🏥 Ukrainian Healthcare System: Current Medical Imaging Practices
Key Insight: Ukraine’s two-level electronic healthcare system (EHS), with 36 million registered patients and 1.6 billion electronic medical records, provides a unique foundation for AI integration—despite wartime challenges reducing viable MIS providers from 40 to just 4-6.
1. Historical Context: From Soviet Legacy to Digital Transformation
Ukraine inherited a declining Soviet healthcare system after independence in 1991. Despite constitutional promises of universal, free healthcare, the system remained:
- Underfunded — chronic budget shortfalls
- Bureaucratic — political connections over clinical need
- Cash-driven — “care for cash” as the norm
By 2014, significant reform began. In 2017, the National Health Service of Ukraine (NHSU) was initiated as a single-payer system, with the electronic healthcare system (EHS) mandated as the sole platform for all medical service providers.
2. Ukraine’s Two-Level Digital Healthcare Architecture
┌─────────────────────────────────────────────────────────────┐
│ CENTRAL DATABASE │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ 36M Patients│ │1.6B Records │ │400K Users │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
│ Processing: 1000-1500 requests/second │
└────────────────────────┬────────────────────────────────────┘
│ API
┌──────────────┼──────────────┐
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│ MIS #1 │ │ MIS #2 │ │ MIS #N │
│ (Local) │ │ (Local) │ │ (Local) │
└──────────┘ └──────────┘ └──────────┘
│ │ │
┌────┴────┐ ┌────┴────┐ ┌────┴────┐
│Hospital │ │Clinic │ │Imaging │
│ A │ │ B │ │Center C │
└─────────┘ └─────────┘ └─────────┘
Figure 1: Ukraine’s Two-Level Electronic Healthcare System Architecture
Key Features:
- Central Component: National data repository with unified registries
- Local MIS: 40+ medical information systems (pre-war) developed by IT companies
- Interoperability: All MIS transfer data in same format to central database
- Flexibility: Local systems can create unique functions for regional needs
3. Medical Imaging Equipment: The Current Gap
📊 EU Comparison (2022 Data):
| Country | CT Scanners per 100K | MRI Units per 100K |
|---|---|---|
| Greece (highest) | 4.9 | 3.7 |
| Germany | 3.5+ | 3.0+ |
| EU Average | ~2.8 | ~1.8 |
| Hungary (lowest) | 1.1 | <1.0 |
| Ukraine (estimated) | ~1.0-1.5 | ~0.5-0.8 |
Source: Eurostat 2022, Ukrainian estimates based on regional data
⚠️ War Impact: Since February 2022, conservative estimates indicate 707 assaults on healthcare facilities and 86 direct attacks on medical personnel. Many imaging centers destroyed or shuttered.
4. Telemedicine Surge in Conflict Zones
The war accelerated telemedicine adoption in unprecedented ways:
TELEMEDICINE ADOPTION BY REGION (2022-2023) ═══════════════════════════════════════════ HIGH ADOPTION (conflict-affected): ├── Kyiv Oblast ████████████████ ├── Chernihiv Oblast ███████████████ ├── Kharkiv Oblast ██████████████ ├── Sumy Oblast █████████████ └── Kherson Oblast ████████████ LEADING INFRASTRUCTURE (pre-war): ├── Odesa Oblast ███████████████ (telemedicine center) ├── Lviv Oblast ██████████████ (telemedicine center) └── Poltava Oblast █████████████ (telemedicine center) SERVICE PROVIDERS: ├── Private facilities ██████████████████████ (majority) └── Public facilities ████████ (minority)
Figure 2: Telemedicine adoption patterns during conflict
Key Findings:
- Private healthcare facilities provide majority of telemedicine services
- Video, medical data sharing, audio, and text consultations prevalent
- Diia app (from July 2024) enables patient access to eHealth records
- 31.6 million Ukrainians have signed declarations with primary care physicians
5. Digital Health Infrastructure for AI
Current EHS Registries (AI-Ready Data Sources):
| Registry | Data Type | AI Potential |
|---|---|---|
| Patient Registry | Demographics, declarations | Population health analytics |
| Healthcare Facilities | Locations, capabilities | Resource optimization |
