GHX Healthcare Hub

Introduction Healthcare organizations are under pressure from every direction. Supply disruptions remain a persistent challenge. Margins continue to tighten. Care delivery continues to expand beyond the hospital, creating increasingly complex clinical workflows and operational dependencies. At the same time, provider and supplier organizations are expected to improve efficiency, strengthen resilience and support better patient outcomes while operating with limited resources.

Introduction Healthcare supply chain leaders have spent the past decade investing in digital transformation, modernizing enterprise resource planning (ERP) platforms, expanding automation, strengthening analytics capabilities and adopting AI to improve visibility and operational efficiency.

The Strategic Imperative The future of value analysis is not human versus AI. It is AI-enabled, human-led governance that combines the speed of artificial intelligence with the accountability, expertise and judgment of experienced healthcare professionals. At GHX, we believe technology should strengthen—not replace—clinical and operational expertise. Our advisory and research teams, which include clinicians, PhDs and healthcare operators, ensure that insights are not just fast, but defensible.

What are the challenges with AI explainability in healthcare supply chains? Black Box Concerns Some AI systems use opaque models that produce outputs without showing how they were generated, making them difficult to interpret. This limits confidence and slows adoption. The difference between traditional AI and explainable AI is significant—explainable AI provides greater interpretability, which helps build trust and supports better organizational decision-making.

Supply Chain Teams Have More Data Than Ever – But Less Clarity Healthcare supply chains generate large volumes of data across purchasing, inventory, suppliers, contracts and increasingly, clinical care workstreams. However, that data is often spread across multiple tools and reports, requiring technical expertise to extract and time-intensive analysis to understand what matters most. When information is fragmented, teams spend more time gathering data than acting on it.

Ways AI Enables Healthcare Supply Chain Efficiency and Resilience Administrative Automation Benefits Generative AI is increasingly being adopted in healthcare supply chains to streamline workflows, improve clinical productivity, and drive innovation. By leveraging generative AI, organizations can enhance operational efficiencies, boost patient engagement, and accelerate advancements in medical technology and digital therapeutics. AI in healthcare order automation builds on that foundation.

The Role of Network-Scale Data in Responsible AI Responsible AI practices become significantly more powerful when AI systems are fueled by network-scale data and connected AI technologies. Broader datasets enable: Stronger pattern detection More accurate benchmarking Earlier identification of supply disruptions Network-driven intelligence allows providers to move from reactive to proactive decision-making—surfacing risks and opportunities earlier than isolated systems can.

What are the common challenges with POAs? Healthcare organizations often face several challenges related to order confirmations: Lack of standardization Suppliers may send POAs through multiple channels, including fax, email or phone, making it difficult to maintain consistency and visibility. In fact, only 2% of healthcare suppliers surveyed say they are excelling in order automation.

Cash Flow Risk Often Begins Before the First Order The contract-to-cash journey starts with accurate customer, contract and item data. When this information is misaligned, orders are more likely to generate exceptions and invoices are more likely to be disputed and delayed as a result.

Marlin Doner, VP of Product Management Tuesday, April 21, 2026 The healthcare supply chain has evolved far beyond procurement and inventory management, connecting providers, suppliers and distributors across increasingly complex care delivery networks. Today, it sits at the intersection of care delivery, financial performance and supplier operations — connecting data from purchasing systems, clinical platforms and supplier ecosystems across the enterprise.