# Contributions of Artificial Intelligence to Decision Making in Nursing: A Scoping Review

**Authors:** Filipe Fernandes, Lucy Shinners, Mauro Mota, Paulo Santos, Luís Sá

PMC · DOI: 10.1111/nhs.70308 · Nursing & Health Sciences · 2026-02-18

## TL;DR

This review explores how AI supports nursing decisions, highlighting benefits like improved accuracy and challenges like transparency and regulation.

## Contribution

The paper provides a scoping review of AI's role in nursing decision-making, emphasizing the need for ethical and transparent integration.

## Key findings

- AI improves diagnostic accuracy and workflow efficiency in nursing.
- Interpretability and ethical concerns hinder AI adoption in healthcare.
- Critical care units are primary areas for AI application, but integration challenges remain.

## Abstract

Recognizing the complexity of decision‐making is essential in nursing practice, where Artificial Intelligence (AI) can serve as a valuable tool to support nurses in the process of decision‐making. This scoping review aims to map and systematize evidence regarding AI's contributions to nursing decision‐making, following the Joanna Briggs Institute (JBI) methodological approach. Databases consulted: CINAHL Complete; MEDLINE Complete; Nursing & Allied Health Collection: Comprehensive; Cochrane Databases; MedicLatina; SciELO; Scopus; LILACS; JBI Database of Systematic Reviews and RCAAP. Thirteen studies in English, Portuguese, and Spanish were included. AI can support the nursing decision‐making process by improving diagnostic accuracy and workflows. However, interpretability remains a limiting factor that affects the adoption of AI. Although critical healthcare units represent the primary areas of application, meeting the ethical, legal, and technical requirements necessary for effective integration into practice continues to be a challenge. AI offers meaningful contributions to nursing decision‐making, particularly through explainable and clinically aligned systems. However, successful integration demands transparency, ethics, and usability, with further studies to ensure safe adoption.

Artificial Intelligence can leverage decision‐making, enhancing nurses' skills.Nevertheless, the diverse array of risks posed by AI‐driven technologies needs comprehensive regulation.Regulating liability and ensuring equitable access to AI‐driven healthcare solutions are essential for building trust and inclusivity.

Artificial Intelligence can leverage decision‐making, enhancing nurses' skills.

Nevertheless, the diverse array of risks posed by AI‐driven technologies needs comprehensive regulation.

Regulating liability and ensuring equitable access to AI‐driven healthcare solutions are essential for building trust and inclusivity.

## Full-text entities

- **Diseases:** pressure injuries (MESH:D003668), SAPS-III (MESH:C537189), death (MESH:D003643), COVID-19 (MESH:D000086382), Hospital-Acquired Pressure Injuries (MESH:D000077299), heart failure (MESH:D006333), diabetes and kidney disease (MESH:D003928), sepsis (MESH:D018805), infectious diseases (MESH:D003141), Coma (MESH:D003128), cognitive overload (MESH:D003072), IA (MESH:C536041), Parkinson's (MESH:D010300), diabetes (MESH:D003920), mentally disabled (MESH:D001523), Alzheimer's (MESH:D000544), lung cancer (MESH:D008175), cardiac arrhythmia (MESH:D001145), acute respiratory failure (MESH:D012131), AI (MESH:C538142), fatigue (MESH:D005221), XAI (MESH:C538243)
- **Chemicals:** XAI (-), bicarbonate (MESH:D001639), Oxygen (MESH:D010100), bilirubin (MESH:D001663)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12917350/full.md

## References

58 references — full list in the complete paper: https://tomesphere.com/paper/PMC12917350/full.md

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Source: https://tomesphere.com/paper/PMC12917350