Clinical Temporal Decision Engine

FHIR-native temporal risk scoring, care-gap detection, shadow analytics, and MCP-compatible orchestration. A deterministic engine with full audit trail — every output is traceable to input data and guideline version.

Overview

The Clinical Temporal Decision Engine processes FHIR bundles against published clinical guidelines to produce reproducible risk scores and auditable care-gap outputs. It is a deterministic engine — every output is traceable to input data and guideline version. AI and MCP layers provide orchestration and navigation, not clinical reasoning.

Temporal Event Ingestion

Accepts FHIR R4 bundles via REST API. Processes Observations, Conditions, Medications, and Patient resources. Temporal ordering preserves clinical context. Supports batch and incremental ingestion modes.

Deterministic Normalization

Maps heterogeneous FHIR data into a canonical clinical data model. Versioned terminology mappings. Quality gates validate completeness and consistency before the pipeline proceeds.

Quality Gates

Pre-execution validation of input completeness, terminology conformance, and temporal consistency. Configurable per-guideline thresholds. Failed gates produce structured error reports, not silent degradation.

Care Gap Detection

Evaluates patient timelines against published clinical guidelines. Identifies missed screenings, overdue monitoring, and guideline deviations. Outputs are guideline-versioned and timestamped for audit.

Temporal Risk Scoring

Deterministic risk scores computed from patient timeline and guideline rules. Every score is reproducible — same input + same guideline version = same score. Full provenance chain recorded.

Shadow Analytics

Run guideline evaluations against historical data or hypothetical scenarios without affecting production records. Useful for population health analysis, guideline impact assessment, and what-if modeling.

MCP-Compatible Orchestration

Pipeline tools and FAQ knowledge base are exposed via Model Context Protocol (MCP) for integration with agent frameworks. Deterministic search and tool execution — not generative chat or LLM reasoning.

PHI-Safe Telemetry

Infrastructure and pipeline metadata only in logs and monitoring. Patient-level data never enters telemetry streams. Azure Monitor, App Insights, and Log Analytics configured with PHI-aware boundaries.

Azure-Ready Deployment

Deployed on Azure App Service with custom domain, HTTPS/SNI SSL, and Managed Identity. Key Vault references for secrets. Cosmos DB for structured data. Event Hubs for pipeline events. GitHub Actions OIDC for CI/CD.

Not a Replacement for Clinical Judgment

The Clinical Temporal Decision Engine is a decision support tool. It provides structured, auditable outputs to assist clinical and operational review. It is not a replacement for qualified clinical judgment. All outputs should be reviewed by licensed healthcare professionals before any clinical or operational action.

This system does not:

  • Diagnose medical conditions
  • Recommend treatments or medications
  • Prescribe interventions or dosages
  • Predict individual patient outcomes as medical advice
  • Replace clinical guidelines or institutional protocols
  • Substitute for regulatory compliance review

Demonstrations use synthetic data only. No real patient data is used in development, testing, or demonstration.

Not a medical device. Does not diagnose, treat, or prescribe. Outputs are clinical decision support, not medical advice.

Not HIPAA, FDA, SOC2, or ISO certified. Compliance program is planned.