Real-Time Visibility and Intelligent Orchestration in Healthcare Supply Chain Management: An Architectural Framework

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Authors: Shandilya Avadhanam Venkata Krishna Sastry
Cited by: 0

Abstract

The healthcare supply chain management industry is also facing the issue of visibility despite investing heavily in enterprise resource planning and tracking technologies. Essentially, the issue lies in the lack of overall situational awareness rather than in the collection of information. Medical institutions are facing shortages of life-critical stock while the same item is expiring in the stores. Healthcare professionals also spend a considerable part of their work schedule looking for devices rather than attending to the patients. Traditional point solutions do not solve the specific issue but are all isolated. Existing systems collect data without interpretation and report historical states rather than enabling prospective intervention. The article presents a comprehensive architectural framework for transitioning healthcare operations from static tracking to intelligent orchestration. The proposed framework comprises four interconnected processing layers, including physical signal acquisition through miniaturized sensors, intelligent capture mechanisms utilizing existing infrastructure, artificial intelligence interpretation through cloud-based machine learning, and purpose-built clinical applications delivering actionable workflows. The tool tackles precision in asset management, inventory optimization, and condition monitoring within pharmaceutical supply chain networks. Real-time visibility helps healthcare systems transition from reactive firefighting to predictive optimization. Clinical settings need systems that can constantly analyze information and take action on their own, instead of just gathering more data.

Fields of Study & Subjects

Supply Chain and Inventory Management Quality and Safety in Healthcare Food Supply Chain Traceability

Publication details

Journal / source
International Journal of Computational and Experimental Science and Engineering
Publication date
5 February 2026