Artificial intelligence in nursing and midwifery: A systematic review

Area of Science:

• Nursing and Midwifery
• Artificial Intelligence in Healthcare
• Digital Health

Background:

• Artificial Intelligence (AI) is being integrated into nursing and midwifery to enhance decision-making and patient care.
• Current understanding of AI's real-world applications across all nursing and midwifery domains remains limited.

Approach:

• A systematic literature synthesis was conducted using CINAHL, Embase, PubMed, and Scopus.
• 140 articles were included, with data extracted and analyzed for a descriptive summary.
• The review adhered to the PRISMA checklist for conduct and reporting.

Key Points:

• AI is predominantly applied in clinical practice for patient care (82.14%), with less focus on administration (15.00%) or education (2.85%).
• Most reported benefits were potential, as only 7.14% of studies demonstrated actual real-world advantages.
• Identified risks include biased datasets, the need for clinical interpretation, privacy concerns, and insufficient AI expertise.

Conclusions:

• Development of digital health datasets is crucial for testing and evaluating AI in nursing and midwifery.
• Educational curricula must be updated to equip professionals with AI knowledge, enabling them to lead and participate in digital health initiatives.
• Nurses and midwives should actively engage in interdisciplinary research to assess AI's clinical efficacy and ethical implications.