Data Analytics and Administrative Decision-Making in Nursing Management: A Systematic Review

Area of Science:

• Nursing Management
• Health Informatics
• Data Science in Healthcare

Background:

• Healthcare is increasingly adopting data analytics for evidence-based decision-making.
• Nurse managers are key to leveraging data for optimizing patient care and organizational performance.
• Digital transformation in healthcare necessitates enhanced administrative processes.

Purpose of the Study:

• To systematically review the impact of data analytics on nurse managers' administrative decision-making.
• To explore the evolving roles of nurse managers in data-driven healthcare environments.
• To identify key areas where data analytics influences nursing management.

Main Methods:

• Systematic review adhering to PRISMA guidelines.
• Comprehensive search of four databases (PubMed, CINAHL, MEDLINE, Embase) for studies from 2019-2024.
• Screening of 2051 studies, with 21 eligible for review, using narrative synthesis and quality assessment.

Main Results:

• Data analytics applications span descriptive, diagnostic, predictive, and prescriptive levels.
• Twenty-one studies with diverse designs explored data analytics in nursing management.
• Integrated approaches combining multiple analytics levels were also identified.

Conclusions:

• Data analytics integration enhances administrative decision-making in nursing management.
• Key impact areas include patient care quality, strategic management, staffing, and crisis management.
• Developing nurse managers' digital competencies is vital for effective data utilization.