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

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Titel: Data Analytics and Administrative Decision-Making in Nursing Management: A Systematic Review.
Autoren: Darach N; Faculty of Nursing, Chulalongkorn University, Bangkok, Thailand.; College of Nursing, University of Illinois Chicago, Chicago, Illinois, USA., Kim MS; College of Nursing, University of Illinois Chicago, Chicago, Illinois, USA., Wisesrith W; Faculty of Nursing, Chulalongkorn University, Bangkok, Thailand., Collins EG; College of Nursing, University of Illinois Chicago, Chicago, Illinois, USA.
Quelle: Journal of nursing management [J Nurs Manag] 2025 Nov 05; Vol. 2025, pp. 4344147. Date of Electronic Publication: 2025 Nov 05 (Print Publication: 2025).
Publikationsart: Journal Article; Systematic Review; Review
Sprache: English
Info zur Zeitschrift: Publisher: Blackwell Scientific Publications Country of Publication: England NLM ID: 9306050 Publication Model: eCollection Cited Medium: Internet ISSN: 1365-2834 (Electronic) Linking ISSN: 09660429 NLM ISO Abbreviation: J Nurs Manag Subsets: MEDLINE
Imprint Name(s): Original Publication: Oxford : Blackwell Scientific Publications, c1993-
MeSH-Schlagworte: Nurse Administrators*/psychology , Decision Making* , Data Science*/methods , Data Science*/trends, Humans ; Data Analytics
Abstract: Competing Interests: The authors declare no conflicts of interest.
Aim: This systematic review aimed to investigate the impact of data analytics on nurse managers' administrative decision-making process and roles.
Background: The growing integration of data analytics in health care has accelerated the shift toward data-driven decision-making in nursing management, aiming to optimize patient care quality and enhance organizational performance within digital healthcare environments. Nurse managers play a pivotal role in leveraging data analytics to support evidence-based management, facilitating more informed, efficient, and strategic administrative decision-making.
Method: This systematic review was conducted in accordance with PRISMA guidelines. A comprehensive search strategy was employed to identify relevant studies published from 2019 through 2024 using four electronic databases-PubMed, CINAHL, MEDLINE, and Embase. A total of 2051 studies were screened, and 83 studies were eligible for full-text screening according to the established inclusion and exclusion criteria. Eight different quality assessment tools were applied. Data tabulation and narrative synthesis were employed.
Results: Twenty-one studies representing eight different study designs were included in the review. There were diverse applications of data analytics across four analytics levels: descriptive ( n  = 4), diagnostic ( n  = 2), predictive ( n  = 9), and prescriptive ( n  = 1). Additionally, integrated approaches combining two levels of analytics were identified ( n  = 5).
Conclusion: The integration of data analytics into nursing management has the potential to enhance an administrative decision-making process across diverse nursing management roles, particularly in four key areas: improving patient care quality, strategic management, nurse staffing and work engagement, and nursing management during health crises.
Implications for Nursing Management: Strengthening nurse managers' analytical and digital competencies through targeted education and continuous training is essential. Ensuring supportive infrastructure can enable more informed, efficient, and evidence-based management, ultimately leading to improved healthcare quality and operational performance. Future research should explore the long-term impact and broader applicability across diverse healthcare settings.
(Copyright © 2025 Nathidathip Darach et al. Journal of Nursing Management published by John Wiley & Sons Ltd.)
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Contributed Indexing: Keywords: data analytics; decision-making; evidence-informed decision-making; nurse managers; nursing informatics; nursing management
Entry Date(s): Date Created: 20251114 Date Completed: 20251114 Latest Revision: 20251116
Update Code: 20251116
PubMed Central ID: PMC12611473
DOI: 10.1155/jonm/4344147
PMID: 41235177
Datenbank: MEDLINE
Beschreibung
Abstract:Competing Interests: The authors declare no conflicts of interest.<br />Aim: This systematic review aimed to investigate the impact of data analytics on nurse managers' administrative decision-making process and roles.<br />Background: The growing integration of data analytics in health care has accelerated the shift toward data-driven decision-making in nursing management, aiming to optimize patient care quality and enhance organizational performance within digital healthcare environments. Nurse managers play a pivotal role in leveraging data analytics to support evidence-based management, facilitating more informed, efficient, and strategic administrative decision-making.<br />Method: This systematic review was conducted in accordance with PRISMA guidelines. A comprehensive search strategy was employed to identify relevant studies published from 2019 through 2024 using four electronic databases-PubMed, CINAHL, MEDLINE, and Embase. A total of 2051 studies were screened, and 83 studies were eligible for full-text screening according to the established inclusion and exclusion criteria. Eight different quality assessment tools were applied. Data tabulation and narrative synthesis were employed.<br />Results: Twenty-one studies representing eight different study designs were included in the review. There were diverse applications of data analytics across four analytics levels: descriptive ( n  = 4), diagnostic ( n  = 2), predictive ( n  = 9), and prescriptive ( n  = 1). Additionally, integrated approaches combining two levels of analytics were identified ( n  = 5).<br />Conclusion: The integration of data analytics into nursing management has the potential to enhance an administrative decision-making process across diverse nursing management roles, particularly in four key areas: improving patient care quality, strategic management, nurse staffing and work engagement, and nursing management during health crises.<br />Implications for Nursing Management: Strengthening nurse managers' analytical and digital competencies through targeted education and continuous training is essential. Ensuring supportive infrastructure can enable more informed, efficient, and evidence-based management, ultimately leading to improved healthcare quality and operational performance. Future research should explore the long-term impact and broader applicability across diverse healthcare settings.<br /> (Copyright © 2025 Nathidathip Darach et al. Journal of Nursing Management published by John Wiley & Sons Ltd.)
ISSN:1365-2834
DOI:10.1155/jonm/4344147