Case Study: University of Utah Health Strengthens Referring Partner Relationships
Apr01

Case Study: University of Utah Health Strengthens Referring Partner Relationships

The costs of inaccurate provider data are significant to HIM departments but difficult to quantify, and often hospitals are unaware of their data’s poor quality. Records containing errors such as wrong phone number, missing information, outdated details, and duplicate records are just a few of the accuracy problems plaguing most systems.

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Five Ways Artificial Intelligence Is Transforming Healthcare Operations
Jan01

Five Ways Artificial Intelligence Is Transforming Healthcare Operations

While the practical applications of artificial intelligence (AI) are still being discovered, one area of AI — natural language processing (NLP) — is already helping advance the revenue cycle. Discover how the right NLP can support accuracy, efficiency and revenue integrity by powering comprehensive clinical documentation improvement and coding earlier in the process.

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Case Study: The Patient Matching Challenge
Nov01

Case Study: The Patient Matching Challenge

With numerous health systems experiencing mergers and acquisitions, interoperability and health information management have presented a significant barrier toward optimal care delivery and improved patient outcomes. The integrity of patient data can be threatened when patient records converged from different electronic health record (EHR) systems can’t be correctly matched and linked.

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White Paper: Improving Patient Matching with a Simple Plug-in
Sep18

White Paper: Improving Patient Matching with a Simple Plug-in

There are substantial—and growing—costs to inaccurate patient matching. Learn how a groundbreaking solution can improve match rates, thereby improving healthcare data exchange.

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