This post is co-written with Vijay Venkatesh, CTO at Bluesight.
If you build software for hospitals, you know that compliance work scales poorly. Hospitals managing 340B Drug Pricing Program compliance face a compounding data problem. Proving that a Group Purchasing Organization (GPO) purchased drug qualifies for an exception requires cross-referencing each purchase against several sources at once. These include Food and Drug Administration (FDA) shortage lists, American Society of Health-System Pharmacists (ASHP) data, days-on-hand inventory, machine learning (ML) based shortage predictions, and backorder signals from hundreds of other hospitals. For a single covered entity, this manual audit process consumes over 4,000 hours annually. Multiply that across a network of over 620 hospitals, and the scale of the problem becomes clear.
This is a companion discussion topic for the original entry at https://aws.amazon.com/blogs/machine-learning/building-an-agentic-ai-solution-at-bluesight-with-amazon-bedrock/