AI Data Abstraction

Evidence-linked registry answers from notes, documents, and EHR data.

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Clinical sources

CTA head and neck

Radiology - 07:39

Imaging impression confirms right M1 occlusion and supports EVT pathway review.

stroke

CTA

Medication administration

MAR - 08:49

TNK administration record includes dose, order time, and bolus timestamp for registry fields.

stroke

TNK

Angio procedure report

Neuro IR - 10:25

Procedure details provide groin puncture, first pass device time, and final reperfusion.

stroke

EVT

Nursing flow sheet

Vitals - ED stay

Timestamped vitals and transfer events help validate door-to-CT and handoff measures.

stroke

timeline

Registry rule packet

GWTG-Stroke - PSC

Measure dependencies and validation rules keep generated answers aligned with submission logic.

stroke

rules

Chart review

4-6 hrs

saved per patient chart review

Sources

Any EHR

FHIR, notes, PDFs, labs, documents

Review model

Human-in-loop

AI drafts, reviewers verify

Workflow

Built around the way clinical quality teams work

Connect source systems

Ingest FHIR resources, clinical documents, registry exports, and uploaded evidence without forcing teams into a single EHR pattern.

Build evidence packets

Curate relevant snippets, source locations, timestamps, and registry criteria before asking AI to produce an answer.

Pre-fill registry measures

Populate row-native measures with answer values, confidence, status, and direct evidence links reviewers can inspect.

Validate and submit

Reviewers verify, edit, ask AI follow-up questions, and export clean evidence-backed cases for registry submission.

Capabilities

Production workflows, not one-off automation

Evidence-linked answers

Every abstracted field carries the clinical source behind it, so teams can defend the answer during audit or survey review.

Registry-aware workflows

Measures, dependencies, repeaters, and case status are modeled around clinical registry logic instead of generic form filling.

Reviewer-first controls

Quality teams can verify, edit, restore, remove, and add rows while preserving a clear source trail.

Change-aware recompute

When source facts change, Evida can target affected cases and measures without overwriting accepted human work.

Outcomes

Better data, better quality operations

Faster abstraction

Less manual chart chasing

Audit-ready answers

Cleaner source traceability

More validation, less search

Lower reviewer burden