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title: Can Oncology Workflows Run Without Human Touch? - Anant...
description: An AI engineer at Trisca describes how they automated oncology prior authorization workflows end-to-end using a multi-agent system. The pipeline uses four...
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# Can Oncology Workflows Run Without Human Touch? - Anant Shankhdhar, Risa Labs

**[AI Engineer](https://daily.dev/sources/aidotengineer)** · 16 min read · 0 upvotes · 0 comments

## Summary

An AI engineer at Trisca describes how they automated oncology prior authorization workflows end-to-end using a multi-agent system. The pipeline uses four agents: an eligibility verification agent, an authorization status agent, a medical necessity agent, and a submission agent. Key techniques include a unified payer integration service with LLM-driven config generation and self-healing RPA, multi-source evidence reconciliation to build confidence scores for drug authorization decisions, a payer rule knowledge base built from portal checks and LLM extraction, and a medical necessity agent that queries a patient biomarker graph to answer clinical questions with supporting evidence. Orders that pass all checks with sufficient confidence are submitted without any human review, while uncertain cases are escalated to clinicians.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=_cVfz88_j7A>

## Questions this post answers

### How can LLM agents be used to automate prior authorization workflows in healthcare without human review?

Four specialized agents handle the process: an eligibility verification agent checks insurance coverage, an auth agent determines whether a drug needs authorization, a medical necessity agent evaluates clinical justification against policy criteria and patient biomarkers, and a submission agent files the request. Deterministic checks and multi-source evidence reconciliation (authorization letters plus a payer rule knowledge base) allow confident cases to skip human review while low-confidence cases still escalate.

_daily.dev surfaces engineering writeups like this for teams designing agentic automation in regulated domains._

### Why can't LLM extraction alone eliminate human review in prior authorization automation?

LLM extraction from patient notes is inherently non-deterministic, so its outputs cannot be blindly trusted and still require human verification even if efficiency improves. Reliability only increased once a second independent evidence source, such as prior authorization letters and a payer rule knowledge base built from portal checks, was added so agreeing signals could raise confidence enough to skip human review.

_Developers weighing LLM reliability in automated pipelines can track patterns like this on daily.dev._

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---

Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#automation](https://daily.dev/tags/automation), [#robotics](https://daily.dev/tags/robotics), [#healthcare](https://daily.dev/tags/healthcare)

[View this post on daily.dev](https://daily.dev/posts/can-oncology-workflows-run-without-human-touch---anant-shankhdhar-risa-labs-x1aqjicvu)

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