How SDC4 solves healthcare's toughest data challenges with version coexistence and semantic clarity
Healthcare systems speak different languages, creating costly barriers to patient care and data exchange
FHIR R4 → R5 migration costs hospitals $2-5M each. Patient data from 2015 becomes incompatible with 2025 systems, forcing expensive migrations or data loss.
Proprietary EHR formats trap data inside silos. Switching vendors costs millions in migration, and interoperability requires expensive interface engines.
Medical records scattered across hospitals, clinics, labs, and pharmacies. No single source of truth. Fragmented care and duplicated tests.
Separate structure from semantics. FHIR resources map to SDC4 Clusters. Data lives forever.
SDC4 and SDC5 data work together in the same system. No forced migrations. When SDC5 is released, add it alongside SDC4 without breaking existing data.
Same Patient component → multiple SDC versions → SDC4 + SDC5 (when released) coexist
Link to SNOMED CT, LOINC, RxNorm, ICD-10, and proprietary code systems—all in the same data element. Semantic clarity without vendor lock-in.
One Diagnosis → SNOMED + ICD-10 + Local Codes
Design once, use everywhere. Patient Address component works for home, work, temporary, billing—different semantics, same structural type.
XdString → Name, Address, Diagnosis, Medication, ...
Patient records from 2025 will still be readable in 2075. CUID2-based component IDs ensure structural stability. Ontology links provide semantic evolution.
mc-abc123xyz → Immutable structure + evolving semantics
Patient, Observation, Medication → SDC4 Cluster types
rdfs:isDefinedBy → FHIR R4, R5, SNOMED, LOINC URIs
XSD validation + SHACL constraints + RDF triples
Comprehensive documentation for mapping healthcare standards to SDC4
Bottom-up analysis of all 56 FHIR datatypes with detailed SDC4 mapping strategies. Learn how primitive, complex, and special-purpose types translate to SDC4 components.
Complete Patient, Observation, and Medication resource mappings with XML examples. Step-by-step instructions for converting FHIR instances to SDC4.
Quick lookup table for implementation decisions. Find the right SDC4 type for any FHIR datatype, cardinality pattern, or terminology binding.
How SDC4 eliminates forced migrations and ensures long-term data permanence. Detailed economic analysis showing $162B in 10-year savings across the healthcare industry.
Legacy message format mapping for ADT, ORM, ORU, and other message types. Bridge the gap between V2 and modern FHIR systems.
Clinical Document Architecture templates for C-CDA, continuity of care, discharge summaries, and other clinical documents.
Real-world applications of SDC4 in healthcare settings
Multi-vendor EHR interoperability. Epic, Cerner, Meditech, and open-source systems exchange patient data seamlessly. No interface engine required.
Regional and national HIEs connect hospitals, clinics, labs, pharmacies, and payers. Single patient view across organizations.
Longitudinal research studies spanning decades. Data from 2025 remains valid and computable in 2050. No migration costs between phases.
AI/ML models trained on structured, semantically rich data. Multi-vocabulary support enables broader training datasets and better predictions.
Aggregate patient data across systems for public health surveillance, quality measures, and outcome reporting. Consistent semantics enable accurate analysis.
Patients control their own health data. Export from any EHR, import to any app. True interoperability without proprietary barriers.
Quantified savings from eliminating forced migrations and enabling true interoperability
By using SDC4→SDC5 version coexistence instead of forced FHIR migrations
Typical cost for FHIR version upgrade including testing, integration, and downtime
SDC5 (when released) coexists with SDC4 data. No forced migrations ever.
Explore our comprehensive FHIR integration guides, or contact us to discuss your specific use case