Evidence surfaced
AI identifies clinical evidence
Relevant evidence is identified within unstructured clinical documentation.
The Healthcare Challenge
Clinical evidence exists inside the notes.
Manual review does not scale.
The symptoms, treatment history, risks, and patient context needed to identify a treatment opportunity are often documented in narrative form. Finding that evidence still depends on someone opening and reading charts one by one.
Unstructured
Evidence is buried in documentation
Critical clinical context lives across long narrative evaluations, progress notes, and treatment histories.
At scale
Teams cannot read every chart
Manual review consumes clinical time and becomes impossible to sustain across thousands of patient records.
The result
Appropriate opportunities remain hidden
Patients may wait longer for review because the documented evidence is difficult to find, organize, and act on consistently.
How OutcomesAI Works
AI extracts evidence. Rules enforce safety.
Clinicians decide.
OutcomesAI separates AI-powered evidence extraction from deterministic clinical rules and safety checks, creating a transparent review workflow for the care team.
- 01
AI identifies clinical evidence
AI reviews unstructured clinical documentation and identifies evidence relevant to a defined care pathway.
- 02
Structured findings are created
Relevant symptoms, treatment history, risks, and supporting note excerpts become reviewable findings.
- 03
Deterministic rules evaluate criteria
Transparent, pathway-specific rules evaluate the structured evidence rather than asking AI to make the decision.
- 04
Safety checks are applied
Governed controls flag exclusions, contraindications, and evidence gaps before an opportunity reaches the team.
- 05
Clinicians review and act
Care teams verify the source evidence, apply clinical judgment, and decide the appropriate next step.
Clinical Transformation
From scattered documentation
to a governed clinical workflow.
OutcomesAI is designed to help clinical teams identify relevant evidence, review treatment opportunities, and prioritize follow-up without replacing clinical judgment.
Traceable findings
Source evidence stays connected
Each structured finding remains connected to the supporting source documentation.
Defined logic
Rules evaluate clinical criteria
Deterministic clinical logic and safety checks operate separately from AI extraction.
Human oversight
Clinicians make the decision
Care teams review the evidence, consider the full record, and determine the appropriate next step.
More than 6,000
new-patient evaluations a year across 12 offices
65 → 88
of every 100 strongest TMS candidates reached treatment
+23 more patients per 100. With OutcomesAI live, 88 out of every 100 reached treatment, most within 30 days.
10 → 7 days
strongest-tier median wait
slowest tenth of strongest candidates: 54 → 23 days. third-tier wait: 51 → 28 days.
98.4%
valid on the first pass
2,990 records from a six-month period not used to build the vocabulary.
Responsible AI
Transparent decision support.
Clinical judgment stays human.
The platform is designed to reduce the burden of finding and organizing evidence without replacing professional judgment.
Traceable
Evidence traceability
Each finding connects back to the supporting clinical documentation so reviewers can verify why it was surfaced.
Human-led
Clinical oversight
The system prepares evidence for review while clinicians retain authority over treatment decisions and patient care.
Bounded
Deterministic safety controls
Explicit clinical rules and safety checks remain separate from AI evidence extraction and can be reviewed and governed.
Decision support
No autonomous treatment decisions
OutcomesAI supports clinical workflows; it does not diagnose, prescribe, or initiate treatment on its own.
Clinical Proof
TMS: the initial clinical application of the Clinical Opportunity Intelligence platform.
OutcomesAI first applied its evidence extraction, deterministic rules, safety controls, and clinician review workflow to identify appropriate TMS opportunities from psychiatric documentation.
TMS validates the platform’s clinical method; it does not define the limits of the platform. The same governed architecture can support additional care pathways with pathway-specific evidence and criteria.
Security & Governance
Secure, bounded, and auditable by design.
OutcomesAI protects patient data, constrains AI to evidence extraction, keeps deterministic safety controls reviewable, and preserves an auditable connection between each finding and its source.
Explore security and governance →
See Clinical Opportunity Intelligence
in your workflow.
Explore how OutcomesAI can turn the clinical documentation you already have into transparent, evidence-backed treatment opportunities.