What Is Data Enrichment?
Behind the Scenes of ProviderTrust’s Proprietary Exclusion Monitoring Strategy
Though automation has made exclusion monitoring a much easier process, not all automated solutions deliver the same quality of results. Many solutions on the market return “potential matches” that require a client to sort through incomplete or missing data to piece together what their results mean.
At ProviderTrust, uncertainty isn’t an option.
Our clients deserve timely, accurate results that eliminate the noise, allowing them to focus on what truly matters.
Enter data enrichment, the advanced data strategy we’ve spent over 15 years refining. Data enrichment enables us to identify exclusions that other automated solutions miss, delivering exact-match results you can trust with no manual intervention needed.
Our clients deserve timely, accurate results that eliminate the noise, allowing them to focus on what truly matters.
Enter data enrichment, the advanced data strategy we’ve spent over 15 years refining. Data enrichment enables us to identify exclusions that other automated solutions miss, delivering exact-match results you can trust with no manual intervention needed.
The Problem at Hand
In a perfect world, the federal and state exclusion lists would contain a standard set of complete data that makes it clear which individual or entity is excluded (and why).
In reality, there are about 50 federal and state primary sources that contain data for more than 280,000 total exclusions, and they all have varying levels of data completeness. An exclusion record for an individual on a state list often looks very different from the record contained on a federal list—yet the penalties for working with this individual are the same across the board.
The comparison chart above, based on a real example, highlights an all-too-common problem: a lack of unique identifiers that can confirm the excluded individual’s identity. It can take hours of digging to confirm whether you’re employing the same John Brown, RN, who’s been excluded in Alabama or another RN in Alabama who happens to be named John Brown.
Did you know?
On average, it takes about 420 days for a state exclusion to reach the OIG LEIE. Currently, 58% of state exclusions (more than 51,000) are not listed on the OIG LEIE. While not all state exclusions should be included on the OIG LEIE, it’s important to monitor every available exclusion list to ensure you’re seeing the complete picture.
Did you know?
On average, it takes about 420 days for a state exclusion to reach the OIG LEIE. Currently, 58% of state exclusions (more than 51,000) are not listed on the OIG LEIE. While not all state exclusions should be included on the OIG LEIE, it’s important to monitor every available exclusion list to ensure you’re seeing the complete picture.
Did you know?
On average, it takes about 420 days for a state exclusion to reach the OIG LEIE. Currently, 58% of state exclusions (more than 51,000) are not listed on the OIG LEIE. While not all state exclusions should be included on the OIG LEIE, it’s important to monitor every available exclusion list to ensure you’re seeing the complete picture.
How Data Enrichment Closes the Loop
Our data enrichment strategy was born out of a need to bridge the gaps and inconsistencies among the various exclusion lists. We can’t control how disjointed the primary sources are, but we can control how we verify and store the data they give us.
Think of exclusion monitoring as a puzzle. Each primary source provides a few pieces of the puzzle, but they still have to be assembled to give a complete picture—and sometimes pieces are missing.
To complete the puzzle, we’ve aggregated all the data points contained in different primary sources to create a centralized, verified profile for each excluded individual and entity. This process, called data enrichment, makes ProviderTrust’s data set even more accurate than the primary source—because it includes verified unique data points from each primary source, rather than just one.
Because the primary sources aren’t perfect, we also add multiple levels of internal verification by ProviderTrust’s data oversight team before enriching a piece of data. Two data experts review each piece of new data, and if they disagree on the validity of the data, we escalate it for further analysis using public records and sources such as NPPES, Nursys, and others.
Over the course of 15 years, we’ve enriched more than 91% of all exclusions that exist today, which allows for faster, more precise identification when there’s a match in a client’s population and quick resolution for those “potential matches” other solutions pass on to their clients. This process not only ensures the accuracy of our results—it also requires many, many hours of expert manual research that other solutions either charge extra for or simply leave to their clients to solve.
Total exclusions across all federal and state lists
State exclusions not listed on OIG LEIE
Data points we've enriched
Exclusions we've enriched with SSNs
Exclusions we've enriched with NPIs
Exclusions we've identified
*data as of December 2025
What Data Enrichment Means for ProviderTrust Clients
When it comes to exclusion monitoring, you want to know that your results are trustworthy. Data enrichment takes the guesswork out of exclusion monitoring, giving ProviderTrust clients peace of mind and eliminating the need for manual work.
Our data enrichment strategy is so powerful that 46% of the 52,783 exclusions we’ve identified over the past 15 years could only be found using enriched data—meaning other exclusion monitoring solutions would have missed them completely.
This record gives us a complete look at the excluded individual or entity, removing “potential matches” from your plate and ensuring you never have to wonder if your results are accurate. To learn more about how ProviderTrust can improve your exclusion monitoring processes, get in touch with us today.
Learn more about ProviderTrust's exclusion monitoring solution.
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Learn more about ProviderTrust's exclusion monitoring solution.
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