Lasting Progress in Lab Kit Management: A Follow-Up Conversation with UPMC Hillman Cancer Center
In summer 2023, Slope attended the Association for American Cancer Institutes (AACI) Clinical Research Innovation conference, where we co-presented a research poster with the University of Pittsburgh Medical Center Hillman Cancer Center (UPMC Hillman). UPMC Hillman is one of only three NCI-designated comprehensive cancer centers in the entire state of Pennsylvania.
UPMC Hillman’s poster findings were remarkable. Over a nine-month period, their use of Slope’s software in two of their disease centers increased the amount of unexpired, traceable clinical inventory by more than 60%.
In the nearly one year since AACI 2023, UPMC Hillman has continued to see sustained improvements in their handling of clinical inventory across their various disease centers despite prolonged growth across their clinical trial portfolio. This is all thanks to Slope’s clinical trial execution platform (which is free for sites!).
Slope’s Site Development Lead, Alex Yant, caught up with Jamie Voyten, a Senior Clinical Research Laboratory Manager at UPMC Hillman and an author of the original poster, to learn more about the new and exciting data she has collected regarding the long-term effectiveness of her organization’s implementation of Slope.
Before we dive into your institution’s journey with Slope, let’s start by painting a picture of the clinical trial landscape at UPMC Hillman for our readers. How many studies are you running? Which phases?
Our department is broken down into twelve disease centers, plus multiple community network sites. Each disease center operates within its own silo under our clinical trial department. My group touches all of the disease centers, but each center has its own unique trial portfolio. As a whole, our institution strives to keep our portfolio diverse, and we aim to implement at least 200 active therapeutic studies per year across all clinical trial phases. Our operation includes a separate and high-accruing Phase I disease center, which manages an extensive portfolio of first-in-human studies and maintains more lab kits than any of our other centers.
How were your disease centers managing lab kits prior to Slope?
Some of our disease centers tracked lab kits with spreadsheets, but we relied heavily on verbal communication and simple documentation (sticky notes, etc.). Most notably, we lacked a standardized system for inventory tracking. Processes varied among disease centers, and even among site staff within the same disease center. It was chaotic.
And for those who may not be familiar, can you share how your organization originally heard about Slope?
We started toying around with the idea of giving Slope a try when we first heard about it back in 2018, but we initially didn’t take the initiative to move forward. The reality of our situation was that we had lab kits scattered all over our facility, we were working with limited staff and limited space, and at the time we didn’t feel we were equipped to pilot a new system.
Fast-forward to 2021, and we started getting even more studies and even more supplies. That’s when we shifted our focus to piloting Slope to see if logging all of our inventory into Slope could save staff time.
Can you offer a recap of your original poster project that looked at the impact of Slope on your inventory management processes? What was the scope of your project?
We needed an unbiased and data-driven way to assess our inventory, so in 2022 we started a pilot with two of our disease centers. The first disease center we looked at was our very busy, high-accruing Phase I disease center with over 30 staff members. Not only did this center have the most hands touching clinical inventory and patient samples, but their study cohorts also open and close very quickly. In general, their trial portfolio is really dynamic and fast-paced. We also looked at a disease center that had less trial activity overall to see if Slope could help our staff better manage our inventory under a variety of circumstances.
Once we identified the disease centers that we wanted to pilot, we quantified all of the inventory they had. There were lab kits stashed under desks, hidden behind doors, and stored on countless shelves. Staff performed a blind walk-through, quantified our lab kit data, and uploaded that into Slope.
From there, we were able to generate data that demonstrated the effectiveness of Slope in both of these disease centers, and we were able to present our findings at AACI in 2023.
What results did you see in the original pilot?
In our first poster, you’ll see that we had very little inventory that we had accounted for before using Slope, meaning we didn’t know what most of our inventory was and whether or not it was in a ready state for use. We had a lot of expired, excess inventory.
From there, the plan was to get rid of the excess and quantify what we called “the gray area” (i.e., inventory that the disease center wasn’t previously aware of). In the original poster, you’ll see that the pie charts keep moving towards the green (i.e., known, unexpired inventory) over time, which was the goal. We quantified what we had, where it was, and got rid of things that were either expired or from closed studies. This took time; it wasn’t something that happened overnight. But we were able to get our Phase I disease center down to only 3-5% inventory that was unaccounted for, and their expired inventory was much lower.
We also looked at another disease center that wasn’t as transient, had more stable staffing, and less inventory turnover. We found that while this disease center was slightly better managed on the front end by site staff, they still had a lot of expired inventory and they still had inventory that hadn’t been accounted for. By using Slope, it was quicker for them to be able to get everything into a ready state.
