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Duke University

AI in Nursing Practice: Foundations for Quality and Safety

Duke University via Coursera Specialization

Overview

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AI is already part of nursing practice. Risk scores, deterioration alerts, prioritized patient lists, and AI‑assisted documentation tools shape what information reaches nurses every shift often without clear explanation or preparation. This Specialization helps nurses understand what these tools are, how they work, and how to use them responsibly in patient care. Across three courses, you'll move from recognition to evaluation to application. You'll learn how AI systems are structured, how AI learns from data, where AI can fall short, and how bias enters tools in predictable ways. You'll practice applying that understanding through guided case studies drawn from realistic clinical scenarios in acute care, outpatient, and telehealth settings, and through AI-enabled discussion activities that ask you to bring a tool from your own workflow into the learning. In support of improving patient care, Duke University Health System Clinical Education and Professional Development is accredited by the American Nurses Credentialing Center (ANCC), the Accreditation Council for Pharmacy Education (ACPE), and the Accreditation Council for Continuing Medical Education (ACCME), to provide continuing education for the health care team. Upon completing the entire Specialization and passing the final assessment, Duke University Health System Department of Clinical Education and Professional Development designates this activity for up to 9 credit hours for nurses.

Syllabus

  • Course 1: Seeing AI in Nursing Practice
  • Course 2: Evaluating AI in Nursing Practice
  • Course 3: Applying AI in Nursing Practice

Taught by

Elaine Kauschinger, Kais Gadhoumi, and Michael Cary

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