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SMARTIdentify: Identify Guideline-Eligible Patients from Unstructured EHR Data

Patient records should clarify care, not distort visibility.

When key clinical criteria live in narrative documentation, eligible patients remain invisible. SMARTIdentify surfaces guideline-qualified patients directly from unstructured EHR text, with verifiable evidence clinicians can trust.

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Benefits

SMARTIdentify helps you:

Improve Clinical Quality

Make patients who meet guideline criteria visible with evidence clinicians can verify.

Increase Operational Clarity

Reduce manual chart review and fragmented interpretation.

Support Service Line Growth

Surface patients who are clinically appropriate but not consistently identified.

Protect Reimbursement Integrity

Support auditable, guideline-based identification and review.

Eligible patients are already within your system

Eligibility Is Not the Same as Visibility.

Patients meet criteria every day, but without visibility, they’re never identified.

Multimorbidity is now the norm, and rare conditions are more common than assumed. With more than 7,000 rare diseases (over 10,000 including cancers), 1 in 10 Americans are affected, yet diagnosis still takes an average of five years and multiple specialists.

Echo reports. Progress notes. Imaging narratives. Discharge summaries.
The signals are there, just not connected.

When they remain buried:

    • Guideline-ready patients are never evaluated
    • Readmission risk is underestimated
    • Quality performance underrepresents clinical reality
    • Service line opportunity goes unrealised

Fragmentation doesn’t just slow workflows, it delays diagnosis and obscures the full patient picture.

*Healthcare Informatics Research (2019)

of diagnostic insight lives in unstructured clinical documentation.*
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Explainable AI for patient identification

Built for Clinical Accountability.

SMARTIdentify goes beyond data extraction. It identifies patients who meet established clinical guidelines, and shows exactly why.

Built on a clinician-led model design and grounded in guideline-defined variables, it sits alongside care teams with real world clinical validation. Every identification is transparent, explainable, and designed for clinical review, not automation.

No autonomous decision-making. No opaque scoring logic. Just clear, defensible insight clinicians can trust.

It is governed patient identification at infrastructure scale, powered by DARWEN™ AI.

  • Every flagged patient includes: 

  • The source sentence 

  • The clinical variable extracted 

  • The guideline criteria met 

  • The context required for review 

    • From data to patient identification

    From Clinical Narrative to Actionable Identification.

    Ingest

    Structured and unstructured EHR data

    Interpret

    Clinically validated variables using the DARWEN™ AI engine

    Surface

    Patients who meet guideline criteria, with supporting evidence attached.

    Verify

    A verifiable patient list, not a probability score, with the evidence required for review, validation, and documented decision-making.

    Ingest

    Structured and unstructured EHR and other system data.

    Interpret

    Clinically validated variables using the DARWEN™ AI engine.

    Surface

    Patients who meet guideline criteria, with supporting evidence attached.

    Verify

    Evidence required for review, validation, and documented decision-making.

    Real World Results

    Demonstrated in High-Impact Service Lines.

    In a 1,000-bed hospital in Atlanta, SMARTIdentify analyzed 15,467 echocardiograms and extracted 36 complex clinical variables, surfacing 200 previously unrecognized valve replacement candidates.

    These patients were clinically eligible, but operationally invisible.

    In cardiology, this translates into:

    • Improved adherence to guideline-directed therapy
    • Reduced avoidable deterioration
    • Stabilized service line performance

    While U.S. deployment is most active in cardiology, the underlying methodology has been validated across oncology, gastroenterology, dermatology, ophthalmology, rare disease, and mental health.

    externally validated

    Built on Clinical Research. Proven in Practice.

    Powered by DARWEN™ AI, developed over 9 years of clinical research and validated across more than 50 peer-reviewed medical publications.

    SMARTIdentify is designed to withstand clinical scrutiny, governance review, and operational validation, not just pilot demonstrations.

    For organizations seeking broader data foundation support, SMARTIdentify can operate independently or as part of the Amadeus AI infrastructure.

    Explore the Amadeus AI infrastructure
    Interested in learning more?

    Identify What Your Structured Fields Miss.

    Bring a real clinical question. See how SMARTIdentify surfaces the patients your documentation already contains. 

    Find out more
    Reimagine the healthcare experience for all