How Renown Health is Predicting Supply Shortages with PINC AI™

Key takeaways:

• Renown Health, like many healthcare organizations across the U.S. during COVID-19, was hit hard by supply chain challenges. The health system partnered with data experts in the PINC AI^TM Margin Improvement team to get ahead of specific shortages and manage critical supplies.
• PINC AI^TM predictive analytics help healthcare organizations identify specific supply shortages weeks before they occur. They also make it easier to manage critical supplies day-to-day.
• With these tools, Renown Health supply chain and clinical staff were able to proactively address hundreds of potential shortages before patient care was impacted.

It’s no coincidence that supply chain challenges continue to dominate headlines. With issues like inflation, COVID-19 and the Russia-Ukraine war, supply chains are in turmoil. The healthcare sector has been at the forefront of these disruptions.

At the start of the pandemic, securing personal protective equipment (PPE) was the main challenge, but now, shortages of other common supplies like syringes, catheters and sutures abound. In some instances, these shortages can cause clinicians to divert their attention away from patients or even delay procedures, which jeopardizes care quality and patient outcomes.

Now, more than ever, the right supply-chain strategies are urgently needed to optimize limited resources and alleviate shortages. The leaders at Renown Health knew it was time to address their own supply chain instability. Initially, Renown Health, like many health systems across the U.S., managed supply shortages by guessing which supplies were going to be an issue and stockpiling.

“When COVID-19 first hit, we weren't exactly sure what we were going to do. We didn't have a very good data model for what supplies we had on hand, what our burn rate was, or what was our back-order status,” said Mary Shipley, Director of Supply Chain Management at Renown Health. “Quite honestly, even just talking to our clinical staff about what supplies were on order and in pipeline didn't make sense to them; the supplies they needed to provide patient care just weren’t in house, so there was a concern there.”

Use a Supply Chain Data Model that fits YOU

To get a handle on their supply needs, Renown Health began using models from the Centers for Disease Control and Prevention (CDC) and other federal agencies to predict how much of each PPE supply they should order. But this one-size-fits-all approach caused Renown to order far more PPE than they needed – a wasteful and costly error. In order to keep their supply chain operations running efficiently and cost-effectively, Renown realized they needed to utilize a model driven by their own data.

The PINC AI^TM Margin Improvement team helped Renown understand their real rates of supply consumption by automatically extracting, standardizing and visualizing the data within Renown’s ERP. The analytics also helped Renown monitor critical supplies using metrics like Days of Supply on Hand and Average Daily Usage. “I was producing COVID-19 reporting on a daily basis that showed the days on hand, our burn rate and our inventory. This was typically done by a spreadsheet so that's where this whole concept first started,” said Shipley. “PINC AI™ was able to pull all that information together and automate reporting and forecasting of critical supplies.”

Technology and data are being used by health systems across the country to gauge the supplies they will require at any given stage of a disease's course. This is crucial as organizations prepare for upcoming waves and maintain financial sustainability. Simply ordering more is not a sustainable solution and makes the overall problem worse. Having time to prepare clinically approved alternative options and conservation strategies is key.

What is Predictive Analytics?

It’s critical for healthcare leaders to anticipate and preempt problems rather than continuing to react to them. A successful approach to this utilizes predictive models driven by organization-specific data. Often referred to as predictive analytics, this approach uses data and machine learning (ML) to predict the probability of a future outcome.

When applied to predict supply shortages, decision-makers are better able to plan and allocate resources to get a head start on any future shortages they might encounter. The PINC AI^TM Margin Improvement team developed ML-powered analytics that reliably predicted which of Renown’s supplies would be constrained (e.g., placed on supplier allocation) 3-6 weeks into the future. This solution, dubbed the PINC AI^TM Supply Disruption Manager, afforded the supply chain and clinical staff precious additional time to establish substitutes and conservation plans to avert each impending crisis.

Managing Supply Chain Shortages with PINC AI™ Margin Improvement

Using the PINC AI™ Supply Disruption Manager, Renown supply chain staff have obtained advanced notice of future shortages as well as the time savings that enable them to be proactive. “We've been able to look at our item master and establish a substitute for about 80 percent of the items,” said Shipley. “So, that's working with clinicians on what products make acceptable substitutions and it's working with our distribution partners to find out what other supplies are available. It's also working in a scenario where if there's nothing else available for us, what can we do from a rationing or centralized supply standpoint, to be able to take care of the inventory that we do have.”

Healthcare data is abundant, but for healthcare leaders, extracting, integrating and transforming the right data to support real-time decisions that affect outcomes, cost and quality is key. With predictive analytics, Renown Health can better understand their ordering behavior and address potential supply shortages before patient care is impacted.

“We've learned a lot from this pandemic by being able to see all of these lessons learned and create better models and be more in touch with our data and report on it regularly, so we know exactly what's going on in the supply chain,” said Shipley. Ultimately, predictive analytics offers insights for proactive informed decision-making. Healthcare leaders can better support stakeholder collaboration, leading to increased supply chain resiliency.

For more:

• Stay ahead of supply chain shortages. PINC AI™ Margin Improvement is ready to partner with you to help you improve performance and quality across your organization.

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