Episode 2: The Data We Slay

In Episode 2, Cody Charbonneau from Blue.Point joins the podcast team as we take a closer look at one of the most powerful tools in modern healthcare: DATA. What exactly do we mean when we talk about “data” in a hospital supply chain setting? Why has it become so critical to patient care, operational efficiency, and decision-making?

From improving patient outcomes to optimizing workflows, data touches every role in a healthcare organization. Whether you’re on the front lines of patient care or working behind the scenes, this episode will help you better understand how data and value analysis impacts your work—and why it matters more than ever. Tune in to build your data literacy and see how informed decisions start with the right information. 

Want to learn more about Blue.Point? Contact us today for a free product demo! More information at www.bluepointscs.com or email jdoty@bluepointscs.com.

Data Slayer Podcast

Through this podcast, our subject matter experts will cover in-depth conversations on healthcare data, clinical research, industry trends, real-world stories, and more. 

Blue.Point provides health systems with a specialized data analysis platform designed to optimize clinical product utilization. Our technology identifies savings opportunities and delivers non-bias insights on product best practices, standardization, and utilization-driven impact across hospital systems.

Interested in learning more? Visit www.bluepointscs.com

Transcript

SPEAKER_02 0:04

Welcome to the Data Slayer podcast brought to you by the team at Blue Point Supply Chain Solutions, where insight meets impact. I am your host, Jennifer Dodi from Blue Point, and today we will be discussing data. But first, just a few introductions. Returning from our first episode, we have Anne Marie Orlando, Keegan Smith, and Sarah Hobbs. And then joining us today also from Blue Point is Cody, who I will introduce himself and his title briefly before we get started.

SPEAKER_00 0:35

My name's Cody Charbonneau. I'm the senior manager of analytics for the Blue Point team. I've been with Blue Points and Yankee Alliance for 13 years now. So have a very good background and understanding of all the data processes that we do on a monthly basis and whatnot. So yeah, I love all things data. And uh here we are.

SPEAKER_02 1:05

Yep, that's why we have you with us today. You'll be answering all the questions I know I'm gonna have. Um and for our new listeners, uh, I'll have Anne-Marie give a brief description as well of Blue Point and what we are.

SPEAKER_01 1:19

Yeah, so Blue Point, we are a uh platform and we are a data intelligence platform, really, where we focus uh very clearly on clinical product utilization, you know, working with supply chain, working with clinicians in really aligning the products that our uh healthcare facilities are using. And are they adding value to the care of the patients or are they just adding cost to the hospitals? And um, how can we identify those opportunities and provide our customers the tools in which to uh get those savings by decreasing that spend?

SPEAKER_02 2:03

So Keegan, can you give us a little insight into how Blue Point uses data?

SPEAKER_03 2:08

Yeah, Blue Point uses data. Um we ask our customers to submit their PO data and uh issuance data where they can. So from there we look at categorizing their submitted data into our categories. Um, and we do that by product type and product detail, and uh then normalize it by their submitted statistics as well. Um, so this helps normalize the data and really give a true uh view on you know where they can then go after uh potential savings to become the top performer. Um, we have everything to a top performer top quartile for those targeted savings that we show in our platform. Um, so it helps give working with uh the customers data, it really helps give a visual understanding of the product mix that they have. Um, and then it helps also us tie that to the clinical best practice. So I'll let Cody go on uh more about the background and all the ins and outs that him and his team do. But that's how Blue Point really uses the data that we collect from our customers.

SPEAKER_02 3:31

Yeah, I think the data team is like the uh oz behind the curtains, right? What drives everything, but you don't get to see them very often.

SPEAKER_01 3:40

That's right, unless they're thrown into podcast meetings.

