Analyzing the Economic Viability of AI-Based Drug Recommendation Systems

Satyam Jaiswal

Independent Researcher

Greater Noida, India

Abstract

The increasing complexity of healthcare and the surge in pharmaceutical options have necessitated advanced decision-support tools for personalized drug recommendation. Artificial Intelligence (AI)-based drug recommendation systems promise to improve treatment efficacy and reduce adverse drug reactions by tailoring prescriptions to individual patient profiles. However, the high cost of implementation, integration, and maintenance raises concerns about their economic viability, particularly in resource-constrained settings. This manuscript analyzes the economic viability of AI-based drug recommendation systems by evaluating direct and indirect costs, potential savings from reduced hospitalizations, time efficiency, and long-term benefits through literature review and comparative modeling. The study concludes that while initial investments are significant, the return on investment (ROI) over time can justify their adoption under specific healthcare models, especially in high-volume tertiary care hospitals.

Keywords

Artificial Intelligence, Drug Recommendation System, Economic Viability, Healthcare Cost Optimization, Personalized Medicine

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