Introduction
Aneurysms are life-threatening conditions that often go undetected until it is too late. According to the Centers for Disease Control and Prevention (CDC), over 50,000 deaths annually in the United States are attributed to aortic and brain aneurysms. In response to this clinical challenge, a global data science and analytics company embarked on a mission to build a robust, real-time Aneurysm Decision Support System (DSS). This system leverages Fast Healthcare Interoperability Resources (FHIR) R4 APIs from Epic and Athenahealth to empower clinicians in acute-care settings to accurately triage, assess, visualize, and monitor aneurysm development and progression.
The core objective of the DSS is to integrate seamlessly with leading Electronic Health Record (EHR) systems and provide physicians with timely, actionable insights directly within their clinical workflows. This document outlines the detailed architecture, implementation approach, integration strategy, and business value of this advanced healthcare
Project Objectives
• 🧠 To enable real-time aneurysm detection and triage in clinical settings
• 🔗 To provide seamless integration with major EHR systems: Epic and Athenahealth
• 🌐 To utilize FHIR R4 resources and SMART on FHIR standards for interoperability
• 🔒 To ensure secure, compliant, and scalable data exchange
• 🏥 To enhance clinical workflows and improve patient outcomes
Business Challenge: Lack of Interoperability and Unified Patient Records
Hospitals and healthcare providers operate in environments where clinical data is often siloed across disparate systems. This fragmentation hinders clinicians’ ability to make data-driven decisions at the point of care. The inability to leverage real-time data due to poor interoperability and the absence of a unified patient record significantly limits diagnostic accuracy and delays treatment. The challenge was to build an intelligent system capable of aggregating, transforming, and delivering context-aware clinical data in a secure, compliant manner.
Scope of the Project
The development was split into two major phases:
Phase 1: Clinical Data Integration
- FHIR-based data extraction from Epic and Athenahealth
- Normalization and mapping using Mirth Connect
- Secure authentication using OAuth 2.0 and SMART on FHIR protocols
- JSON output generation for DSS ingestion
Phase 2: Workflow Integration and SSO
- iFrame embedding of DSS in EHR environments
- Context-passing for patient-specific insights
- Single Sign-On (SSO) using SAML 2.0 and OpenID Connect
Integration with Epic EHR
Registration and FHIR Access The DSS was successfully registered with the Epic Developer Portal to enable API access. Epic’s FHIR R4 APIs offer RESTful endpoints along with OAuth 2.0 authentication to facilitate secure data exchange.
Authentication Workflow Using the Standalone Launch framework of SMART on FHIR, the DSS initiated an OAuth 2.0 handshake to retrieve access tokens. This ensured secure communication and protected patient health information (PHI).
Data Extraction and Transformation Relevant FHIR R4 resources such as Patient, Condition, Observation, ImagingStudy, and Procedure were queried. Mirth Connect acted as the transformation engine, mapping extracted data to the DSS schema. The output was delivered in structured JSON format, ready for real-time analytics and visualization.
Integration with Athenahealth EHR
API Access Models Athenahealth provides multiple integration pathways, including Certified FHIR APIs and proprietary AthenaOne APIs. The latter requires a vendor agreement and is billed based on API call volume.
Authentication and SMART Back-End Services The DSS used a 2-legged OAuth 2.0 flow (Client Credentials Grant) to authorize access. It operated as a SMART back-end service, functioning autonomously without requiring end-user interaction.
Event-Driven Data Access Athenahealth supports changed data subscriptions, allowing the DSS to poll for specific events and clinical changes. This capability emulates HL7 v2’s event-based messaging and is instrumental in triggering DSS workflows.
Contextual Launch and SSO Athenahealth’s support for SAML 2.0 and OpenID Connect allowed for secure, seamless SSO integration. Clinicians could launch the DSS directly from their EHR interface, with full patient context passed through iFrame embedding.
Technology Stack
• 📦 FHIR R4 Resources: Patient, Observation, Condition, ImagingStudy, Procedure, Encounter
• 🔄 Integration Engine: Mirth Connect
• 🔐 Authentication: OAuth 2.0 (SMART on FHIR, Client Credentials)
• 📊 Data Standards: USCDI, SMART on FHIR, HL7 v2, JSON
• 🛡️ Security Protocols: TLS/SSL, SAML 2.0, OpenID Connect
Key Features and Capabilities
• ⚠️ Real-Time Risk Alerts: Immediate notification for high-risk aneurysm indicators
• 📈 Clinical Visualization: Graphical rendering of aneurysm growth and comparison over time
• 🧩 EHR-Embedded Workflows: DSS accessible directly within Epic and Athenahealth portals
• 🧠Contextual Intelligence: Patient-specific recommendations based on structured and unstructured data
• ✅ Regulatory Compliance: HIPAA, HITECH, and ONC certification-aligned architecture
Business Impact and Outcomes
- Improved Diagnostic Accuracy: Clinicians received risk assessments based on complete, real-time data
- Workflow Optimization: Reduced need to switch between systems; improved usability and clinical efficiency
- Time to Insight Reduced: Decisions made faster due to near-instant access to relevant clinical data
- Clinical and Financial ROI: Fewer missed diagnoses led to improved outcomes and cost savings for hospitals
- Scalability: The modular architecture allows easy expansion to other diseases and healthcare systems
Conclusion
The Aneurysm Decision Support System represents a significant leap in real-time, data-driven healthcare. By leveraging modern interoperability standards like FHIR R4, and integrating with industry-leading EHR platforms such as Epic and Athenahealth, the DSS enables providers to deliver proactive, precise, and personalized care. Through robust authentication mechanisms, advanced data mapping, and seamless SSO-enabled workflows, this solution stands as a model for future clinical decision support innovations.
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