Hospital CIOs: The Importance of Enrichment in Enterprise Data Strategy

Hospital CIOs: The Importance of Enrichment in Enterprise Data Strategy

Today, we’re starting a four-part blog series on the importance of data enrichment. We all regularly hear that data is the future – that Big Data and enterprise analytics will transform the industry. This isn’t the whole story, however. Simply obtaining enterprise data analytics isn’t enough. To succeed with data, healthcare systems need the right data paired with the right strategic enterprise data strategy. They need quality, rich data that’s both actionable and accurate.

In this first installment in the series, we’re sharing insights from Nic Sagez, Curvo’s Chief Technology Officer. Nic is instrumental here at Curvo Labs in product development and in helping tailor software and data for the needs of enterprise customers. He’s the perfect person to explain why merely having data isn’t enough and why data enrichment is critical to long-term success.

Here’s what Nic has to say to CIOs about the importance of data enrichment in healthcare:

Why do data enrichments matter for large hospital systems?

One of the biggest challenges we at Curvo see today in healthcare spend data is that the data is, for lack of a better term, messy. Large hospital systems are collecting tons of data, but much of the time, no one can quite tell what the data actually represents. Messy data is better than no data, but it doesn’t produce concrete, actionable results for the decision makers who need them.

CIOs, supply chain professionals, and surgeons alike all need to be able to make sense of clinical data. When the data is messy, they can’t.

This is where thoughtful data enrichment comes into play. Without it, CIOs and others can’t navigate clinical data in the ways they need to. Thoughtful enrichment from Curvo connects the data in meaningful ways and adds categorizations to further make sense of it.

To give one example, because Curvo contains Orthopedic Network News categorizations, we can start with a particular part and identify which procedure or procedures it is used in. This enables surgeons and supply chain professionals to quickly compare various procedure and part costs. It would be nearly impossible without data enrichments.

How are hospitals doing this today (without Curvo)?

To be blunt, some hospitals just aren’t enriching their clinical data. They’re doing the best they can with the lacking data they have, but it’s a real missed opportunity. Some are manually looking up entries on the FDA website, but this is, of course, a massive time expense. And when you have 10,000 lines of spend or more, it’s beyond tedious. For this reason, it’s scarcely done on a wide scale.

Another option is trying to group entries by vendors, but even this requires at least one dedicated resource just to manage this catalog. Finding the needed expertise and justifying the headcount is problematic, so, once again, this often doesn’t happen.

How does this manual work affect the quality of analysis (and business as a whole)?

First, it’s a lot harder to connect with the data and convert numbers into real-world meanings. Clinical data enrichments reveal the soul of what’s behind the numbers. Where they are even bothering to work with the data, they must spend all their resources painstakingly and manually analyzing data. That’s time they could be spending achieving a wide range of business goals.

One of the points of enrichment that Curvo provides is quality benchmark information. This is another great area of weakness for many hospital systems: they simply do not have access to quality benchmark information. Whatever they manage to glean through their highly manual data analysis process can’t be leveraged against benchmark data without some kind of outside partnership.

But with Curvo, benchmark data is a part of the clinical data enrichment that data subscription customers receive.

Without Curvo, what are hospitals relying on for benchmarking data? Why is this a problem?

ECRI is one source for benchmarking data, and some hospitals receive benchmark information from competitors. Hospitals may also be attempting to do manual benchmarking. The problem, of course, is that all these methods are intensely time-consuming, as is normalizing the data they produce. While hospitals may have significant amounts of data, they often struggle to make sense of it and garner practical insights to help them make decisions. Despite the labor and resource requirements, the quality doesn’t compare to what Curvo can provide.

What problems do hospitals encounter when doing their own categorization and normalization?

What Curvo hears consistently is that doing so is really difficult as there’s a lot of noise in the data. When manually entering data into a system, there are many open fields. There may be spelling variances in part names, manufacturer or vendor names, or abbreviations, and more. Sometimes, part numbers themselves aren’t consistent between facilities.

It’s very challenging to say with confidence that apples are being compared to apples.

How do Curvo’s data enrichment customers describe the value of this service?

Curvo’s data enrichment service has normalized data for numerous large health systems. Within a particular system, Curvo normalizes all hospitals so that each member of the system is speaking the same language and has the right data analytics in place.

Curvo empowers these customers to better address contract negotiations with vendors as well. With rich, clean data, they can speak from a place of knowledge in those negotiations. Customers have also gained insights into practice patterns, case constructs, and procedures that can lead to cost savings initiatives.

Why is clinical data collected by most large hospital systems so messy?

There are two primary reasons clinical data comes in so messy:

First, in most cases, the data entry fields are freeform, meaning they don’t lock inputs into a particular format. Different people accessing the system, then, may input the same item number in slightly different ways. Nothing in the software limits how this is done, and, most of the time, no one is checking this data as it goes in. There may also be duplicates in the master catalog. In this case, users have to choose between entries that seem nearly identical. Of course, the people doing the data entry don’t choose correctly every time, leading to messy data. And all of this is within an individual hospital. The complexity (and the mess) grows when you add in multiple hospitals that make up a large hospital system.

Second, across a large hospital system, there are often multiple competing data collection systems. Normalizing the data across these systems is challenging, and internal teams often encounter problems doing so.

Is there anything that hospitals can do to clean up the data coming in?

There are many processes a hospital system can enable internally to clean up clinical data, but they all come at a resource cost:

  • Managing the item master and keeping it up to date
  • Training the internal resources to enter things consistently
  • Hardening the data entry process in the software so it doesn’t accept variations (however, this will slow your people down as they now must find the “one right way” before they can move on)

To get better enterprise data analytics, you must reduce user error (or even user variation). And, while challenging, it’s not impossible to do this with your internal resources.

The problem most hospital systems encounter is a resource constraint. They don’t have the resources they need to manage these efforts, so the data remains messy.

Can you describe in greater detail how Curvo’s data enrichment services improve enterprise data strategy?

First off, let’s go back to that “local noise” mentioned earlier where duplicates in the master catalog and variations in data entry fields complicate matters. Curvo’s data enrichment services get rid of that noise. This allows your team to aggregate information for any given part across a given facility or an entire system. Knowing hospital system-wide the exact quantities of a particular part you’re purchasing is powerful leverage in vendor negotiations.

Identifying price abnormalities is another benefit Curvo provides for enterprise systems. It’s not unusual for individual hospitals within a large system to pay varying prices for the exact same part. With Curvo’s data enrichment services, you’re able to view pricing for a part across all your hospitals, which further strengthens negotiating power.

Data-as-a-Service with Curvo

The benefits of a data enrichment services subscription (otherwise known as data-as-a-service) are numerous. With Curvo enriching your enterprise data analytics, your health system can finally truly take control of its data, leading to powerful insights, better negotiations, and significant cost savings opportunities.

If you’re ready to learn more, let’s schedule a demo today.