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Intelligent Healthcare Data Interoperability Platform Using SMART on FHIR, Medplum, .NET and AWS
FHIR Academy Capstone Project
Author
Himanshu Agrawal
Organization
CitiusTech
Program
FHIR Academy Capstone Project
Executive Summary
Healthcare organizations rely on multiple Electronic Health Record (EHR) systems to manage patient information. While these systems contain critical clinical data, the lack of interoperability between healthcare applications often leads to fragmented patient information, delayed decision-making, and operational inefficiencies.
This project presents a cloud-native Healthcare Data Interoperability Platform that leverages SMART on FHIR standards, Medplum FHIR Server, .NET 8 microservices, React-based user interfaces, and AWS cloud services to provide secure, scalable, and standardized healthcare data exchange.
The platform enables clinicians and healthcare organizations to retrieve patient healthcare information from SMART on FHIR-enabled EHR systems, validate and normalize healthcare resources, synchronize data into Medplum, and provide a centralized, secure, and scalable patient data platform.
Project Vision
To build a modern healthcare interoperability platform that enables seamless exchange, validation, and management of clinical data across healthcare systems using FHIR standards and cloud-native technologies.
Project Objectives
Primary Objectives
Healthcare Interoperability
Enable seamless healthcare data exchange using FHIR R4 standards.
SMART on FHIR Integration
Develop a SMART on FHIR application capable of securely launching within EHR workflows.
Data Standardization
Validate and normalize healthcare resources before persistence.
Centralized Data Platform
Synchronize healthcare data to Medplum FHIR Server.
Secure Cloud Architecture
Deploy the platform using AWS cloud services.
Scalable Infrastructure
Support future expansion and integration with additional healthcare systems.
Business Problem
Healthcare organizations face several challenges:
Fragmented Patient Data
Patient information is distributed across multiple healthcare systems, making it difficult to obtain a complete view of patient health.
Limited Interoperability
Different EHR vendors implement healthcare standards differently, resulting in integration challenges.
Data Quality Issues
Incoming healthcare data may contain validation errors, missing fields, or inconsistent coding systems.
Security and Compliance Requirements
Healthcare applications must securely manage sensitive patient information and comply with industry regulations.
Scalability Challenges
Traditional healthcare systems often struggle to scale efficiently as the volume of patient data grows.
Proposed Solution
The Intelligent Healthcare Data Interoperability Platform addresses these challenges by introducing:
- SMART on FHIR-based authentication and authorization
- Real-time patient data retrieval
- Automated FHIR resource validation
- Data normalization services
- Medplum FHIR Server integration
- AWS-hosted cloud architecture
- Secure OAuth 2.0 authentication
- Audit logging and monitoring services
Solution Architecture
Core Components
SMART on FHIR Application
Provides clinicians with access to patient healthcare information directly from EHR systems.
Backend API Services
Developed using .NET 8 to process, validate, and synchronize healthcare resources.
Validation Engine
Performs healthcare resource validation and normalization.
Medplum FHIR Server
Serves as the centralized FHIR repository.
PostgreSQL Database
Stores healthcare resource data and application metadata.
AWS Cloud Infrastructure
Provides scalable hosting, monitoring, and security.
Functional Scope
Supported Resources
The platform supports synchronization and management of:
- Patient
- Observation
- Encounter
- Condition
- AllergyIntolerance
- Procedure
- MedicationRequest
- Immunization
- Practitioner
- Organization
- DiagnosticReport
- CarePlan
End-to-End Workflow
Step 1
Clinician launches SMART on FHIR application from EHR.
Step 2
OAuth 2.0 Authorization Code Flow is initiated.
Step 3
Access token is issued by the EHR authorization server.
Step 4
FHIR resources are retrieved.
Step 5
Resources are validated against predefined rules.
Step 6
Normalization engine corrects allowed field discrepancies.
Step 7
Validated resources are synchronized into Medplum.
Step 8
Audit records are generated.
Step 9
Resources become available for downstream healthcare applications.
Validation Engine
Purpose
To ensure healthcare data quality before storage.
Validation Rules
Patient Validation
- Gender validation
- Birth date validation
- Identifier validation
- Name validation
Observation Validation
- Status validation
- Code validation
- Subject validation
Condition Validation
- Clinical status validation
- Verification status validation
MedicationRequest Validation
- Status validation
- Intent validation
Encounter Validation
- Encounter status validation
Allergy Validation
- Clinical status verification
Security Architecture
Authentication
SMART on FHIR OAuth2
Authorization
Role-Based Access Control
Transport Security
TLS / HTTPS
Data Security
Encrypted database connections
Cloud Security
AWS IAM and Secrets Management
AWS Deployment
Frontend Layer
- AWS S3
- AWS CloudFront
Application Layer
- ASP.NET Core APIs
- Docker Containers
- AWS ECS/Fargate
Data Layer
- Medplum
- PostgreSQL
- AWS RDS
Monitoring Layer
- AWS CloudWatch
- Application Logs
- Audit Logs
Key Features
- SMART on FHIR Launch
- OAuth 2.0 Authentication
- Resource Validation
- Resource Normalization
- Medplum Integration
- AWS Deployment
- Individual Resource Synchronization
- Audit Logging
- Secure APIs
- Cloud-Native Architecture
Benefits
Clinical Benefits
- Faster access to patient data
- Improved clinical decisions
- Better workflow integration
Technical Benefits
- FHIR-compliant architecture
- Cloud scalability
- Standardized APIs
Organizational Benefits
- Reduced integration effort
- Improved interoperability
- Better data governance
Deliverables
- SMART on FHIR Application
- React Frontend
- .NET Backend APIs
- Validation Engine
- Medplum Integration
- AWS Deployment Architecture
- Technical Documentation
- User Guide
- Deployment Guide
- Final Presentation
Future Enhancements
Artificial Intelligence
AI-assisted clinical recommendations.
Clinical Decision Support
Real-time decision support workflows.
Healthcare Analytics
Population health dashboards.
Event Streaming
FHIR event-driven architecture.
Multi-EHR Integration
Epic, Cerner, Allscripts, Meditech, Athena.
Generative AI
Conversational healthcare assistants.
Conclusion
The Intelligent Healthcare Data Interoperability Platform demonstrates how SMART on FHIR, .NET 8, Medplum, React, and AWS can be combined to create a secure, scalable, and interoperable healthcare ecosystem.
The platform improves healthcare data accessibility, enhances interoperability, promotes data quality, and establishes the foundation for future innovation in healthcare technology.