Putting Real-Time Data Mastering in Practice

Businesses today operate in real time. But oftentimes, their data does not. Bogged down by disparate, siloed systems, businesses struggle to accurately identify, match, and link data across their systems, slowing down their ability to gain accurate, holistic insights that drive critical, customer decisions. 

Such was the case with CHG Healthcare. As the nation’s largest physician staffing company, CHG struggled to improve its data quality. Inconsistent data entry practices resulted in multiple records for the same provider, making it difficult to gain the insights required to meet the needs of their patients. New leads would come in, but the firm had no way of matching those records with existing golden records in real time. Not only did this further exacerbate the duplicate record issue, but it also put CHG at risk of burning out providers from over assigning them.

In partnership with Tamr, however, CHG Healthcare is now able to resolve provider records in real time, enabling them to keep their data clean and duplicate-free. Let’s take a look at their journey.

CHG Healthcare’s MDM Journey: From Duplicate Data to Real-Time Resolution 

CHG Healthcare is a force in the healthcare staffing industry. And they knew that the key to quickly and accurately matching skilled professionals with facility requests was clean, accurate, up-to-date data. However, for years, CHG Healthcare relied on rules-based processes to identify and remove duplicate physician records. This time-intensive process made it difficult to engage with leads quickly, manage physicians’ patient loads accurately, and ensure appropriate staffing levels during peak times.

CHG Healthcare recognized they had a data quality issue on their hands. And until they fixed their dirty, duplicate data, they wouldn't be able to properly operationalize it for use across the firm. They embarked on an MDM journey, with Tamr by their side. Their goal? To achieve a holistic, unified view of providers that would help them better address requests during peak times while also avoiding burnout from over-committing their providers.  

CHG’s journey began with their use of Tamr to support their batch pipeline. Their aim was to create a master list of providers and to prevent duplicates from entering the system, and so they employed Tamr’s low-latency APIs to conduct ad hoc lead searches. But many times, the “new” leads included records that match providers already captured in other systems across the firm. Tamr helped to deduplicate the data, however, without real-time data mastering, CHG Healthcare struggled to act swiftly and confidently on the incoming leads.

The firm wanted to evolve its processes so that they could deduplicate data at the point it enters the system – not via a batch process. That’s when they began to use Tamr RealTime. Now, CHG is employing Tamr’s “search before create” workflow. Using Tamr, they can identify duplicate leads while the data is still in motion, which prevents duplicate leads from entering the system altogether. And when the search reveals that the lead does not currently exist in the system, Tamr knows to create a new record. 

Today, the outcomes are clear. Using Tamr, CHG Healthcare reduced duplicate physician records by 48% and mastered millions of provider records in weeks, not months or years. Further, with Tamr’s real-time APIs, CHG can match new leads with existing entities and enrich them with any new information that’s available, instead of creating new, duplicate records every time. 

Putting Tamr RealTime into Practice 

Consider this example from the healthcare industry that is representative of a common challenge experienced when managing data across multiple systems. A nurse practitioner is looking for a job and applies to three different jobs at three different clinics in a single day. For a staffing agency receiving job applications from all three clinics as an inbound lead list, this nurse practitioner would be listed three times. And if that lead list were imported into the system of record as is, there would be three lead records created for the same person, polluting the system with duplicate data that is potentially inconsistent across all three records. 

Tamr RealTime, however, intelligently prevents those duplicates from being created. During the import of the lead list, Tamr RealTime checks to see if the nurse practitioner is already known in the system. If they are not, it creates a new record for them. If they are already present, then Tamr updates the existing information in the system, referencing information from the new job application. While this example is specific to the healthcare industry, this approach is applicable to use cases in many domains including finance, insurance, retail, and manufacturing.

5 Tips for Avoiding Duplicate Data Chaos

If your organization is struggling with duplicate data, here are five tips to help you calm the data chaos and achieve the complete, accurate, up-to-date data you need to drive better decisions.

1. Know where your data is coming from – and where it's going to. That way, you can determine what data actually needs to enter your systems of record – and which does not. 
2. Once you know which systems are involved, understand which fields and values need to be part of the golden record. Remember, not every field needs to be captured or shared within the golden record.
3. Get a handle on your master data before you implement real-time. Otherwise, you’ll just speed up the chaos by merging bad data.
4. Acknowledge that not everything requires real-time data mastering. By understanding what humans and machines will do with the data, you can assess where real-time makes sense – and where it’s not necessary.
5. Make use of external enrichment data. Many sources exist that can be used to improve the quality of data being used to power your business, but they often have biases towards specific regions or industries. To overcome this situation, consider taking a best-of-breed approach where data is aggregated across multiple providers. 

Ready to get started? Download our latest ebook, The MDM Journey: From Trusted Data to Operationalization.