Measuring AI's value for nurses, beyond faster charting

Health systems are testing whether nursing documentation automation improves presence, note quality, wellbeing and retention – not just reducing the minutes required to finish a note. This is Part 1 of a two-part feature. Part 2 will be published tomorrow. Is artificial intelligence documentation for nurses returning meaningful bedside time? Or simply relocating administrative work? That may be the central question when assessing whether AI is worth the investment for nurses. "Where I have seen AI documentation tools make the most meaningful difference is when they are designed around the realities of nursing practice, not simply adapted from another clinician workflow and placed in front of nurses," said Tracy Breece, RN, vice president of nursing informatics AI and emerging technology at Advocate Health, a 69-hospital health system that serves eight states. AI documentation tools give nurses meaningful time back when they shift the nurse's role from primary author to reviewer, added Dedera Tucker, RN, managing director of healthcare informatics at Healthcare IT Leaders, a consulting firm. "That is where the time back becomes meaningful," Breece said. "It is not just fewer clicks or fewer minutes at a keyboard. It is less time trying to remember and recreate care after the fact. It is more ability to stay present with the patient. It is more space for purposeful patient education, family-centered conversations, and the visible and invisible work of nursing that has not always been reflected well in the medical record." AI documentation's expansion into workflows There has been an expansion in the use of AI from physician-focused ambient tools to nursing workflows – where documentation is continuous, interrupted, relational and inseparable from clinical judgment. "The AI tools that work best are the ones that stay in the background and support the nurse rather than asking the nurse to support the tool," said Angel Bozard, RN, chief nursing officer at VirtuAlly, a company that provides 24/7 telehealth care. "Ambient documentation and voice capture during patient encounters can genuinely give time back, especially for routine notes and shift documentation that used to eat into direct care time." The nurse still reviews, validates and owns the final documentation, but the first draft is closer to the actual care encounter – and that matters because it supports both accuracy and presence, Breece explained. But friction persists in the forms of correction and reformatting, partial workflow coverage, awkward verbalization of care, extra review steps, and technology that adds work instead of removing it. "Where I see friction is when nurses have to stop to correct or reformat AI-generated notes more than they would have spent writing them from scratch," Bozard said. "That's not time saved – that's time moved." However, friction occurs when tools address only isolated tasks versus a complete workflow, Tucker added. And Breece said the friction usually comes when the workflow is not designed with nurses, when education focuses only on the tool and not the practice change, or when leaders measure use instead of listening to experience." Scoring the value of AI Hospitals and health systems, thus, need a broader value scorecard. They must move beyond minutes saved to cognitive load, after-shift work, documentation quality, continuity of care, patient experience, workforce wellbeing, and retention. "Minutes saved matter, but they are not enough," Breece advised. "If we only measure time, we miss the larger question: What is the technology improving in the practice environment?" Leaders should track outcomes that reflect real operational and clinical value, Bozard added. "I'd want to see reductions in nurse-reported cognitive load and documentation-related burnout, as well as whether time saved is actually being reinvested at the bedside rather than simply offset by higher patient loads," she said. And does the documentation more accurately reflect the patient story, the nurse's assessment, education provided, family conversations, interventions and clinical judgment? Does it improve continuity of care for the next clinician or the next shift? These are questions Breece wants answered. What is the standard for success? So, there should be a standard for success when it comes to nursing artificial intelligence documentation. "With virtual nursing, we have seen that when nurses get real time back, the impact shows up in retention and in how they describe their job – not just in a productivity dashboard," Bozard noted. The goal should never be productivity alone, Breece said. "The goal is to reduce friction that pulls nurses away from the work only nurses can do: assessing, teaching, advocating, comforting, coordinating and caring," she concluded. Part 2 of this two-part feature will be published tomorrow. More stories like this: Follow Bill's health IT coverage on LinkedIn: Bill Siwicki Email him: [email protected] Healthcare IT News is a HIMSS Media publication. HIMSS is hosting the one-day AI Executive Leadership Summit in San Diego on Oct. 21, 2026, followed by its AI in Healthcare Forum Oct. 22–23. Register separately for the two events here and here.