SPEAKER_00 3:46

Yeah, so I've always said, you know, the data is the you know the foundation to everything that we do. So if there's you know cracks, cracks in the data, you know, um uh inaccurate data uh classifications and whatnot, um, then it kind of you know affects everything that we do and you know affects the savings opportunity. So it's really, really important that you know initially we do get ensure that our um data files that we do collect from our facilities are accurate and meet all of our specific requirements. Um I can kind of just go through a high-level um high-level overview of of that process and why it's so important to um establish that initial data feed um with our facility. So um, as Keegan mentioned, we do collect um PO data data, and in some instances where we can uh we do collect issuance data. So um PEO data, you know, is kind of everyone kind of sends that just because it's you know readily available, um, and it gives us you know that high-level overview of what facilities are purchasing on a monthly basis. Um, where we do try to collect issuance data is when there's a lot of items that um go to inventory locations. So um the issuance data allows us to see down to the to the department level of um where those inventory items are getting used. So this is you know especially important when we're looking at you know utilization. So um we can see which down to the department which um which who's using you know um this many exam gloves versus um if we only use PO data, we would just see that it goes to inventory, so we can't really tell. Um so when we combine the PO and issuance, it gives us the full picture of of uh what the facility is doing. Um and it allows you know Amory and uh her team and and the facility to see you know deeper into into into what they're purchasing or what they're using, I should say. Um so um establishing that you know initial um data collection with the facility and ensuring those files are um set up for future submissions is especially important uh to ensure that everything going forward um remains accurate um and uh so that we can um move forward without any you know um any any uh inconsistencies and um inaccuracies. So um so once once that initial collection has been uh finalized and um ongoing it's just you know maintenance and uh monthly data collections, um, which are much smoother because um, like I said, the files have been um set up and uh finalized. So um from there, our team uh cleanses the data um on a monthly basis. We uh run the data through our matching process, which looks at you know lines of data every which way to ensure that we're capturing um new items that facility is purchasing, um, whether facility purchased from a new vendor, uh, we capture that as well. So we've we've really evolved over the course of you know 10 plus years um um in ensuring that you know we've tweaked our process along the way to ensure that you know we we do capture uh all those items and you know and make sure that you know items aren't being included that shouldn't be and whatnot. And um, you know, the whole team has been uh played a huge part in that in that in that role. Um so from there, um our team of analysts um reviews reviews the matching um results and uh the uh cleanse the data, um perform a lot of research on the items to ensure that um they belong in the category and whatnot. So um it's a lot of lot of uh a lot of lines to look at. You know, we can look at anywhere from a couple hundred thousand to a couple million, um, depending on the onboard of the facility. So it's uh you know, like I said, over the course of the years that we've become a lot more efficient in our process.

SPEAKER_01 8:18

So what I what I think is unique about it is that we are uh nimble enough to work with our customers on that data acquisition, where uh we've had customers and still do have customers who instead of using PO data want to use invoice data, right? Because there could be uh sometimes a difference, uh a variation there, right? Um in the other piece to that is that uh we have customers that sometimes will say, you know what, I may not want to look at my offsites. We have a lot of physician offices. And so Cody and his team are able to cut out those particular um sites so that maybe we don't want to see all those doctor offices or those ambulatory care centers or those urgent care centers that fall under that larger corporate umbrella. And then we have other facilities who say, I really want to know what my ambulatory surgery centers are are buying. So uh please include them. And so then we have others who want to see that that spend, and and we're able to uh provide that service depending on what they want to see in their tool, what kind of data they want to see. So um, and Cody and his team are really good at uh making sure that we're customizing that for them.

SPEAKER_02 9:46

Right, and working in making this data also presentable, you know, with the platform, because doing all this work behind the scenes, you know, we can then work with uh our customers to make sure that they're seeing only what they need to see or want to see.

SPEAKER_01 10:02

Exactly. Exactly. And and everyone's a little bit different, you know. Um their data feeds are can vary a little a little bit or sometimes a lot. And uh it's really nice to be able to say, yeah, we can do that. Yeah, you want to see you want to see it this way? Sure, sure, we we can we can work on that.

unknown 10:21

Yeah.

SPEAKER_02 10:22

And we're talking like value analysis teams, right? And supply chain teams like that that are okay. Um, but there's also um who else would benefit besides, you know, in the long run, the patient, from um seeing all this data. Um, I don't know if Sarah, your experience coming as the news member to Blue Point and coming straight from, you know, being you know, front and center on the floor as a nurse. Um, how how did you deal with data?

SPEAKER_04 10:52

You know, it's funny because you speak all different languages in in healthcare, right? And that the one commonality is that data. That data drives the healthcare, right? But we all totally use it differently. The nurse at the bedside, um, I would rely on real-time vitals, right? You're looking at vitals, labs, and all of that for all the individual patients. You're very rarely thinking about how much this four by four um dressing costs. Um, but you're not supposed to do that. That's why, that's why there's supply chain there to kind of help with that. Um, value analysis in the broader, so you have the nurse at the bedside, if you think of it in an ecosystem, right? You have the nurse at the bedside that's in the micro level, right? And then value analysis brings it out to let's say the mid-level of what we're looking at hospital-wide. Um, we're drawing that broader view, we're looking at the cost, at the product performance, at the outcomes, um, trying to balance that quality and the expense across the entire hospital. And then you add that with Blue Point, which is a completely different language, right? But it grows on a bigger ecosystem level, right, into like the macro of the entire system. Um, we're using all of that complex data that um that Cody and Keegan are pulling together and classifying for us and making it making it readable for the nurse at the bedside. Yeah. But then using that platform and spotting those trends and seeing those variations very quickly in the graphs and in the action plans that you can see, which then drives that strategic savings across the entire system. Um, so that's kind of like I see different languages, but you think of it in an ecosystem. So you have the micro level, the mid-level, and then that that macro level. Um, and so driving it through the entire system is really gives you that big picture of transformation.

SPEAKER_01 13:08

Yeah, I think I think it I I've seen, and I know probably many of you have seen that um that picture of the Legos where the bricks are all scattered everywhere, right? And that's like data. And then you take those bricks and you may organize them by color, but they're still in piles, right? And then you kind of stack them, right? So they look a little neater, and then all of a sudden you have this house, right? And and I think data is like that, right? Right, all those different pieces of data that are coming in, right? So whether it's uh invoice, it's PO, it's pricing, it's the department level data, it's the vendor they're purchasing from, it's the manufacturers they're using. And then on top of that, uh we add in that layer of uh product types and product details by really and really group them by clinical functionalities, quick clinical equivalents, and help tell that story, right? So help build that house so that someone without you know extensive data analytic skills, like that bedside nurse, can look at it and say, oh wow, that doesn't look right. That door is crooked, right? Or maybe I have too many doors to choose from, right? You know, and and you know, I think there's uh, you know, when we look at clinical product utilization, I think a lot of that, yes, it's standardizing to the manufacturer or you know, whatever, but it's beyond that. It's really that data helps us identify those items where we have overlapping and multiple clinical equivalents. It and so in a product type, is it you know feasible to have 20 or 85 choices of that same type of product, you know, and from an end user, I know uh walking into that room and trying to make those decisions of which one am I going to use, and then layer that with which one should I use for this patient? What does this patient have, or what does this patient need that this product can, you know, fit that need? And how do I make that decision quickly, efficiently, and not suffer from like a decision fatigue uh process, you know, um, or you know, have that those products be wasted or overused, underused. And uh, you know, so I I love that Lego story because it really, you know, it it really tells how uh you know the the the team can take that data and and make it understandable to everyone throughout the organization. Yes.

SPEAKER_04 15:52

It's the same data, it's just in a lot of different lenses, right? That's right.

SPEAKER_02 15:57

Yeah. And I think that's where Blue Point can really add value because we have taken it and organized it in such um uh unique way that you know makes it um that much more accessible and easy to understand.

SPEAKER_01 16:16

Exactly. And people are visual, you know. I think the platform adds that that piece to it where it's not just a you know an Excel spreadsheet. Yes, knowing the SKUs are important, right? You know, at the end of the day, if you're gonna work on the project, you need to understand the SKUs. Uh, you need to understand the research behind uh the decisions that you're going to be making, right? So if you're looking at IVs, what is some of the clinical guidelines I need to understand? Uh in and so that's all in the tool. But you know, what what really is uh helps us in that is the platform itself because it helps you visualize that data in a way that's again, it's so easy to see that wow, that's a standout. Wow, why is that different? Um, you know, and it's some you know so simple, but yet so impactful and powerful.

SPEAKER_02 17:08

Yeah. And for anyone who is listening and interested in seeing this platform, um, we will have links to our website in the description so you can go and sign up for a demo so we can go ahead and show you what we're all talking about. So that is definitely going to be in the description, depending on where you're listening or watching this podcast. Any final words about data that we want to share? Final words.

SPEAKER_01 17:34

Here's the thing. I think from an from a nursing, I'll say from a nursing perspective, I, you know, trans going from that bedside nurse into a value analysis role or a supply chain role, or you know, having anything to do with, you know, the the products, or I think there's a lack of comfort at times with manipulating data, table looking at tables, looking in and interpreting data. And for for you at the facility, if that is something that you identify that you have a shortfall on, I want to say don't hesitate to reach out to someone in your organization and say, you know what, can you help me understand how to how to make this better, right? Right? How to make this so I can understand it better more easily. Uh, you know, if if if it's Excel uh is your you know choice, right? I think a lot of people are are comfortable with that these days, but there are a lot of people who aren't. Um how can how can we, you know, outside of a platform like Blue Point, don't be afraid to uh go and get some education on that, right? There's a lot of classes, a lot of online tutorials. And I just have to say that from the nursing perspective, that sometimes we need to advocate for ourselves because we're put in some of these positions where suddenly we're in charge of this data set and it's how do we operationalize that? How do we interpret it? How do we know what to do with it? And you know, if you don't have a platform like Blue Point and you don't have the clinicians at Blue Point to help guide you and help kind of hand you that packet of what to do, um, you know, and you're on your own, you know, uh definitely reach out, you know, get a mentor, uh, you know, and and don't be afraid to ask questions. There will be someone in your facility. Uh, you know, most facilities do have analytics as uh, you know, someone who you could reach out to and say, hey, walk me through this, help me, help me understand this. Um, and so I that's all I wanted to say for the clinicians out there that if you know if you don't have a platform like this, you know, ask for help. And if you're if you're in charge of data and you need to interpret.

SPEAKER_02 19:56

So good point. Thank you, Emory. All right, well, I think that is a wrap on episode two, data. Uh, thank you for joining us today. Please like and subscribe wherever you're watching or listening to your favorite podcast so that you'll be informed the next time we have an episode air. Uh again, more information will be available in description to all our social media and website links. And lastly, remember best practice doesn't have to cost more when you slay your data with Blue Point. So until next time.

unknown 20:27

Bye.

SPEAKER_02 20:28

Bye.

SPEAKER_01 20:34

Uh and the cat buttons. So too, so it's like a curse.

SPEAKER_02 20:40

It's gonna follow all of us. Like someone I'll have to lock her in a room next time and down to lap.