It takes fragmented clinical and claims data and turns it into structured, unified patient records that are ready for downstream use.
Input: HL7, FHIR, X12 (837, 835), ADT
Output: Structured raw data
Input: Conflicting codes, legacy formats
Output: Unified clinical models
Input: Disparate sources across providers/payers
Output: Longitudinal patient records
who want a complete view of the patient
You can use SyncMesh as the groundwork to build any healthcare-native system to help you with any use-case, some of which are to:
SyncMesh natively understands the complex, inconsistent formats used across healthcare systems, so you don’t have to normalize anything manually.
Most integration platforms treat healthcare like any other industry. We don’t.
Feature | SyncMesh | Mirth Connect | Rhapsody/Redox |
---|---|---|---|
Cloud-Native & Serverless | ✅ Fully serverless, stateless, auto-scalling | ❌ Stateful, always-on | ❌ Stateful, always-on |
Incremental Message Processing | ✅ Native support for message-by-message processing | ⚠️ Channel-based (indirect support) | ⚠️ Limited Support |
Schema Validation & Type Safety | ✅ Strongly enforced schema and static typing | ⚠️ Limited; custom scriptiing | ❌ Minimal |
Transformation Model | ✅ Schema-driven, declarative mappings | ⚠️ Script-based or GUI-driven | ⚠️ Script-based (JavaScript) |
Developer Workflow | ✅ Fast, self-service, low vendor dependence | ⚠️ Medium-DUI-driven | ❌ Slow, vendor-led |
Cost Model | ✅ Pay-per-utilization; no idle infra | ❌ Requires provisioning; always-on | ❌ Requires provisioning; always-on |
Architecture | ✅ Microservices; composable & modular | ❌ Monolithic | ❌ Monolithic |
UI & Observability | ✅ Optional UI; deployable without it | ❌ Required | ❌ Required |
We’ll show you how we turn fragmented clinical and claims data into a unified patient record.