For population health and clinical informatics.
IntelliNurse™ is clinical AI built for the way nurses actually reason. Reasoning runs over a longitudinal CommonWell-enriched patient record. Built for ACO, MA, and Medicaid managed care environments where care management capacity is the binding constraint on quality measures, MLR, and risk-adjusted outcomes. EHR integration via standard interoperability surfaces (FHIR R4, CommonWell, TEFCA). The full architecture is walked through in the briefing under NDA.
What your committee will want to see.
An integration surface that supports Epic, Oracle Health, and Meditech with FHIR-native read/write, plus CommonWell-mediated longitudinal data access for participating institutions. An audit log structure that traces every recommendation to its evidence source and the protocol that governs it. A validation methodology disclosed under NDA. A first-class deferral path when evidence is insufficient. Every substantive claim in the product is traceable. No black boxes. No "trust us." The architecture itself, the test-set construction approach, the threshold configuration, and the known failure modes are walked through in the briefing under NDA.
Where we scope inside the governance framework.
IntelliNurse™ is scoped as non-device clinical decision support under the FDA's January 2026 revised CDS guidance — not by interpretation, by design. The scoping analysis is available under NDA. State AI practice law alignment is built in, not retrofitted — California SB 1120 and AB 3030, Texas SB 1188 and HB 149, with configurability for state-by-state data residency and disclosure requirements. Alignment with the American Academy of Nursing's February 2026 position statement on AI, the Joint Commission/CHAI Responsible Use framework, and the ANA Code of Ethics is designed into the product, not bolted on as documentation.
What the technical brief covers.
The pre-read for population health and clinical informatics covers the architecture in the level of detail your engineering and architecture review needs, the integration surface at the API and workflow layer (FHIR R4, CommonWell, TEFCA), the validation methodology (blinded where NDA requires, disclosed where possible), the audit log schema, the deployment mechanics, and the known limitations. It is built to be pressure-tested, not to be pretty.