AI for Clinical Care

Artificial intelligence is rapidly transforming healthcare delivery, creating new opportunities to enhance patient communication, clinical decision-making and care team effectiveness. The AI for Clinical Care program prepares healthcare professionals to responsibly integrate AI-enabled tools into patient-facing clinical environments while maintaining the human-centered approach that remains essential to quality care.

Developed by Quinnipiac University in partnership with VRSim and leading Connecticut healthcare organizations, this hands-on program combines applied learning with simulation-based practice to help participants build confidence using AI technologies in real-world clinical scenarios. Participants will leave with practical strategies for leveraging AI to support clinical excellence, improve patient interactions, and enhance workforce effectiveness in an increasingly technology-enabled care environment. No prior technical background is required. 

You should attend this program if:

• You work in a patient-facing clinical care role

• You want to develop practical skills using AI tools in healthcare environments

• You are interested in improving communication, coaching, and patient engagement strategies

• You want to understand the ethical, regulatory, and operational considerations associated with AI in healthcare

• You are preparing for the growing integration of AI technologies across care delivery systems 

This program is designed to give learners the knowledge and skills to communicate effectively with diverse patient groups by establishing best practices for AI-enhanced healthcare communications and leveraging AI-enabled coaching and feedback for continuous improvement.

• Execute Effective Prompting 

• Critically Evaluate AI Output in a Clinical Context

• Interpret AI Performance Analytics and Data-driven Feedback 

• Manage Ethical Challenges in Automated Care

• Transfer AI Literacy to the Workplace

• Model Adaptive Learning in Technology

This program is delivered online through a mix of synchronous, instructor-led sessions and asynchronous AI-based coaching and feedback activities.

Spring 2027 (7 weeks)

• February 19-April 9, 2027

  • Online, synchronous sessions held on Fridays from 10-11 a.m. ET

Register to Attend