Powering a World-Class Clinician Experience with Real-Time Master Data
AMN Healthcare: Mastering Provider Data with Tamr’s AI-Native MDM Solution
Challenges
- Fragmented, duplicated clinician data disrupted the user experience
- Lack of real-time data access led to missed opportunities to match clinicians with open assignments
- Legacy rules-based MDM system generated about 1 million data conflicts or unresolved records that required manual review
- Data mastering workflows lacked real-world business user feedback, limiting accuracy and relevance of mastered data
- Decentralized data enrichment processes led to redundant purchases and unnecessary spending
Outcomes
- Reduced record mastering time from 1-to-2 hours to less than 30 seconds
- Enabled record loads of 1M+ in minutes (vs. 7-to-10 days with legacy solution)
- Improved clinician experience by reducing onboarding time from weeks to minutes
- Delivered fresh, accurate data to business user apps via real-time integrations
- Streamlined governance through easier, faster business reporting
AMN Healthcare’s master data management (MDM) transformation wasn’t just a system upgrade—it was a strategic shift. Their goal: to deliver a world-class experience for clinicians and place candidates in open roles faster than the competition.
But the existing data mastering solution couldn’t keep up. With data scattered across multiple source systems, the AMN team struggled with duplicate records and login issues in the AMN Passport app, an all-in-one platform that helps travel nurses and allied healthcare professionals streamline job searching, credentialing, assignment tracking, and communication.
The goal of this project was to create a world-class experience for clinicians and become their preferred staffing partner—not just to fix data in a vacuum.
Mark Hagan
The existing system lacked real-time capabilities and couldn’t keep up with AMN’s business demands. Mastering 1.5 million clinician records could take up to two weeks—far too slow for a business that relies on rapid clinician placement to drive revenue and user satisfaction. At the same time, clinician data was fragmented across multiple systems, making entity resolution—determining whether two records referred to the same person—difficult and error-prone. This confusion led to multiple logins in the Passport app, hurting adoption and reducing engagement.
AMN needed a faster, smarter, and more scalable solution. By switching to Tamr, the team replaced their slow, heavily manual mastering process with a proven AI-native MDM platform. Tasks that once took weeks now take minutes. Record mastering time dropped from 1-to-2 hours to just 20-to-30 seconds, and AMN can now process over 1 million records in minutes—compared to 7-to-10 days with their previous system.
Tamr has unified millions of clinician records, providing a single, trusted, real-time view of each clinician across all AMN platforms.
Speed to placement is everything. If we can match and onboard faster, we win—clinician satisfaction goes up, and the business sees results. With Tamr, we went from 7-to-10 days to just a couple of minutes for massive record loads.
Karthik Sambasivam
Governance was also reimagined. With the previous solution, publishing mastered data to Snowflake—a key step in making data available for reporting and analysis—could take 5-to-10 hours. With Tamr, it takes only 3 minutes. As a result, AMN can refresh its analytics dashboards daily, providing business users with automated insights into data quality issues and cluster inconsistencies, without requiring manual checks or interventions.
It gives us the ability to go back to the business with data in hand and say, ‘You don’t need to come to us—here’s the report, here’s the link, go clean it up.’ We’re not just nickel-and-diming teams—we’re giving them actionable insights they can act on every day.
Karthik Sambasivam
Another exciting improvement AMN is planning is to move feedback loops earlier in the process. With Tamr’s 360-degree clinician views, AMN will expose curated clinician profiles to business users sooner, creating a two-way feedback loop that helps catch errors earlier, improves data accuracy, and increases adoption of the system. It isn’t just about fixing data for AMN—it is about building trust.
Lastly, Tamr has transformed how AMN manages external data, greatly improving AMN’s ability to extract value from it. In the past, individual business units purchased third-party datasets—such as National Provider Identifiers (NPIs) and other provider data—on their own, leading to redundant spending and fragmented usage. With Tamr now serving as the central hub for clinician data, AMN has consolidated external data procurement, streamlining access and eliminating unnecessary costs.
Tamr’s enrichment capabilities have also enabled AMN to tap into Tamr’s extensive firmographic datasets, improving match accuracy and ensuring every healthcare organization record represents a real, verified entity. The project marked a shift for AMN’s central data team—from controlling access to data to enabling business units with accurate, trusted information to support their operations.
With Tamr, we became a data provider to our own organization. Instead of business units buying data from vendors, they now come to us. We give them the best version of the truth.
Mark Hagan
With a trusted, real-time view of clinician data, AMN is poised to continue driving greater operational efficiency, unlocking strategic insights, and further enhancing the clinician and business user experiences.
To learn more about how Tamr helps healthcare organizations master their data at scale, please read our ebook, Healthcare Provider Data Management: Tamr’s New Approach with AI-Native MDM.
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