Automate or Delegate? Digitizing Your Strategy for Supply Chain Data Management

Removing inaccuracies and inefficiencies from data can help healthcare proactively address inevitable disruptions, pivot faster and build stronger supplier relationships. The result is a more resilient supply chain that helps to drive better patient outcomes and cost savings. But with constant changes and multiple data sources, keeping item data clean is arduous.

Fortunately, supply chain teams can now turn to new capabilities in their cloud ERPs to synchronize data cleansing, correct errors, and fill gaps. This includes all item data (e.g., item masters, P.O. history and contract data) that multiple teams depend on.

During a recent webinar, GHX’s Pete Nelson and Keith Lohkamp, Senior Director, Healthcare Industry Strategy at Workday, discussed how and why automation has evolved to accelerate the transformation to cloud-based, digital supply chain management. They were joined by Prisma Health Director of Supply Chain Information Systems Leslie Thomas, who described the bold steps that her organization took to integrate a cloud-based data management solution and service that keeps their supply chain data current and synchronized.

Data Management Best Practices to Prepare for Cloud ERP

• Pete Nelson, General Manager, Global Alliances

Your cloud ERP system will only be as valuable as the data that powers it. An investment this costly—both in time and financial resources—should be supported by a modern item data strategy that helps ensure the enhanced visibility, efficiency and resiliency you understandably expect. It provides your organization with data that’s comprehensive, precise, trusted and actionable.

Supporting the clinically integrated supply chain

• Hani Elias, Senior Vice President and General Manager, Lumere, a GHX company

To deliver greater value in healthcare, providers and suppliers must first be able to identify those factors that impact cost, quality and outcomes—as the adage goes, you can’t manage what you can’t measure. Historically, the clinical and operational sides of healthcare have worked in silos, making collaboration and data sharing a challenge. But as payments for care delivery are increasingly tied to quality and efficiency, the industry has begun the hard work of tearing down long-standing barriers.

GHX and Workday Align in the Cloud for Healthcare

• Pete Nelson, General Manager, Global Alliances

Over the past 30 years, hospitals have been adopting technologies to steadily increase process automation throughout their operations in an effort to enhance efficiency and reduce costs. It began in the 1980s with the initial use of mainframes and desktop computers for electronic patient registration, continued through the late 1990s with “Best of Breed” systems, such as materials management information systems (MMIS) for order processing and inventory management, and then transitioned in the early 2000s to present day with the adoption of on-premise (“on-prem”) enterprise resource planning (ERP) systems that automated both materials management and financial operations.

Clean Up Dirty Data in the Item Master: A long-term plan

While every healthcare organization has its own unique challenges when it comes to item master data management, many of the problems are the same – inaccuracies, duplicates, missing information – in essence “dirty data” that causes errors and rework throughout a number of operational and clinical processes (e.g. procurement, inventory management, patient billing).

Both Catholic Health and Oregon Health & Science University have implemented master data management strategies that leverage the NuVia® content management solution. While these organizations have derived significant value from their work, they can tell you that best-in-class data management doesn’t happen by accident. In this Q&A, Ashleigh E. Gross, supervisor for Supply Chain Analytics at Catholic Health, and Dina Walden, Content Manager for Oregon Health & Science University, share tips on how they developed sustainable processes to achieve and maintain quality data.