SCRIMED Atlas Intelligence Core v1
A continuously validated healthcare intelligence operating system.
Faith-neutral, compliance-centered operating model for governance, trust, ROI, interoperability, and agentic workflows. Atlas now exposes document intelligence, evidence-backed reasoning, Trust Cards, sandbox runtime, validation metrics, AI governance, and reimbursement readiness while live clinical execution remains gated.
Enterprise boundary
Enterprise Atlas surfaces must remain procurement-ready, compliance-focused, and institutionally neutral.
SCRIMED Atlas Intelligence Core v1 is a synthetic pilot and enterprise assessment operating layer. Medical-record, claims, payer, wearable, and telehealth workflows remain gated until tenant approval, BAA readiness, live connector controls, durable audit, and human review are approved.
Structural Intelligence Engine
Parse layout before LLM extraction across healthcare documents.
forms
Parse layout, labels, tables, and visual grouping before LLM extraction.
- field grouping
- checkbox state
- signature blocks
- required field detection
tables
Preserve table structure and source cell references before summarization.
- row-column mapping
- merged cells
- header inference
- numeric unit detection
contracts
Extract clauses with page/section source references and governance review status.
- section hierarchy
- defined terms
- obligations
- dates
- exceptions
referrals
Structure referral context into review queues with missing-information detection.
- referral source
- requested specialty
- missing attachments
- routing cues
claims
Structure claims context into denial-risk and reviewer queues.
- claim lines
- denial codes
- payer reason text
- supporting documentation references
prior-authorizations
Map prior authorization packets to policy evidence, missing support, and reviewer checkpoints.
- payer policy fields
- requested service
- evidence checklist
- authorization status
medical-records
Medical-record parsing requires approved tenant controls and must preserve provenance before LLM extraction.
- note sections
- medication tables
- lab tables
- problem list structure
- source provenance
Atlas Evidence Layer
Answers require citations, confidence, source attribution, and validation timestamps.
answer
Short operational answer or recommendation framed for human review.
citations
Source IDs, titles, URLs, and relevant evidence snippets or section references.
confidenceScore
Numerical confidence score with explanation of uncertainty and missing evidence.
sourceAttribution
Named source owner, version, validation timestamp, and scope boundary.
validationTimestamp
Timestamp for when source freshness and TrustQA checks were last evaluated.
humanReviewRequirement
Reviewer role and checkpoint required before any external, clinical, payer, or patient-facing action.
Operating subsystems
Atlas combines document intelligence, evidence, governance, reimbursement awareness, and validation.
Structural Intelligence Engine
Document layout understanding before LLM extraction across forms, tables, contracts, referrals, claims, prior authorizations, and gated medical records.
- layout-first parsing
- source provenance
- field-level review
- no live PHI in synthetic pilots
Atlas Evidence Layer
Evidence retrieval from guidelines, protocols, publications, policies, standards, and buyer knowledge sources.
- citations
- confidence score
- source attribution
- validation timestamp
Trust Card System
Attach provenance, confidence, source version, validation state, and human-review requirement to recommendations.
- source IDs
- confidence
- guideline version
- last updated
- review gate
Agent Sandbox Runtime
Isolated agent environments with memory, files, tools, audit logs, and workflow-specific boundaries.
- per-task sandbox
- scoped memory
- tool allowlist
- audit log
- blocked live execution
Continuous Validation Engine
Measure workflow outcomes instead of generic benchmark scores.
- denial reduction
- time saved
- revenue impact
- escalation rate
- override rate
- trust metrics
Governance Layer
AI Asset Registry, shadow AI detection, model/prompt/source inventory, connector tracking, and audit trails.
- asset registry
- shadow AI signals
- complete audit trail
- exception review
Reimbursement Layer
CMS ACCESS-aware chronic care monitoring, telehealth, wearable integration, and outcome reporting readiness.
- policy evidence
- reviewer approval
- consent model
- no reimbursement guarantee
Reimbursement Layer
CMS ACCESS-aware posture for chronic care monitoring, telehealth, wearables, and outcomes.
This layer supports readiness and reporting design; it does not guarantee reimbursement or perform billing actions.
ACCESS-aligned chronic care monitoring readiness
care-plan adherence, remote monitoring review, escalation queue, outcome reporting
- CMS program policy
- tenant clinical protocol
- reviewer disposition
- patient consent model
Telehealth workflow intelligence
visit modality, follow-up need, access bottleneck, documentation completeness
- tenant telehealth protocol
- state/regional policy review
- documentation policy
Wearable integration planning
device signal availability, review thresholds, escalation policy, outcome trend
- device data agreement
- consent model
- clinical protocol
- alert fatigue policy
Outcome reporting layer
time saved, denial risk surfaced, access bottleneck, override rate, trust completeness
- baseline method
- buyer-approved metric definitions
- audit trace
- validation timestamp