Generative artificial intelligence has the potential to be a helpful tool for healthcare organizations, especially when it comes to increasing efficiency in clinical and operational settings. However, many generative AI tools out there lack transparency regarding the data sets they’re trained on, which could lead to biases.
As the industry moves toward adoption and expanded generative AI use cases, organizations must be prepared to implement governance and processes created with all stakeholders at the table.
During June’s AWS Summit in Washington, D.C., AI and population health experts discussed the benefits of generative AI tools as well as the guardrails needed to ensure these models don’t harm patients or communities.
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Ways Healthcare Can Benefit from Generative AI
There are several ways healthcare organizations can benefit from generative AI tools. Ambient listening can generate clinical notes based on conversations between physicians and their patients. Monica Coley, senior business development manager at Amazon Web Services, said that generative AI-powered chatbots can help handle the volume of calls coming into contact centers. These chatbots can help some patients with their concerns when appropriate, with no human interaction required.
Additionally, some agencies and departments in the federal government are still using data on paper locked in filing cabinets, according to Dawn Heisey-Grove, senior federal public health account manager at AWS. She said that using AI services can speed up the process of digitizing those files while a human verifies accuracy.
Another example of how AI tools can help healthcare organizations is by reformatting data or research to be compliant with specific standards. Heisey-Grove points out that the organization may store data one way but need to share research with another entity in a different way for grant approval. She said that AI paired with human validation can accelerate the process of reformatting that data.
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