# 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

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# 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.

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# 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.

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# 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.

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# 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.

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# 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

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# 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.

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# Functional Scope

## Supported Resources

The platform supports synchronization and management of:

- Patient
- Observation
- Encounter
- Condition
- AllergyIntolerance
- Procedure
- MedicationRequest
- Immunization
- Practitioner
- Organization
- DiagnosticReport
- CarePlan

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# 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.

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# 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

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# 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

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# 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

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# 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

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# 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

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# 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

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# 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.

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# 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.