End-to-End Validation Report
Automated testing on Raspberry Pi 5 · 2026-03-02
6 test suites · 13 patient scenarios · CIRS v3.26
13 patient scenarios from registration to transfusion to station evacuation
72-hour network blackout simulation — offline queues, LoRa, DR backup/restore
Consignment goods from vendor to surgical consumption to cloud reconciliation
Reconnected stations auto-reconcile — zero manual data cleanup needed
Replace destroyed hardware, restore full operations within minutes
When stations consolidate under crisis, every record transfers intact
This report covers six test suites with 595 automated steps, validating that xGrid maintains complete data continuity — patient identity, blood traceability, surgery handoff, inventory and financial accuracy — through station evacuation, 72-hour network blackout, supply chain reconciliation, sync resilience, disaster recovery, and station merge. All on a single offline Raspberry Pi.
Why This Matters
In disaster or conflict — earthquake, typhoon, battlefield — the first thing that fails is not supplies. It's information continuity. Patient records, blood traceability, and medication chains break down when stations evacuate, merge, or lose connectivity.
What's at stake:
- Wrong blood given to a patient — loss of chain-of-custody
- Surgery handoff undocumented — critical context lost between teams
- Inventory mismatch after station merge — supplies unaccounted for
- Triage records lost during evacuation — patients become unknowns
xGrid keeps staff working and data intact — even when stations evacuate, patients transfer, and surgery must resume elsewhere. All on a credit-card-sized Raspberry Pi, fully offline. Nurses operate from their phones.
Every claim below is backed by automated test steps. 428 steps, 3 test suites, open methodology.
When Everything Goes Wrong, Care Continues
3 of 8 stations forced to evacuate mid-operation. Active blood transfusions, an ongoing surgery, critical medications in transit. The question isn't whether to keep going — it's whether the system lets you.
At that moment:
- 3 patients receiving blood transfusions — bags must transfer safely and be re-verified at the new station
- A surgery in progress — must be interrupted, patient transferred via EMT, then resumed at a new station
- All medications and equipment must be reallocated instantly across remaining stations
The real questions:
- Does the patient's identity and medical history follow them?
- Is every blood bag accounted for — from origin to transfusion?
- Can the surgeon resume exactly where they left off?
- Is every transfer, every decision, every handoff documented — automatically?
The Answer: Yes, All of It
- Patient identity preserved across station transfer
- Blood chain-of-custody maintained — re-crossmatched and verified
- Surgery resumed at new station with complete ISBAR handoff
- Inventory reconciled across all merged stations
- 34 steps, 34 passed, zero data loss
13 Patient Scenarios
Internal Medicine Outpatient
Complete clinic visit from registration to billing
Can a standard outpatient visit run entirely offline?
Orthopedic Surgery
Surgery cycle including anesthesia, blood transfusion, and billing
Can blood be safely transfused during emergency surgery without losing chain of custody?
Multi-Station Logistics
Inventory transfers and pharmacy dispensing across 3 stations
When supplies move between stations, does inventory stay accurate?
Echelon Evacuation
ISBAR handoff from field to hospital with triage and transport
When a patient is evacuated to a higher echelon, does the handoff record survive?
Anesthesia Deep Dive
Full anesthesia lifecycle: induction through PACU discharge
Does the anesthesia record remain complete from induction through discharge?
Mass Casualty (MCI)
20 casualties triaged and registered in under 3 seconds
When 20 casualties arrive simultaneously, can the system keep up with triage?
Blood Bank Stress
10 concurrent crossmatch and transfusion cycles
Can 10 crossmatch-and-transfusion cycles run concurrently without conflict?
Full-Day Operations
Morning shift to night shift handoff with 50+ patients
Does the system maintain integrity across a full day of shift changes?
Concurrent Stress Test
4 parallel write-heavy workflows under maximum station load
When multiple stations hammer the database simultaneously, does data remain consistent?
Station Emergency Consolidation
3 stations evacuated mid-operation, patients and supplies transferred
When 3 stations must shut down mid-operation, can staff keep working and data stay intact?
LSCO Battlefield Medicine
Full LSCO lifecycle: PFC care plan, TCCC card, MEDEVAC request, DCS surgery, Walking Blood Bank, permissions mode switching
Can battlefield medicine workflows — from field care to evacuation — run entirely on a single offline Raspberry Pi?
Station Management
Station registry, inter-station transfers, failover and consolidation operations
Can multi-station operations — transfer, failover, and consolidation — be orchestrated reliably?
Combat Casualty Chain
Single patient through TCCC card, PFC care plan, MEDEVAC request, and DCS surgery with cross-module verification
When a combat casualty moves through the full LSCO pipeline, does data link correctly across all modules?
xGrid 72H Survival Test
Simulating 72 hours of complete network isolation — 6 phases, 353 steps
Phase 1: Calm → Storm
Normal operations to network failure. SSE reconnection, PWA offline queues activate, LoRa bridge simulation, Dock Sync status.
