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Healthcare Interoperability Solutions: How Momentum Builds FHIR-Compliant Data Pipelines

Author
Aleksander Cudny
Published
April 24, 2026
Last update
April 24, 2026

Table of Contents

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Key Takeaways

  1. Momentum has shipped interoperability solutions across 7 EHR systems simultaneously (Epic, Cerner, AthenaHealth, NextGen, Veradigm, AllScripts, Altera) within a single project.
  2. Choosing the right standard matters as much as the integration: FHIR R4 for modern APIs, HL7 v2 for legacy hospital infrastructure, CCDA for transitions of care, CDS Hooks for real-time decision support inside EHR workflows.
  3. Clients typically reduce compliance-related development time by up to 60% using Momentum's pre-built modules for HIPAA-compliant data handling, audit logging, and secure transport.
  4. For teams building AI features on clinical data, interoperability is the prerequisite: normalized, structured FHIR data is what makes cross-system analytics pipelines and AI models work at all.

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A clinician at a regional hospital opens three tabs every morning before seeing a patient: the hospital's EHR, a specialist portal from a different health system, and a lab results platform that still sends PDFs. None of these systems talk to each other. The physician spends 20 to 30 minutes per patient pulling data that already exists somewhere, reconciling conflicting medication lists, and re-entering information that was entered correctly in another system two days earlier.

For digital health companies building software on top of this reality, the problem compounds quickly. A new app integrates with one EHR, ships, and then a client asks for a second. Each new system has its own API conventions, authentication flows, and data formats. The analytics pipeline that worked fine with Epic's FHIR R4 endpoint breaks when a hospital partner runs Cerner with a different resource model. By the time the fourth EHR is in scope, the team is maintaining four separate integration codebases and spending a third of every sprint on data normalization.

Momentum specializes in healthcare interoperability solutions that solve this at the architecture level, not one integration at a time.

Momentum's Approach to Healthcare Data Interoperability

The starting point for any EHR integration decision is standards selection. Each standard covers a distinct problem space, and picking the wrong one for a given integration creates technical debt that compounds as the system grows.

Standard Use case When to use
FHIR R4 Modern EHR APIs, mobile apps, patient access Primary choice for new integrations
HL7 v2 Legacy hospital systems, lab results, ADT messages Required for older infrastructure
CCDA/CCD Clinical document exchange, referrals Transitions of care, patient summaries
CDS Hooks Real-time clinical decision support Alerts inside EHR workflows

FHIR R4 is the primary standard for new work. It has broad adoption across Epic, Cerner, AthenaHealth, and most modern EHRs, a well-defined REST API model, and strong tooling support. For teams building patient-facing apps, SMART on FHIR handles the authorization layer, letting your app request specific FHIR scopes from within the EHR without custom OAuth implementations per vendor.

Legacy hospital infrastructure rarely speaks FHIR natively. HL7 v2 remains the dominant wire protocol for lab results, ADT messages, and inpatient workflows at institutions that have been running the same hospital information system for fifteen years. Momentum builds HL7 translation layers that normalize v2 messages into FHIR resources, so the rest of the pipeline works against a consistent data model regardless of what the source system sends.

CDS Hooks lets you inject cards, alerts, and suggestions directly into the EHR's existing workflow at defined trigger points: when a patient chart opens, when a prescription is ordered, when a referral is placed. Momentum has built CDS Hooks integrations that surface risk scores, flag drug interactions, and present care gap alerts without requiring any change to the clinical workflow.

Use Cases Momentum Has Shipped

Patient data sync across multiple EHR systems. Connecting a new application to EHR systems so patients or caregivers can access their records without logging into separate portals. Each EHR gets a dedicated connector handling authentication, resource mapping, and rate limit management.

Cross-system clinical analytics. Momentum builds normalization pipelines that transform heterogeneous source data into a unified FHIR-based schema before it reaches the analytics layer. This includes concept mapping (SNOMED, LOINC, ICD-10), deduplication, and temporal alignment when timestamps differ across sources.

Real-time clinical decision support. CDS Hooks integrations connect your clinical logic to the EHR at defined trigger points. Momentum has implemented this pattern across both Epic and Cerner.

App-layer FHIR access for patients. SMART on FHIR provides the authorization framework for patient-facing apps requesting access to clinical records from within an EHR. Momentum builds SMART on FHIR integrations handling the full OAuth flow, scope negotiation, token refresh, and graceful handling of EHR-specific variations.

Project Example: Caily

Caily is a family caregiving platform that lets family members coordinate care for aging relatives, including access to medical records across the care team's health systems. Momentum integrated Caily with seven EHR systems: NextGen, Veradigm, AllScripts, Altera, AthenaHealth, Cerner, and Epic. Each required a distinct approach.

Rather than building seven independent integrations, Momentum designed an abstraction layer with a canonical data model (FHIR R4 resources: Patient, Condition, Observation, MedicationRequest, AllergyIntolerance, DocumentReference) and per-system adapters mapping to this model. The platform launched in July 2025, on schedule. Wynter Johnson, co-founder of Caily: "Momentum were the only company understanding our vision, and knew how to deliver it."

Stack and Tools

HAPI FHIR. Open-source FHIR server Momentum deploys when clients need full control over their FHIR infrastructure. Appropriate for teams with strict data residency requirements or building an internal FHIR repository aggregating data from multiple source systems.

AWS HealthLake. Managed FHIR-compliant data store for ingestion, querying, and analytics on clinical data at scale. Faster to stand up than self-hosted HAPI FHIR, well-suited for analytics workloads.

