SAE Narrative Auto-Coding Assistant
Converts narrative safety text into structured coding candidates for faster clinical safety workflows Evidence basis: Trial-focused NLP studies showed automated coding of adverse event narratives is feasible and can outperform baseline approaches; pharmacovigilance coding studies show throughput gains while still requiring human QC
The Problem
“SAE Narrative Auto-Coding Assistant”
Organizations face these key challenges:
Converts narrative safety text into structured coding candidates for faster clinical safety workflows
Impact When Solved
The Shift
Human Does
- •Read SAE narratives and identify relevant safety terms
- •Assign structured coding manually using standard checklists
- •Coordinate case updates in spreadsheets and review logs
- •Perform retrospective quality checks and resolve discrepancies
Automation
Human Does
- •Review suggested coding candidates and make final coding decisions
- •Approve exceptions, ambiguous cases, and unresolved discrepancies
- •Apply documented review procedures and quality oversight
AI Handles
- •Convert narrative safety text into structured coding candidates
- •Standardize inputs with guided data capture and controlled selections
- •Flag incomplete, inconsistent, or uncertain narratives for human review
- •Prioritize cases for faster review based on likely coding relevance
Operating Intelligence
How SAE Narrative Auto-Coding Assistant runs once it is live
AI runs the first three steps autonomously.
Humans own every decision.
The system gets smarter each cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Assemble Context
Step 2
Analyze
Step 3
Recommend
Step 4
Human Decision
Step 5
Execute
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.
The Loop
6 steps
Assemble Context
Combine the relevant records, signals, and constraints.
Analyze
Evaluate options, risk, and likely outcomes.
Recommend
Present a ranked recommendation with supporting rationale.
Human Decision
A human accepts, edits, or rejects the recommendation.
Authority gates · 1
The system is not allowed to finalize SAE narrative coding without review and approval by a clinical safety coder [S1].
Why this step is human
The decision carries real-world consequences that require professional judgment and accountability.
Execute
Carry out the approved action in the operating workflow.
Feedback
Outcome data improves future recommendations.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in SAE Narrative Auto-Coding Assistant implementations: