One of the themes that emerged from the webinar on The Power of Orthopedic Data Enrichments in Driving Value and Perspective is the value of construct data. Below you’ll find several relevant webinar highlights.
Understanding Construct Data Is Key to Achieving Price Parity
One of the biggest reasons that construct data carries significant value in orthopedics is that it helps hospitals achieve price parity. At the risk of stating the obvious, you cannot achieve price parity until you identify that you don’t have it.
By having and understanding construct data, your healthcare system will be capable of noting price disparities between identical or very similar constructs within the same procedure type. Without clinical data enrichments in your construct data, you likely don’t have a true understanding of the constructs and components you’re using.
If you’ve ever seen a purchase order that simply said, “Dr. Smith’s hip,” you know what we’re referencing. Many procedures simply don’t have the data associated with them that you need to make smart decisions.
But once you gain this data enrichment, you can begin to identify those price disparities and work to resolve them.
Similarly, understanding construct data is the key to better negotiations with vendors. They, too, have construct data, and they generally aren’t expecting you to have data that’s as good or better than theirs. Because of this knowledge gap, vendors tend to feel fairly secure, like they have the upper hand. Once they begin seeing that you have comparable (or even better) construct data, they tend to become much more willing to negotiate.
Construct Data Fuels Better Conversations with Physicians
When you have quality construct data, you can have better conversations with physicians about all sorts of aspects of procedures and procedure costs. With weak, surface-level data, it’s challenging to talk about specific cases or procedures in a way where you and the surgeon can be sure you’re both thinking about the same case.
But with construct data all the way down to individual components, you’re in a position to ask very specific questions. When you can identify not just general cost overages but specific wasted components or targeted overages, your surgeon is much more likely to remember the specific instance. The surgeon may remember, for example, the one instance where a nurse dropped a component (necessitating using an additional one), or where something broke during the procedure.
But without good enough construct data to jog the surgeon’s memory about an unusual situation, it’s far less likely you’ll get the information you need.
Construct- or Component-Level Pricing: Which Is Better?
There’s some debate among supply chain professionals about which way of tracking pricing is more useful: at the construct level or the component level. We’re making the case in this article that construct-level data is quite important, especially in orthopedics, but this can be at least a little bit confusing on the surface.
If you’ve read our blog regularly, you’ve even seen us make the opposite point. We’ve argued elsewhere that construct-level data isn’t sufficient, and that you need a data partner that can dive down to the component level to get you the best insights.
You may even be wondering about this from your own experience. Perhaps you were focused in the past on general construct pricing data and have already made the transition – through the help of Curvo or another data partner – to evaluating component-level pricing. Are we taking a step backward by focusing once again on construct-level data?
No, we’re not. And here’s the reason: it’s not an either-or conversation; it’s both-and.
The kind of construct data that we’ve lobbied against in the past is general, messy, and even incomplete construct data. It’s construct data without component-level pricing. The kind of construct data we’re talking about here is construct data that’s infused with component-level data.
Looking at the data in terms of constructs tends to be a very effective method, but it’s only effective when the data is well supported by component-level pricing.
In other words, for many healthcare organizations, construct-level data is the better approach – but only when you can break that construct down into its component parts when needed. If you don’t collect that underlying data, you’ll quickly find your construct pricing creeping, and you won’t know why. Component prices will be creeping up, or add-ons will be sneaking in – and you won’t have an effective method for finding them.
Watch the Webinar to Learn More About Construct Data
We’ve just scratched the surface on the importance of construct data in orthopedics here. And today’s topic is just one small element of the broader discussion of the ways that orthopedic data enrichments can empower your healthcare organization.
For more on this crucial topic, watch the entire webinar, The Power of Orthopedic Data Enrichments in Driving Value and Perspective, featuring Kelley Young along with Curvo’s own Jake Titzer and Stan Mendenhall of Orthopedic Network News.