por Lauren Dubinsky
, Senior Reporter | February 22, 2021
From the January/February issue of HealthCare Business News magazine
The health system has their own consolidated service center that already had a fair amount of PPE in stock and it’s now their strategic initiative to build up that inventory supply.
“We have continued to build that up knowing that there would be a potential additional surge expected,” said Aafedt.
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Banner Health also worked to identify local sourcing instead of offshore sourcing and partnered with Prestige Ameritech, the largest U.S.-based manufacturer of face masks, including N95 respirators and surgical masks. The health system also acquired a minority stake in the organization.
At the height of the initial surge, Banner was using nearly a million disposable gowns per month. They decided to implement reusable isolation gowns and partnered with a laundry provider to clean them. They found that one reusable gown can account for roughly 75 disposable gowns. After switching to this option, they reduced the use of disposable gowns to roughly 200,000 per month.
Leveraging analytics for real-time intelligence
Adrian R. Bissette and his team at Children’s Healthcare of Atlanta have succeeded in the face of many adversities. From product recalls to new regulatory mandates, their program relies on data-driven reporting to improve inventory performance and make the most of a tough situation.
“The past several flu and respiratory seasons prepared us for sudden substantial demand increases and an unpredictable supply chain environment,” said Bissette, whose title is senior supply chain engineer. However, he added, with COVID-19 they “faced a major challenge getting to a place where we could be proactive.”
Ultimately, they were able to overcome that by building dynamic dashboards and leveraging advanced analytics. That gave the supply chain team the ability to drive process and performance improvement instead of continually reacting to disruptions.
“The biggest lesson learned was constantly looking at how to adapt to a drastically changing environment,” said Bissette.
For instance, as more items were put on allocation, they had to enhance their demand model to account for those changes. Allocated items can vary daily in some cases and source data often needs to be scrubbed and converted before buyers can create a purchase order.
Adapting the analytics helped them to see allocation changes in close to real-time, explained Bissette. When that was coupled with their collaborative process, it led to a dramatic decrease in the time from getting an allocation report to submitting a purchase order.