High-quality data enables medical research


Electronic health records (EHRs) have become ubiquitous, but the data they contain is often inconsistent and incomplete. And when one considers that by some estimates, one-third of all data generated in the world is related to healthcare, shouldn’t that aggregated information be preserved and prepared to be as useful as possible?

However, in order for this vast amount of information to reach its full potential – supporting clinical purposes or enabling groundbreaking research – the raw EHR data requires tools designed for data standardization and cleanup.

Read our latest white paper, produced in association with MIT Technology Review Insights, to learn about overcoming the challenges to creating high quality clinical data with the goal of improving patient care.

Key learnings

  • Understand the limitations of EHRs due to poor data quality resulting from inconsistent data entry and loss of essential detail.
  • Discover the potential of electronic health records (EHRs) in the U.S. to provide valuable real-world data about millions of patients.
  • Learn about tools designed to standardize and clean up EHR data, enabling its usability for various purposes, supporting clinical applications, and facilitating groundbreaking research.

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