Odesso CDC II Clinical Evidence Intelligence

Health plans and value-based care networks have sophisticated claims, risk adjustment, quality analytics and interoperability infrastructure. Yet a critical source of clinical truth remains largely inaccessible: evidence buried in scanned PDFs, outside records, faxes, specialist notes, imaging reports and longitudinal EHR narratives.

A completed mammogram may exist only in an external report. An HbA1c result may be present in a scanned lab. A suspected chronic condition may appear across multiple encounters but require additional clinical validation before it is reportable. When these facts are absent from structured feeds, quality gaps remain open, risk opportunities go unrecognized, and teams repeatedly retrieve and review the same charts.

The challenge is clinical, not merely technical. A keyword or OCR result cannot establish that an HEDIS measure is met, that a condition is currently supported for risk adjustment, or that evidence belongs to the right patient and measurement period. Doing so requires longitudinal reconciliation, measure-specific clinical logic, documentation sufficiency checks and traceability to the original source.

Existing payer data platforms can identify opportunities; they cannot operationalize evidence that is missing, unvalidated or trapped in provider workflows. Odesso addresses this last-mile gap: converting unstructured evidence into defensible risk and quality intelligence, then making it actionable within existing systems—without introducing another provider portal.

Odesso CDC is a production-deployed clinical evidence intelligence layer. NOT generic OCR, a standalone HCC model, or another analytics dashboard. It combines specialized clinical AI, longitudinal chart reconciliation, configurable risk/quality rules, source-level traceability and native EHR workflow integration.

1. CLINICAL EVIDENCE RECOVERY: Interprets image-based PDFs, faxes, external labs, specialist notes and imaging reports; identifies clinical concepts, dates, results, negation and context; and links each finding to its source.

2. HCC RISK SUSPECTING: Cross-references structured and unstructured history to surface candidate ICD-10/HCC conditions with supporting documentation and MEAT-oriented review cues. Clinicians and authorized coding teams retain responsibility for reportable diagnoses.

3. HEDIS / STARS ABSTRACTION: Evaluates evidence for breast and colorectal cancer screening, HbA1c, blood-pressure control and configurable measures, including relevant dates, values and measure-specific criteria. Distinguishes documented completion from a genuine outstanding care gap.

4. LONGITUDINAL RECONCILIATION: Matches external evidence to the correct patient, checks existing chart values, reduces duplicates and connects new findings with known clinical history.

5. EVIDENCE-TO-ACTION DELIVERY: Provides prospective pre-visit opportunities, retrospective review outputs and authorized, API-based updates to native EHR workflows where supported—rather than requiring another provider-facing application.

6. APPIAN ORCHESTRATION: Appian coordinates work queues, exception routing and operational oversight; Odesso provides the clinical interpretation, evidence models and EHR integration layer.

Proven at enterprise scale across millions of clinical pages, Odesso complements existing payer risk, quality and data platforms by recovering and operationalizing evidence they cannot use from structured feeds alone.