When the network drops, can all PWA workstations seamlessly switch to offline mode?
Phase 2: Storm
Prolonged isolation. Safety-II break-glass authorization, SYNC conflict detection, MIRS DR backup/restore.
After 24+ hours of total isolation, can the system maintain operations and handle authorization exceptions?
Phase 3: Catastrophe
Dual RPi survival validation. Device failover, extreme failure paths.
When the primary RPi fails, can the backup RPi take over with complete data integrity?
Phase 4: Merge Storm
Consolidation + conflict resolution across Alpha/Beta stations.
T+36h → T+48h — Alpha decommissioned, patients merged to Beta with full conflict detection and resolution
Phase 5: Degraded Ops
Single-station survival under resource constraints.
T+48h → T+60h — Beta operates alone with depleted supplies, equipment failures, and emergency protocols
Phase 6: Endurance
Final accountability and 72-hour validation.
T+60h → T+72h — PFC alerts, equipment cycling, supply chain collapse/recovery, and full reconciliation audit
Supply Chain Reconciliation
Full consignment chain verification — from vendor to surgical consumption to cloud
Complete consignment lifecycle: vendor shipment → RPi local receiving → surgical consumption → offline queue sync to cloud → financial reconciliation ¥91,600. 28 steps, all passed.
Scenario-to-Risk Mapping
How each test scenario addresses real operational risks
| Concern | Risk | Evidence |
|---|---|---|
| Blood traceability | Wrong blood given or chain-of-custody lost | Patient B, I: transfer + re-crossmatch |
| Surgery interruption | Undocumented interruption or handoff failure | Patient I: ISBAR → EMT → resume |
| Multi-site inventory | Stock mismatch across merged stations | Patient C, H + 370/s benchmark |
| Mass casualty intake | Triage overwhelmed by surge | MCI: 200 in 21s on RPi 5 |
| Offline continuity | Internet/power loss halts operations | All 428 steps on RPi, no internet |
| Supply chain accounting | Consignment consumption untracked, financial mismatch | Supply chain: 28 steps, ¥91,600 verified |
Hardware Performance
Tested on a single Raspberry Pi 5 (8GB, $80 USD)
One Raspberry Pi 5 processes every operation faster than a human can initiate it.
Write Performance
| Operation | Throughput | Latency |
|---|---|---|
| Patient Registration | 58.5/s | 17ms |
| Inventory Receive | 244/s | 4ms |
| Inter-Station Transfer | 370/s | 3ms |
| Full Anesthesia Cycle | 37.5/s | 27ms |
| Cross-System Round Trip | 14.8/s | 68ms |
Even at 20 simultaneous stations, the system responds in under 1 second with zero errors.
Concurrent Station Load
| Stations | Throughput | P95 Latency | Errors |
|---|---|---|---|
| 5 | 59/s | 92ms | 0 |
| 10 | 56/s | 318ms | 0 |
| 15 | 56/s | 578ms | 0 |
| 20 | 55/s | 641ms | 0 |
Even at 20 simultaneous stations, throughput drops only 7% with zero errors
Mass casualty documentation capacity exceeds realistic arrival rates by orders of magnitude.
Mass Casualty Capacity
200 casualties registered in ~21 seconds
Real MCI arrival rate: 30-60 minutes
System uses ~1% of capacity
Benchmark Methodology
All benchmarks run on Raspberry Pi 5 (8GB RAM, Debian Bookworm). SQLite WAL mode, single-process Python ASGI. Sequential tests: 100 operations, average of 3 runs. Concurrent tests: asyncio tasks per station count, 50 operations each. No network overhead — localhost only. Measured with Python time.perf_counter().
A single Raspberry Pi serves 15-20 workstations, handles 500+ patients/day, zero errors. In the field, the computer is never the bottleneck — people are.
Rapid Iteration
From 10 gaps to zero in 48 hours
LSCO Readiness
8 battlefield medicine modules — all validated on Raspberry Pi
Validated
Scope & Limitations
- •Engineering validation in a defined simulated environment, not a clinical outcomes study.
- •Results bounded by the specific hardware, software version, and deployment configuration.
- •De Novo xGrid is not a medical device. Not cleared by any regulatory agency.
- •Detailed technical appendix available upon request.
Interested in deploying xGrid for your medical unit?
Definitions
- PASS
- — Step executed and assertion verified successfully
- FAIL
- — Step executed but assertion failed
- GAP
- — Step not yet implemented (API exists, test missing)
- SKIP
- — Step intentionally excluded (e.g., FHIR export — not in scope)