The role of business intelligence tools in improving healthcare patient outcomes and operations
This paper investigates the role of business intelligence (BI) tools in enhancing patient outcomes and operational efficiency within the healthcare sector. The primary objectives are to analyze the integration of BI tools in healthcare settings, assess their impact on clinical and administrative processes, and evaluate their contribution to improved patient outcomes. The research methodology encompasses a comprehensive literature review, case studies of healthcare institutions that have implemented BI tools, and quantitative analysis of operational and patient outcome metrics pre- and post-BI tool implementation. Key findings indicate that BI tools significantly improve data management and analytics capabilities, leading to better-informed decision-making processes. This enhanced decision-making is linked to reduced patient readmission rates, improved treatment plans, and more efficient resource allocation. Additionally, the study finds that BI tools contribute to operational efficiency by streamlining administrative tasks, reducing operational costs, and improving compliance with regulatory standards. The conclusions highlight the transformative potential of BI tools in healthcare, emphasizing their ability to provide actionable insights through real-time data analysis. These insights facilitate proactive patient care, optimize operational workflows, and ultimately lead to better patient outcomes. The paper suggests that continued investment in and adoption of BI tools will be critical for healthcare providers aiming to enhance patient care quality and operational efficiency. Future research should focus on longitudinal studies to further validate these findings and explore the evolving capabilities of BI tools in healthcare.
Authors
- Opeyemi Olaoluawa Ojo
- Amarachi Queen Olufemi-Phillips
- Stephane Jean Christophe Zouo
- Jeremiah Olamijuwon
- Rahman Akorede Shittu
- Anita Jumai Ehidiamen
- Bamidele Michael Omowole
Publication Details
- Journal
- World Journal of Advanced Research and Reviews
- Published
- 2024-11-15
- DOI
- https://doi.org/10.30574/wjarr.2024.24.2.3414
- Citations
- 15
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 7.93