The HPN Conversation: From Supply Chain to Care Chain
Key Highlights
- Healthcare supply chains are shifting from support functions to strategic partners directly linked to patient outcomes and clinical decision-making.
- The COVID-19 pandemic highlighted vulnerabilities, prompting increased focus on resiliency planning, contingency sourcing, and operational flexibility.
- Integrating ERP, EMR, and revenue cycle systems is crucial for achieving end-to-end visibility and improving operational efficiency.
- Stanford Health Care improved data quality and system integration, reducing 'special' item orders from 43% to 8%, enhancing standardization and revenue cycle workflows.
- Overcoming cultural silos and balancing standardization with physician preference are key challenges in creating a unified, efficient care chain.
Healthcare supply chain leaders are increasingly being asked to think beyond purchasing, logistics, and inventory management. As financial pressures, disruption risks, and clinical complexity continue to rise, many health systems are rethinking how supply chain connects to patient care, physician decision-making, and operational performance across the organization.
That evolving mindset was at the center of a recent Healthcare Purchasing News webinar, "From Supply Chain to Care Chain: Driving Clinical Integration and Operational Excellence," sponsored by Amazon Business. During the discussion, Omar Devlin, Executive Director of Supply Chain Technology and Analytics at Stanford Health Care, shared how healthcare organizations are working to build more resilient, data-driven, and clinically integrated supply chain operations.
For Devlin, the concept of “care chain” reflects a broader shift happening across healthcare. Supply chain is no longer viewed solely as a support function focused on product movement and cost containment. Instead, it is becoming an increasingly strategic function tied directly to patient outcomes, physician collaboration, operational visibility, and financial sustainability.
The conversation explored several major themes shaping healthcare supply chain today, including pandemic-driven resiliency planning, disruption modeling, physician engagement, data integration challenges, and the growing importance of connecting ERP, EMR, and revenue cycle systems into a more unified operational framework. Stanford’s efforts to improve item master data quality, reduce non-standard purchasing, and expand procedural analytics also offered a practical look at how health systems are beginning to bridge long-standing silos between supply chain and clinical care.
Daniel Beaird, Editor-in-Chief, HPN: When you hear the phrase “supply chain to care chain,” what does that mean inside Stanford Health Care today?
Omar Devlin, Executive Director of Supply Chain Technology and Analytics, Stanford Health Care: At the center of everything we do in healthcare is the patient experience and patient care. That’s what makes healthcare supply chain fundamentally different from many other industries.
Outside healthcare, supply chains are often focused primarily on profitability, customer demand, and ensuring products are available at the right place and price. In healthcare, our responsibility is much broader because every operational decision ultimately touches patient care.
For us, “care chain” means ensuring clinicians have the right products, at the right place, at the right time, while also managing disruption risk, substitutions, shortages, and operational complexity behind the scenes so those issues never impact patient outcomes.
Healthcare is also incredibly complex operationally. We manage approximately 100,000 SKUs across the network, and at any point we’re navigating supply disruptions, substitutions, changing physician preferences, and patient variation. The challenge is maintaining optionality while still driving efficiency and resiliency throughout the organization.
Beaird: How has the pandemic changed the relationship between supply chain and patient care?
Devlin: The pandemic was a major catalyst for the industry. It exposed how vulnerable healthcare supply chains could become during prolonged disruption events.
Before COVID, many organizations relied heavily on inventory levels and traditional sourcing models without fully appreciating how quickly global disruptions could affect care delivery. During the pandemic, healthcare organizations learned the importance of having contingency planning already in place — alternate sourcing strategies, pre-approved substitutions, and better visibility into supply risk.
We’ve also experienced additional disruption events since then, whether it’s IV fluid disruption, cyber incidents affecting suppliers, or geopolitical and weather-related events. What’s improved significantly is healthcare’s ability to pivot more quickly during disruptions.
Today, organizations are much more focused on resiliency planning and operational optionality. Technology is also helping make those transitions easier by improving reporting, substitution management, and visibility into alternate sourcing strategies.
Looking ahead, I think the next evolution is predictive disruption modeling — essentially using simulation capabilities and digital twin concepts to understand how different disruption scenarios could impact operations before they occur.
Beaird: Is clinical integration becoming the next major frontier for healthcare supply chain?
Devlin: Absolutely. One of the biggest opportunities — and challenges — in healthcare today is connecting fragmented systems and fragmented data.
