UCLA Health nursing AI program reduces clinician burnout and streamlines documentation across inpatient and ambulatory care

Nurses at UCLA Health faced heavy cognitive and administrative burdens, including managing documentation, shift handoffs, and patient queries across multiple simultaneous patients. The volume of charting and care coordination tasks contributed to clinician burnout and reduced time available for direct patient care.

UCLA Health Nursing, led by Nursing Informatics, deployed a Care Coordination tool to identify high-risk patients for prioritization and a generative AI tool to draft responses to patients' medical advice queries. Additional tools under development include AI-generated Insight Summaries, End of Shift Reports, Care Transition Handoffs, and a Nursing Knowledge-Base search tool integrating digital reference libraries. All tools were validated through a nurse-led AI Focus Group of ~20 nurses across specialties and reviewed by the UCLA Health AI Council for bias and patient privacy.

Deployed tools are actively in use across ambulatory and inpatient settings. The Insight Summaries tool entered a pilot phase with a select group of nurses providing feedback to Epic. Nurses report reduced cognitive burden and improved access to relevant clinical information, with expectations that tools will meaningfully reduce time spent on documentation and administrative tasks.

• Nurse-led validation is essential: tools that aren't co-developed with frontline staff won't be adopted, regardless of technical quality.
• AI governance structures (bias review, privacy checks, professional committee sign-off) are a prerequisite for responsible deployment at scale.
• The goal is augmenting nursing judgment and reducing administrative load — not replacing the human element of care.