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Using AI to break down the challenges of clinical documentation

Published on 2/24/2020

Estimated read time: 1 minute

Tech solutions designed to make records more accurate can help eliminate some of the challenges associated with clinical documentation, including miscommunication between physicians, coders and clinical documentation specialists. Giving physicians dynamic, real-time documentation support can reduce inaccuracies and the need for coding specialists to clarify diagnoses with physicians or to capture information that wasn’t logged the first time.

However, simply outfitting a health system’s electronic health record with AI tools isn’t enough to ensure that clinical documentation improvement (CDI) programs achieve organizational goals. The technology must be applied in a way that takes into consideration the concerns of the people using the solutions.

In a recent interview with Becker’s Healthcare, Dr. Tanuj Gupta, vice president of Cerner Intelligence, and Beth McCauley, lead clinical terminologist at Cerner, shared six principles of using technology to support clinically driven CDI:

  1. Avoid black box solutions
  2. Ensure decisions are made by clinicians
  3. Use AI solutions for CDI that support clinical validation
  4. Integrate solutions in a way that reduces the cognitive burden
  5. Balance standardization with customization
  6. Test run in “silent mode.”

To learn more about these six tenants and to read all of Tanuj’s and Beth’s comments, download the Becker’s Healthcare and Cerner whitepaper, The 6 principles of AI-assisted clinical documentation improvement.

Visit the Cerner booth (2941) at HIMSS20 March 9-13 in Orlando, Florida to learn more about our AI and CDI solutions.