Healthcare organizations often have ERP systems, EMRs, revenue cycle systems, analytics platforms, and other applications that were designed independently to solve specific operational problems. The issue is they don’t always communicate effectively with one another.
That fragmentation makes it difficult to create a true end-to-end operational view. Ideally, we should be able to understand the entire chain — from product purchasing and inventory management all the way through clinical utilization, patient outcomes, and reimbursement.
Compared to other industries, healthcare still has significant opportunity to improve holistic operational visibility across those systems.
Beaird: What has Stanford done to improve that level of integration?
Devlin: One of our major initiatives has focused on improving item master data quality and strengthening integration across systems following our ERP implementation.
We manage around 100,000 items, and each item contains approximately 135 different attributes. That creates a tremendous amount of operational complexity.
What we found was that data wasn’t always flowing cleanly between systems and revenue cycle platforms. There were duplicate fields, inconsistent coding, missing attributes, and manual workarounds happening across departments.
Through significant cross-functional collaboration, we focused heavily on data health, data governance, and integration accuracy. We reduced large numbers of problematic data elements, improved charge capture workflows, and strengthened traceability throughout the organization.
Beaird: Were there measurable operational gains from those efforts?
Devlin: Yes, several.
One major improvement involved reducing what we call “special” item orders — essentially products ordered outside standard item master workflows.
At one point, approximately 43% of our orders were classified as specials. That creates visibility challenges, traceability issues, and inefficiencies throughout the system.
We’ve now reduced that number to roughly 8%, which significantly improves standardization, tracking, reporting, and downstream operational workflows.
We also improved revenue cycle efficiency because cleaner data now flows more effectively between systems. Previously, revenue cycle teams often had to manually code products or correct information. By improving item master accuracy and integrations, we dramatically reduced manual intervention requirements.
Beaird: What are some of the biggest barriers healthcare organizations still face around integration?
Devlin: One major challenge is cultural.
Healthcare organizations still tend to operate in silos. Clinical teams focus appropriately on patient care. Supply chain teams focus on inventory and logistics. Revenue cycle teams focus on reimbursement and coding.
Each group is optimizing for different priorities, but they don’t always have visibility into how decisions impact other parts of the organization.
The fragmentation of healthcare IT systems reinforces those silos because it’s difficult for teams to see the downstream operational consequences of inaccurate data, inconsistent workflows, or disconnected processes.
Another challenge is healthcare’s complexity itself. Unlike many industries, healthcare cannot simply standardize everything around cost. Patient variation matters. Clinical judgment matters. Physician preference matters. That creates a much more nuanced operational environment.
Beaird: How do you balance standardization with physician preference and patient-specific care?
Devlin: That’s one of the toughest challenges in healthcare operations.
In other industries, standardization decisions are often primarily cost driven. Healthcare is different because patient outcomes always come first.
There are legitimate situations where different products may be clinically appropriate for different patients. The challenge becomes understanding what variation is necessary versus what may represent unwarranted variation.
We’ve spent a lot of time analyzing procedural variation, preference cards, and supply utilization patterns to better understand those differences.
The key is not eliminating physician choice. It’s creating better transparency and data-informed conversations so organizations can distinguish between clinically necessary variation and opportunities for improvement.
Beaird: How is Stanford engaging physicians in sourcing and standardization discussions?
Devlin: One example is our procedural analytics program, which I’m very excited about.
The platform allows us to analyze supply utilization patterns across procedures, physicians, and service lines. It highlights variation in product selection, procedural costs, and utilization patterns in a way that supports more informed clinical conversations.
For example, if one surgeon consistently uses a $2,000 product while others performing the same procedure use a $1,000 alternative, the platform helps surface that information transparently.
The goal is not to dictate physician behavior. It’s to create visibility and support collaborative conversations around value, outcomes, and standardization opportunities.
What’s been especially valuable is giving clinicians better comparative information while still respecting clinical judgment and patient-specific decision-making.
Beaird: Looking ahead, where do you see healthcare supply chain evolving next?
Devlin: I think healthcare supply chain will continue becoming more integrated with clinical and operational decision-making.
We’ll see greater use of predictive analytics, disruption modeling, procedural analytics, and connected data environments that help organizations make faster, more informed decisions.
The future is about building a more resilient, transparent, and clinically integrated care chain — one capable of supporting both operational efficiency and better patient outcomes simultaneously.
