Digital Innovations Improving Nursing Practice Through Artificial Intelligence: The State of the Science

Despite significant concerns about the broad use of artificial intelligence (AI) in clinical practice, registered nurses are commonly challenged to adopt, evaluate, and improve these digital solutions in almost any care environment. The aim of this study is to appraise, then analyze, the scientific literature for contemporary digital innovations that improve nursing practice through the use of AI. This scoping review with thematic analysis of digital innovations impacting nursing practice was conducted using CINAHL and PubMed databases (2022-2024). We describe the use of large language models and associated software tools in supporting this work, highlighting the essential human-in-the-loop activities involved. Results: This review highlights emerging themes, notably improved patient safety and greater trust and acceptance. A persistent emphasis on AI as an assistive entity was found across many products, processes and pilots identified in our corpus. This body of literature is rapidly evolving and characterized by multiple competing themes. The proper implementation and execution of AI as an assistive mechanism is crucial for safety enhancement, improved quality, and trust. Recommendations include the provision of transparency in all aspects of AI innovations for practice (from inception to evaluation) and participatory implementation activities.

Authors

Institutions

Publication Details

Journal
Nursing Administration Quarterly
Published
2025-12-17
DOI
https://doi.org/10.1097/naq.0000000000000721
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Digital Innovations Improving Nursing Practice Through Artificial Intelligence: The State of the Science

Hannah Jang Kim, Mary Anne Schultz, Fang-yu Chou, Evangeline Fangonil-Gagalang et al.
Nursing Administration Quarterly
Artificial Intelligence in Healthcare and Education
article

Digital Innovations Improving Nursing Practice Through Artificial Intelligence: The State of the Science

Hannah Jang Kim, Mary Anne Schultz, Fang-yu Chou, Evangeline Fangonil-Gagalang, Sarah L. Flores
article en

Abstract

Despite significant concerns about the broad use of artificial intelligence (AI) in clinical practice, registered nurses are commonly challenged to adopt, evaluate, and improve these digital solutions in almost any care environment. The aim of this study is to appraise, then analyze, the scientific literature for contemporary digital innovations that improve nursing practice through the use of AI. This scoping review with thematic analysis of digital innovations impacting nursing practice was conducted using CINAHL and PubMed databases (2022-2024). We describe the use of large language models and associated software tools in supporting this work, highlighting the essential human-in-the-loop activities involved. Results: This review highlights emerging themes, notably improved patient safety and greater trust and acceptance. A persistent emphasis on AI as an assistive entity was found across many products, processes and pilots identified in our corpus. This body of literature is rapidly evolving and characterized by multiple competing themes. The proper implementation and execution of AI as an assistive mechanism is crucial for safety enhancement, improved quality, and trust. Recommendations include the provision of transparency in all aspects of AI innovations for practice (from inception to evaluation) and participatory implementation activities.

Nursing Administration QuarterlyVol. 50(1)
Kaiser Permanente (US), Center for Children (US), California State University, San Bernardino (US), San Francisco State University (US)
Openalex Percentile: Top 41%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Digital Innovations Improving Nursing Practice Through Artificial Intelligence: The State of the Science — Hannah Jang Kim, Mary Anne Schultz, et al. · Nursing Administration Quarterly (2025) | TGRS Research Map | TGRS