Paper Title
ENHANCING HEALTHCARE OUTCOMES THROUGH DATA-DRIVEN DECISION MAKING: A BUSINESS ANALYTICS APPROACH
Abstract
Healthcare systems worldwide are buckling under the pressures of rising costs, increases in patient demand and the complexity of chronic disease management. It is in this context that data-driven decision-making (DDM) backed by business analytics (BA) have become a critical enabling factor for efficiency, precision, and better patient outcomes. This paper investigates the role of BA in improving healthcare outcomes by means of a systematic review of the recent empirical studies and a secondary analysis of quantitative datasets from sources worldwide, such as the World Health Organization (WHO), the Organization for Economic Co-operation and Development (OECD) and the Centers for Medicare & Medicaid Services (CMS). The study combines descriptive analytics, predictive analytics, and prescriptive analytics models to determine their contribution to operational efficiency and cost reduction and clinical effectiveness. Findings include that predictive analytics can lead to a saving of up to 20% in hospital readmission, descriptive dashboards can enhance resource allocation and increase staff productivity, and prescriptive analytics can be used to optimize treatment pathways, leading to measurable improvements in patient satisfaction and clinical outcomes. Unlike previous studies that tend to separate the clinical/operational benefits, this paper introduces a holistic framework of the linkages between BA adoption and strategic decision-making at organizational and policy levels. The novelty of this study is the cross-functional nature of the approach, which emphasizes the synergy of clinical, managerial, and policy decisions which are grounded in analytics. Ultimately, the results highlight the importance of healthcare organizations investing in the capabilities of BA and aligning the data strategy with patient-centered care goals, all while achieving sustainable improvements in both outcomes and efficiency.
Keywords - Business Analytics, Data-Driven Decision-Making, Healthcare Outcomes, Predictive Analytics, Health Systems