ArticleLearning health systems2026
AI-powered nursing handoffs: Introducing and evaluating the patient report template.
Article in Learning health systems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Catching the Wave: AI In Health Services Research.Learning health systems · 2026Article
- Reframing Person-Centered Fundamental Care in the Age of Artificial Intelligence, Robotics and Posthumanization: A Theory-Informed Narrative Review.Journal of multidisciplinary healthcare · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To understand (1) if nurses view the individual components of the Patient Report Template as useful in their day-to-day workflow, and (2) understand the perceptions of nurses related to artificial intelligence use in their day-to-day work. Materials and Methods: A survey was distributed to 2118 nurses at the University of Iowa Health Care System in order to gather feedback over each component of the patient report template and to assess perceptions about artificial intelligence in their work; 108 nurses elected to participate in the study and share their opinions. Results: The study found that (1) nurses have reservations about the accuracy and trustworthiness of artificial intelligence in their work, but believe that it will provide utility to them, and (2) most components of the Patient Report Template, with exceptions, received favorable ratings in terms of their perceived usefulness in nurses' work. Conclusion: While nurses believe that artificial intelligence will bring utility to their work, they feel that these systems have the potential for inaccuracy and may not be trustworthy. This highlights a need for education, transparency, and support when artificial intelligence systems are implemented. Highly rated sections of the Patient Report Template like Patient Profile, Actions, and Safety suggest that these components could be beneficial to nurses, aiding the accuracy and completeness of nursing handoffs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.