change Management Essentials
  3. 7.3 Creating an AI Playbook: A Comprehensive Roadmap for Sustainable Success
  4. 7.4 Monitoring Quality Improvement: Leveraging AI Metrics for Continuous Enhancement
  5. 7.5 Error Reporting and Safety Protocols: Ensuring Safe and Reliable AI Integration
  6. 7.6 Hands-On Activity: Calculating Clinical Risk Scores and Visualization with ChatGPT

Module 8: Capstone Project

  1. 1. Capstone Project u2013 Designing a Personal AI-in-Nursing Impact Plan
AI Enabled Coordinated Assurance Certification

Certificate Code:

AP 1102

Duration:

  • Instructor-Led: 1 day (live or virtual)
  • Self-Paced: 8 hours of content

Prerequisites:

Basic nursing knowledge, Familiarity with healthcare technology, Critical thinking, Foundational AI and ML concepts, Problem solving skills

Why This Certification Matters

AI in Patient Care:

Learn how AI enhances patient monitoring, early warning systems, and proactive care delivery.

Clinical Decision Support:

Understand AI tools that assist nurses in medication management, triage, and treatment recommendations.

Workflow Optimization:

Discover how AI reduces administrative burdens and streamlines nursing workflows for efficiency.

Ethical and Human-Centered Care:

Explore responsible AI practices that preserve empathy, trust, and patient-centered values in nursing.

Practical Simulations:

Apply skills in real-world nursing scenarios through interactive, AI-powered case-based learning.
Who Should Enroll

  • Registered Nurses (RNs):u00a0Professionals seeking to integrate AI into daily patient care and clinical decision-making.

  • Nursing Students:u00a0Learners aiming to build future-ready skills in AI-driven healthcare practices.

  • Healthcare Administrators:u00a0Individuals looking to optimize nursing workflows and enhance patient care outcomes.

  • Clinical Informatics Specialists:u00a0Experts interested in applying AI to electronic health records and patient data analysis.

  • Nurse Educators & Trainers:u00a0Professionals preparing the next generation of nurses with AI-powered healthcare knowledge.

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