| Health Professionals | Specializations, workload | Workflow analysis |
| Prescriptions | Medications, dosages | Drug interaction detection |
| Electronic Medical Records | Clinical notes, diagnoses | Diagnostic AI training |
| COVID-19 Data | Testing, vaccination | Epidemiological modeling |
Upcoming Digital Initiatives:
- e-Stock: Digital inventory management for medical supplies
- State Registry of Medicines: Modernization for drug tracking
- Medical Equipment Registry: Device tracking including imaging
- Rehabilitation Initiative: Supporting wounded civilians/military
- Big Data Analysis Platform: Foundation for ML applications
6. Challenges for AI-Powered Medical Imaging
Critical Constraints:
- MIS Consolidation: Pre-war 40 MIS reduced to 4-6 viable systems
- IT Workforce Evacuation: Many qualified specialists fled abroad
- Infrastructure Destruction: Imaging centers damaged/destroyed
- Financial Losses: IT companies suffered huge losses
- Equipment Scarcity: CT/MRI density below EU standards
7. Opportunities for ScanLab Integration
🎯 Strategic Entry Points:
- Surviving MIS Integration: Partner with 4-6 remaining viable MIS providers
- Central Database API: Leverage existing interoperability standards
- Telemedicine Enhancement: Add AI-assisted remote diagnostics
- Rehabilitation Focus: Align with government priority on wounded care
- NHSU Contracting: Single-payer system simplifies adoption path
8. Unique Conclusions
Original Insights:
- The “Leapfrog Opportunity”: Ukraine’s forced digital transformation during crisis could enable faster AI adoption than gradual EU approaches—similar to mobile banking leapfrogging in developing economies.
- MIS Consolidation Advantage: While tragic, reduction from 40 to 4-6 MIS providers actually simplifies AI integration—fewer systems to support, more standardization.
- Private-Public Imbalance: Private sector’s dominance in telemedicine suggests AI solutions should target private facilities first, then expand to public hospitals.
- Data Richness Despite Chaos: 1.6 billion electronic medical records + COVID-19 data + rehabilitation tracking = substantial training data for Ukrainian-specific ML models.
- Workforce-AI Synergy: With medical workforce depleted, AI assistance isn’t a luxury—it’s becoming a necessity for maintaining care quality.
9. Practical Recommendations
For ScanLab Development:
| Phase | Action | Rationale |
|---|---|---|
| Immediate | Map surviving MIS APIs | Integration foundation |
| Short-term | Pilot with Lviv/Odesa centers | Existing telemedicine infrastructure |
| Medium-term | NHSU partnership proposal | Single-payer enables system-wide deployment |
| Long-term | Training data acquisition from EHS | Ukrainian-specific model development |
10. References
- PMC12491902 — “The future of Ukrainian healthcare: the digital opportunity” (2025)
- PMC10754247 — “Insight into the Digital Health System of Ukraine (eHealth)” (2023)
- WHO European Observatory — “Health systems in action: Ukraine 2024”
- Eurostat — “Healthcare resource statistics – technical resources and medical technology” (2024)
- VoxUkraine — “White Book of Reforms 2025: Healthcare reforms”
- Ukrainian Ministry of Health — eHealth initiative documentation
Questions Answered
✅ What is Ukraine’s current medical imaging infrastructure?
Below EU average (~1.0-1.5 CT, ~0.5-0.8 MRI per 100K), further degraded by war damage.
✅ How does eHealth enable AI integration?
Two-level architecture with central database (36M patients, 1.6B records) and standardized APIs across MIS providers creates interoperable foundation.
Open Questions for Future Articles
- What specific imaging modalities are most available in Ukrainian facilities?
- How can federated learning address data privacy in cross-border Ukrainian healthcare?
- What regulatory approvals (Ukrainian MHSU) are required for AI diagnostic tools?
Next Article: “ML Model Taxonomy for Medical Imaging” — exploring CNN, ViT, and hybrid architectures for diagnostic applications.
Stabilarity Hub Research Team | hub.stabilarity.com