Workflow · healthcare · workflow
Aetion uses Amazon Bedrock to translate natural language scientific intent into patient variable measures
Scientists, epidemiologists, and biostatisticians had to manually translate complex natural language scientific intent into algorithmic patient variable definitions (Measures), a process requiring specialized training and days of effort.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User submits natural language query
When a user asks a question through the assistant UI, Substantiate initiates a request containing the question and previous message history.
Tools used
Amazon BedrockClaude 3 HaikuKubernetes on AWSmxbai-embed-large-v1
Outcome
Measures Assistant enables users to convert natural language scientific questions into AEP Measures in minutes rather than days, without requiring support staff or specialized training.
Results
Time savedminutes as opposed to days
Grounding & classification
Source type: technical build writeup
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