Supply Chain Enterprise System Integrations in Healthcare: Technical Overview
This article comprehensively examines enterprise system integrations within healthcare supply chains, exploring the technical frameworks, methodologies, and standards that enable effective interoperability across the healthcare ecosystem. The article establishes the critical importance of integration to address key challenges in healthcare supply chains, including clinical-supply synchronization, regulatory compliance, multi-stakeholder communication, and temperature-sensitive logistics management. The article details the core system landscape comprising ERP systems, Warehouse Management Systems, Electronic Health Records, Vendor Management Systems, and Transportation Management Systems, highlighting how their interconnection creates value across healthcare operations. Integration methodologies, including API-first approaches, EDI implementations, and event-driven architectures, are thoroughly analyzed for their benefits and applications in healthcare contexts. The article examines data standards and interoperability, with a particular focus on GS1 standards implementation and HL7/FHIR integration points that bridge clinical and supply chain domains. Implementation considerations, including master data management, security frameworks, and testing methodologies, provide practical guidance for successful integration initiatives. The article explores emerging technologies reshaping healthcare supply chain integration, specifically blockchain applications for supply chain integrity and AI-driven predictive analytics for enhanced decision-making. Throughout, the article draws upon findings from multiple studies across diverse healthcare settings to provide evidence-based insights on integration best practices and their impact on operational efficiency, regulatory compliance, and patient safety.
Authors
- Ajay Mutukula
Institutions
- Kite (United States) (US)
Publication Details
- Journal
- International Journal of Advanced Research in Science Communication and Technology
- Published
- 2025-03-30
- DOI
- https://doi.org/10.48175/ijarsct-24608
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00