Transforming Clinical Intelligence
Icon’s Clinical Healthcare Intelligence solution empowers healthcare organizations to unlock the full value of unstructured clinical data with Snowflake Intelligence. It transforms physician notes, patient summaries, and outcome documentation into governed, explainable intelligence within Snowflake. Researchers and clinicians can ask natural language questions and receive cited, contextual answers in seconds. The result is accelerated discovery, improved outcomes, and secure, enterprise-scale adoption of advanced analytics.
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Countless Opportunities to extract value from unstructured data
ONCOLOGY
A health system wants to understand why
patients discontinue first-line therapy early.
Clinical Reality
-
Oncologists document why chemo or
immunotherapy is stopped in progress notes -
Structured data only shows that it stopped — not why
What’s Possible
-
Surface discontinuation drivers across
thousands of notes -
Combine with regimen, stage, and
outcomes data -
No manual chart review
TREATMENT DISCONTINUATION & SWITCHING
CARDIOLOGY
A hospital wants to reduce 30-day
heart failure readmissions.
​
Clinical Reality
-
Readmission drivers are often social
or behavioral -
These are documented in discharge
summaries, not codes
What’s Possible
-
Extract patterns not visible in claims or labs
-
Link narrative context to readmission events​
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DOSE ESCALATION & OPTIMIZATION
BEHAVIORAL HEALTH
A payer wants to understand why members
stop antidepressants or antipsychotics.
​
Clinical Reality
-
Psych side effects are inconsistently coded
-
Clinicians describe them in free text
What’s Possible
-
Identify side effects without relying
on ICD codes -
Connects symptoms to adherence patterns
​​
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MEDICATION SIDE EFFECTS &
NON-ADHERENCE
SURGERY
A surgical department wants earlier
detection of post-op complications.
​
Clinical Reality
-
Early complications show up in nursing notes and progress notes
-
Coding happens later (or not at all)
What’s Possible
-
Detect emerging issues days earlier
-
Enable near real-time monitoring
​​
POST-OP COMPLICATIONS DETECTION
EMERGENCY MEDICINE
A health system wants to identify drivers
of frequent ED visits.
​
Clinical Reality
-
ED notes explain why patients return
repeatedly -
Social determinants dominate
What’s Possible
-
Identify patterns across visits and facilities
-
Inform intervention strategies
FREQUENT ED UTILIZERS
PHARMACY &
MEDICATION SAFETY
A pharma or health system wants to
understand real-world off-label usage.
​
Clinical Reality
-
Off-label use is documented narratively
-
Structured fields don’t capture intent
What’s Possible
-
Extract intent and rationale
-
Support governance and auditability
OFF-LABEL USE DETECTION
CARE TRANSITIONS
A hospital wants to identify patients at
risk due to poor discharge planning.
​
Clinical Reality
-
Discharge summaries contain
inconsistencies -
Follow-up plans live in text
What’s Possible
-
Flag risky patterns
-
Enable targeted interventions
DISCHARGE SUMMARY GAPS
CLINICAL RESEARCH
A research team wants to identify
eligible patients faster.
​
Clinical Reality
-
Trial eligibility criteria are text-based
-
Screening is manual and slow
What’s Possible
-
Automate pre-screening
-
Reduce chart review time dramatically
ELIGIBILITY SCREENING
GLP-1 THERAPY SWITCHING
A payer or health system wants to under
stand why patients switch between GLP
1 therapies during treatment, to improve
outcomes & formulary decisions.
Clinical Reality
-
Off-label use is documented narratively
-
Structured fields don’t capture intent
What’s Possible
-
Extract intent and rationale
-
Support governance and auditability
DOSE ESCALATION & OPTIMIZATION