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Cognizant Releases Healthcare LLM Suite Built on Google

IT services firm Cognizant has expanded its healthcare solution portfolio with four new AI large language models (LLMs) aimed at streamlining administrative processes.

The company tapped into Google's AI technologies, including the Vertex AI platform and the Gemini models, to form the backbone of its new healthcare LLMs, which are designed to "help reduce administrative burden, and streamline manual tasks," according to Amy Waldron, director of Healthcare and Life Sciences Industry at Google Cloud.

The new LLMs "addresses four high-cost workflows," Cognizant said in its announcement earlier this month. They are as follows:

  • Appeals Resolution: This LLM automates manual and error-prone tasks related to medical appeals, including data retrieval and analysis. Its aim is to make medical appeals processing more accurate and streamlined.
  • Contract Management: This LLM aims to reduce incidences of human error and inconsistencies around contract lifecycle management. It automates contract reviews, generations and configurations, potentially saving time.
  • Marketing Content Generator: As the description suggests, this LLM is designed for marketing teams looking to automate their content creation processes.
  • Health Plan Shopping: This LLM is designed to help individuals choose a health plan based on preferences, health profiles and other data.

The healthcare industry has a complex view of generative AI. Many see AI as potentially being more trouble than it's worth, but others welcome the help to reduce staff burnout, which is endemic in healthcare.

"The solutions Cognizant and Google Cloud developed to address the challenges imposed by healthcare administrative workflows could have a significant impact on both operational cost profile as well as consumer experiences," said Rohan Kulkarni, executive research leader at HFS. "These are outcomes anyone would welcome."

About the Author

Gladys Rama (@GladysRama3) is the editorial director of Converge360.

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