Patient 360 Platform Planned and Designed in Under One Week
A stalled greenfield Patient 360 program fast-tracked from months of planning uncertainty to a funded, execution-ready program with complete target-state data models, ETL scripts, and project plans through AI-powered forward engineering.
Key Metrics
5 Days - Strategy to Execution-Ready
48 - Source Feeds Analyzed
50+ - KPIs Mapped
Funded - Sponsors Approved in Days
THE CHALLENGE
A US healthcare business unit needed to build a Patient 360 analytics platform from scratch, consolidating patient data from 48 distinct source feeds spanning APIs, flat files, and database objects. They had the source data specifications in hand but lacked the architectural direction, target-state data models, ETL logic, project structure, and defensible artifacts needed to get sponsors and leadership to fund the program. Traditional consulting estimates for this planning phase ranged from 8 to 14 weeks.
PAIN POINTS
✖ No target-state architecture defining data layers, ingestion patterns, or serving layer design
✖ No Patient 360 data models for patient, encounter, clinical, claims, and operational entities
✖ No ETL or transformation logic showing how 48 heterogeneous source feeds would flow into target layers
✖ No development roadmap, effort estimates, or work breakdown structure for sponsor approval
✖ No clarity on team composition, hiring priorities, or technical skill requirements
✖ Traditional consulting engagement would take 8–14 weeks before any development could begin
THE SOLUTION
3X Data Engineering's Forward Engineering Accelerator processed all 48 source data feed specifications, business objectives, and KPI requirements through graph-based intelligence and deep data architecture domain knowledge. In under one week, it delivered a comprehensive Forward Engineering Canvas including target-state data layer designs, Patient 360 data models, ETL scripts for all feeds, a phased roadmap, fact-based effort estimates, a detailed project plan with WBS, team skill matrix, governance frameworks, and developer standards.
SOLUTION HIGHLIGHTS
✓ Automated source data intelligence processing all 48 input feeds at the attribute level across APIs, flat files, and database objects
✓ Target-state data layer architecture with raw, curated, conformed, and serving layers designed for Microsoft Fabric
✓ Patient 360 conceptual and logical data models with entity relationships, grain definitions, and SCD strategies
✓ ETL script generation for all 48 source feeds covering ingestion, transformation, and standardization patterns
✓ Business objective and KPI alignment mapping 50+ KPIs back to source feeds with gap identification
✓ Complete project plan with WBS, phased roadmap, gate criteria, effort estimates, team skill matrix, and developer standards
SAMPLE OUTPUT: GENERATED PATIENT 360 DATA MODEL
Core Entity Relationships (AI-generated from 48 source feeds)
| Entity | Grain | Key Relationships | SCD Strategy |
|---|---|---|---|
| Patient Master | 1 row / patient | Encounter, Claims, Provider | Type 2 |
| Encounter | 1 row / visit | Patient, Provider, Facility | Type 1 |
| Clinical Events | 1 row / event | Encounter, Patient | Append-only |
| Claims | 1 row / claim | Patient, Provider, Facility | Type 2 |
| Provider | 1 row / provider | Facility, Encounter | Type 2 |
Target Data Layer Architecture
| Layer | Description |
|---|---|
| Raw Landing | As-is ingestion from 48 feeds |
| Curated | Standardized, deduplicated, typed |
| Conformed | Patient 360 unified view |
| Serving | KPI-ready, 50+ metrics |
RESULTS
DELIVERY TIMELINE
DAYS 1–2: Ingest & Analyze: 48 source feeds processed at attribute level, business objectives mapped, architecture initiated
DAYS 3–4: Design & Estimate: Architecture, roadmap, ETL scripts, effort estimates, and project plan generated
DAY 5: Deliver & Enable: Full Canvas handover, skill matrix, governance, knowledge transfer session
ACCELERATORS USED
3X Forward Engineer: Greenfield architecture, data models, ETL generation
3X Metadata Intelligence: Source feed analysis and domain classification