Redesigning Value-Based Healthcare Delivery Using Data-Driven Decision Support Systems and AI-Powered Predictive Analytics

Arina Bhavya Fatima

Authors

Arina Bhavya Fatima AI Research Scientist (Healthcare), Saudi Arabia. Author

Keywords:

Value-based healthcare, Predictive analytics, Decision support systems, Artificial intelligence, Data-driven healthcare

Abstract

The shift from volume-based to value-based healthcare models marks a fundamental transformation in how care is delivered, evaluated, and reimbursed. This paper investigates the role of data-driven decision support systems (DSS) and artificial intelligence (AI)-enabled predictive analytics in facilitating this transition. By synthesizing insights from the study examines the technological frameworks and clinical applications that support more efficient, outcomes-oriented care.

The analysis explores how predictive models can enhance clinical decision-making, reduce diagnostic errors, and minimize hospital readmissions, thereby aligning with the goals of value-based healthcare. Visual comparisons between traditional and value-based delivery systems are provided to illustrate structural and operational contrasts. Additionally, the paper proposes an integrated framework that combines DSS, predictive analytics, and continuous performance monitoring to support sustainable healthcare transformation. The findings suggest that AI-enhanced, data-informed strategies are critical to improving patient outcomes, optimizing resource use, and ensuring accountability in modern healthcare systems.

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