Custom middleware. Legacy systems that predate FHIR require middleware translating their native protocols into FHIR resources: HL7 v2 message parsers, CCDA document transformers, proprietary API adapters. Built as standalone services so the translation layer can be updated when a source system changes without touching the main application.

API gateway layer. Provides a unified endpoint for the application team. Routing, authentication delegation, rate limiting, and response normalization happen at the gateway.

Sync health monitoring. Every interoperability deployment includes monitoring for which provider API connections are active, last successful sync timestamps, and whether data completeness has degraded.

For a deeper look at interoperability standards in the US context, see our USCDI guide.

Frequently Asked Questions

What is healthcare interoperability?
Healthcare interoperability is the ability of different health information systems to exchange data and use that data in a meaningful way. In practice, it means a patient's records from one EHR can be read by another system, a lab result from one platform can flow into a clinical decision support tool, and a mobile app can pull data from a hospital's records without requiring manual re-entry. Standards like FHIR R4, HL7 v2, and CCDA define the protocols that make this exchange possible.

Healthcare interoperability is the ability of different health information systems to exchange data and use that data in a meaningful way. In practice, it means a patient's records from one EHR can be read by another system, a lab result from one platform can flow into a clinical decision support tool, and a mobile app can pull data from a hospital's records without requiring manual re-entry.

Standards like FHIR R4, HL7 v2, and CCDA define the protocols that make this exchange possible. See the USCDI guide for the US regulatory framework around interoperability.

What is the difference between FHIR R4 and HL7 v2?
FHIR R4 is a modern REST-based standard for healthcare data exchange, designed for web and mobile applications. It uses JSON or XML resources (Patient, Observation, Condition, etc.) and supports OAuth-based authorization. HL7 v2 is an older message-based protocol, still dominant in hospital infrastructure for clinical events like admissions (ADT), lab results (ORU), and scheduling (SIU). Most modern EHRs support FHIR R4 for new integrations, but HL7 v2 remains required for legacy systems and many inpatient workflows.

FHIR R4 is a modern REST-based standard for healthcare data exchange, designed for web and mobile applications. It uses JSON or XML resources (Patient, Observation, Condition, etc.) and supports OAuth-based authorization.

HL7 v2 is an older message-based protocol, still dominant in hospital infrastructure for clinical events like admissions (ADT), lab results (ORU), and scheduling (SIU). Most modern EHRs support FHIR R4 for new integrations, but HL7 v2 remains required for legacy systems and many inpatient workflows.

What is CDS Hooks?
CDS Hooks is a standard for integrating clinical decision support into EHR workflows. It lets external services inject cards, alerts, and suggestions directly into the EHR interface at defined trigger points: when a patient chart opens, when a prescription is ordered, or when a referral is placed. Unlike standalone clinical tools, CDS Hooks surfaces information inside the clinician's existing workflow without requiring them to switch applications. Momentum has built CDS Hooks integrations across Epic and Cerner.

CDS Hooks is a standard for integrating clinical decision support into EHR workflows. It lets external services inject cards, alerts, and suggestions directly into the EHR interface at defined trigger points: when a patient chart opens, when a prescription is ordered, or when a referral is placed.

Unlike standalone clinical tools, CDS Hooks surfaces information inside the clinician's existing workflow without requiring them to switch applications. Momentum has built CDS Hooks integrations across Epic and Cerner.

What is SMART on FHIR and how is it used in healthcare interoperability?
SMART on FHIR is an authorization framework that combines OAuth 2.0 with FHIR to let health apps request access to patient or provider data stored in EHR systems. For patient-facing apps, it handles the patient authorization flow: the patient logs in and grants the app specific data access. For provider-facing apps, SMART Backend Services handles system-to-system authorization without a patient login. SMART on FHIR is supported by all major EHR vendors and is the primary authorization mechanism for interoperability in modern health app development.

SMART on FHIR is an authorization framework that combines OAuth 2.0 with FHIR to let health apps request access to patient or provider data stored in EHR systems.

For patient-facing apps, it handles the patient authorization flow: the patient logs in and grants the app specific data access. For provider-facing apps, SMART Backend Services handles system-to-system authorization without a patient login. SMART on FHIR is supported by all major EHR vendors and is the primary authorization mechanism for interoperability in modern health app development.

How does Momentum handle EHR systems that don't support FHIR?
For EHR systems without native FHIR support, Momentum builds middleware that translates the system's native protocol into FHIR resources. HL7 v2 feeds are parsed into FHIR-compatible structures (ADT to Encounter, ORU to Observation, etc.). Systems exposing proprietary REST APIs get a custom adapter mapped to the application's data model. CCDA clinical documents are parsed and normalized. File-based systems use SFTP or batch processing. The application layer always works against the same normalized interface regardless of what the source system exposes.

For EHR systems without native FHIR support, Momentum builds middleware that translates the system's native protocol into FHIR resources.

HL7 v2 feeds are parsed into FHIR-compatible structures (ADT to Encounter, ORU to Observation, etc.). Systems exposing proprietary REST APIs get a custom adapter mapped to the application's data model. CCDA clinical documents are parsed and normalized. The application layer always works against the same normalized interface regardless of what the source system exposes.

Written by Aleksander Cudny

Business Analyst
Aleksander helps HealthTech founders make sense of complex interoperability requirements, integration strategies, and product costs. With a background in healthcare data systems and a sharp analytical mindset, Alek translates regulatory and technical nuance into actionable insights.

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