After about nine months of using Slope for managing our lab kits at those two disease centers, the large disease center was able to manage their supplies a lot better. The smaller disease center was able to remain fully in the green over an extended period of time so that they didn’t have any expired inventory on hand. As a result, we were able to re-allocate space accordingly.
We have also experienced significant time savings thanks to Slope, which we were able to quantify. When 68% of items at our site were not accounted for and/or were expired, we were spending a lot of time sorting through excess inventory, as opposed to walking over, grabbing a kit off the shelf, and going.
Slope has also saved a lot of time for patients who are in screening and patients who have end-of-treatment visits. Those visits often require unscheduled kits, which could be needed at any time. Now we’re not spending time looking for them. As a result, our patients are able to get out of the building quicker and don’t have to wait for a lab draw.
In the time since your original poster project, you’ve continued to collect additional data on the amount of stock marked as unaccounted for or expired, even as UPMC Hillman’s clinical trial portfolio has seen sustained growth. What trends have you seen in this newer data?
Since our original pilot, we’ve rolled out Slope completely across our twelve disease center departments and generated overall departmental data. This was very exciting to see — and even a bit terrifying — to actually quantify the number of supplies we have. We could tell by walking around how much we had, but seeing a quantifiable number and seeing that number change over time helped us determine that we needed to go full-force with implementing Slope.
After we looked at the data from the two disease centers from our original pilot, we assumed that all of our disease centers were more similar to the more stable disease center that we studied. We thought maybe the issue with lab kits only applied to early-phase studies (as we saw with our Phase I center), but that was not at all the case. 58% of our inventory across all of our disease centers ended up being either expired or previously unaccounted for. That’s a lot of forts that you can build with your shippers. That’s a lot of kits on hand that you don’t necessarily need.
From there we were able to implement the same process as before where we gradually got rid of expired kits, identified all of our inventory, entered our data into Slope, and discarded unusable supplies.
After a year, we found that over half of our inventory was ready and accounted for. Only a small percentage of our on-hand inventory had expired. This trend was remarkable given the fact that our total inventory increased by an additional 7,000 items — or about 41% — over that time period. We still had inventory that hadn’t been accounted for, which helped us identify an area for improvement. But through all of this, we still had new studies starting up, and new supplies were coming in.
We did another walkthrough earlier this year. Although inventory levels continued to grow at a rapid pace, we were so excited to find that only 3% of our inventory was unaccounted for; 74% of our items were unexpired, accounted for, and ready for use; and only 23% of our inventory was expired. Our goal for 2025 is to be very close to having all of our on-hand inventory documented in Slope and ready for use at our main hub and community sites.
What would you say to other research sites experiencing similar issues?
You need to have the mindset that change doesn’t happen overnight — it has to be a process. Invest a little time up front, because it does pay off on the backend.
Because of Slope, we’re now able to manage the front-end supply of the inventory. We’re no longer getting as much excess inventory in the door because we have cut back on oversupply. We’re able to talk to sponsors and say, “Please don’t send us this,” “We don’t need this much,” or “We don’t have enough space for this.”
Implementing Slope is also better for your staff. Now instead of having to unpack 50 boxes of lab kits, maybe they’re only unpacking 20. Now you’re saving time on the front end. Conversely, we’re also able to have more productive conversations with our leadership about our staffing needs based on quantifiable data.
My advice to sites would be to give Slope a try for 30 days across one of your disease centers or functional groups and observe the change on a large scale. We saw progress after a month of using Slope, and from there we kept the momentum going. The 30-day mark is when those expiration alerts started coming in, and that made a real difference. We’re not tracking that — Slope is!
I’ll also add that you (Alex) were extremely helpful in helping us implement Slope. I emailed you several times a day during this process, and Slope was there to help us get this moving.
Slope is also very receptive to feedback. Be vocal about what’s working for your site versus what’s not working. Thanks to the Slope team, we were able to get the features we needed in the platform, or at least figure out how to use the system in a way that benefited our institution.
Case Study Contributor
Jamie Voyten is a Senior Clinical Research Laboratory Manager for UPMC Clinical Research Services with over 15 years of experience in laboratory science, a Six Sigma Black Belt, and over 10 years’ experience in GMP, GCLP, and Clinical Research Laboratory science. She oversees over 600 clinical trial protocols’ correlatives and ensures staff are adequately trained in correlative sample collection and processing to allow clinical trial protocols to meet their objectives. Jamie is the mom of two highly energetic young boys and one not-so-energetic cat.
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