SKCoreHealth Technologies
AI that suggests, never decides — with a complete audit trail and human in the loop, always.
The responsible AI framework woven through every SKCore product — advisory-only architecture, PHI de-identification, per-hospital configuration, bias monitoring, and a full audit log of every AI suggestion made, accepted, or modified.
No AI output is ever written to the clinical record without explicit human approval. Every AI suggestion is presented as a draft for clinician review.
All patient data is de-identified using NLP and rule-based stripping before any call to an external LLM. Re-identification risk assessment built in.
Every AI suggestion logged — prompt context, model used, output, clinician action (accept/modify/reject), and timestamp.
Each hospital can independently enable or disable AI features per product, per role, and per workflow. API key managed securely in admin console.
Continuous demographic and clinical bias monitoring across all AI outputs — flagging if suggestions diverge by patient age, gender, or comorbidity.
Intelligent model routing — complex clinical reasoning uses high-capability models, documentation uses efficient models, reducing cost without sacrificing quality.
161 specialized AI agents across 15 departments. Department-level token budget controls. Full agent audit trail.
Ongoing research in genomics, population health, federated learning, and ambient clinical intelligence — all governed by advisory-only principles.
AI Governance itself uses AI to monitor AI outputs — detecting bias, drift, and quality degradation across all SKCore products.
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