Year: 2025 | Month: January | Volume: 15 | Issue: 1 | Pages: 196-202
DOI: https://doi.org/10.52403/ijhsr.20250125
Data Analytics for Informed Healthcare Leadership Decision Making: A Scoping Review
Anthony Vincent Razzano
Department of Business Administration and Economics, Worcester State University, Worcester, Massachusetts, United States.
ABSTRACT
Background: In recent decades, data analytics has emerged as a transformative force in healthcare, leveraging advanced technologies to analyze vast and complex datasets. This evolution has revolutionized how healthcare organizations operate, from enhancing clinical decision making to optimizing resource allocation and improving patient outcomes. Key applications include medical image analysis, disease surveillance, outbreak prediction, and personalized treatment strategies. The integration of big data analytics, machine learning, and artificial intelligence has enabled healthcare providers to extract valuable insights from both structured and unstructured data sources, stored in electronic health record systems and other repositories. These insights not only inform strategic decisions but also support evidence-based practices and operational efficiencies across various healthcare settings. Despite its promise, challenges such as data quality assurance, security concerns, and the need for robust analytical methodologies remain critical for the widespread adoption and effective implementation of data analytics in healthcare.
Methodology: This scoping review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews checklist to explore the impact of data analytics on healthcare system performance. A systematic search was conducted on PubMed for English-language articles published in 2023 using key terms "data analytics," "leadership," "decision making," and "hospital." Initially identifying 20 relevant articles, screening of titles and abstracts led to the selection of 5 articles for full-text review. Three articles met the inclusion criteria and were synthesized to examine trends, challenges, and outcomes related to the utilization of data analytics in healthcare leadership. The review centers around the population, intervention, comparison, and outcome (PICO) question “Among hospital leadership, does the utilization of data analytics for decision making compared to traditional methods improve healthcare system performance?”
Conclusion: The findings reveal the transformative potential of data analytics in healthcare leadership, revealing significant insights into clinical practices, patient management, and system-wide efficiencies. The review identifies a need for continued integration of qualitative and quantitative analytics methodologies to address complex healthcare challenges effectively. Future research should prioritize refining data collection processes, enhancing interdisciplinary collaboration, and investing in advanced analytics capabilities to support evidence-based decision making and improve healthcare outcomes globally.
Key words: data analytics, leadership, data-driven decision making