Applications of Healthcare Analytics in Multidisciplinary Clinical Decision-Making Across Nursing, Pharmacy, and Diagnostic Imaging Departments

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Published: 2025-06-06
DOI: https://doi.org/10.70102/IJARES/V5S1/5-S1-423
Keywords:
Healthcare analytics, clinical decision-making, nursing, pharmacy, diagnostic imaging, predictive analytics, interprofessional collaboration

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Salman Mohammad Altulaihi
Field Military Medicine, National Guard Health Affairs
Monaa Awadallah Aladwani
National Guard Health Affairs image/svg+xml
Hamad Hadi Saeed Aldughman
Eastern Health Cluster, Buqayq Hospital
Waad Khalid Maringah
King Abdulaziz Medical City - King Abdulaziz Cardiac Center
Fawaz Muslih Alanazi
King Abdulaziz Medical City, National Guard Health Affairs
Turki Zaid Alotaibi
Military School for Health Sciences, National Guard Health Affairs
Ahmad Mohammed Aid Alharbi
Field Medicine, National Guard Health Affairs
Salh Marzog Alghtani
Field Medicine Hospital, Riyadh, National Guard Health Affairs
Ahmad Thaar Alharbi
King Abdullah Brigade Command, Al Ahsa, National Guard Health Affairs
Rakan Nazal Owaid Alruwaili
Field Medicine, Riyadh, National Guard Health Affairs
Majed Hamdan Fehaid Alanazi
Field Medicine Hospital, Riyadh, National Guard Health Affairs

Abstract

Background: Healthcare analytics has emerged as a core component of modern healthcare systems, enabling the transformation of large-scale clinical and administrative data into actionable insights. It integrates data from electronic health records, diagnostic imaging, laboratory systems, wearable technologies, and pharmaceutical databases to support evidence-based decision-making across multidisciplinary clinical environments. Aim: This study aims to explore the role of healthcare analytics in multidisciplinary clinical decision-making across nursing, pharmacy, and diagnostic imaging departments, with emphasis on its contribution to clinical performance, patient safety, and interprofessional collaboration. Methods: A narrative analytical approach was used based on an extensive review of published literature on healthcare analytics, clinical informatics, and interprofessional healthcare practice. The analysis focused on the evolution, types, applications, and clinical implications of descriptive, diagnostic, predictive, prescriptive, and discovery analytics in healthcare settings. Results: Healthcare analytics enhances clinical decision-making by identifying patterns in patient data, supporting diagnostic accuracy, and enabling predictive risk stratification. Nursing practice benefits from real-time patient monitoring and outcome tracking, while pharmacy services utilize analytics to optimize medication safety and therapeutic effectiveness. Diagnostic imaging departments apply analytical tools to improve diagnostic precision and workflow efficiency. Predictive and prescriptive analytics support early intervention, resource allocation, and personalized treatment strategies. Conclusion: Healthcare analytics significantly strengthens multidisciplinary clinical decision-making by improving efficiency, accuracy, and coordination across healthcare teams. Its integration into nursing, pharmacy, and diagnostic imaging promotes patient-centered care, enhances safety, and supports evidence-based practice.

Article Details

Issue

Volume 5, Issue S1 (June), 2025

Section

Articles

How to Cite

Applications of Healthcare Analytics in Multidisciplinary Clinical Decision-Making Across Nursing, Pharmacy, and Diagnostic Imaging Departments (S. M. Altulaihi, M. A. Aladwani, H. H. Saeed Aldughman, W. K. Maringah, F. M. Alanazi, T. Z. Alotaibi, A. M. Aid Alharbi, S. M. Alghtani, A. T. Alharbi, R. N. Owaid Alruwaili, & M. H. Fehaid Alanazi, Trans.). (2025). International Journal of Aquatic Research and Environmental Studies, 5(S1), 214-228. https://doi.org/10.70102/IJARES/V5S1/5-S1-423

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