How Microservices Improve Healthcare Interoperability
Introduction
Healthcare interoperability remains limited, leading to repeated tests, delays, unknown medications, and compromised patient safety. While systems could provide doctors instant access to medical records, patients still rely on carrying their files.
This lack of interoperability in healthcare leads to oversight, compromises patient safety, and wastes billions annually. Outdated monolithic architectures remain a significant obstacle for healthcare systems worldwide.
Monolithic software is a single, integrated unit where a shared codebase and tightly coupled components lead to complex deployments, inefficient scaling, and high maintenance costs.
Transitioning to microservices is an elegant solution to the above problems and enhances interoperability among healthcare systems. This switch equips healthcare systems with loosely coupled services, independent deployments and scaling of each component, and easier maintenance.
This blog starts with the basics of microservices and their importance in healthcare. Then, we dive deep into this transition's technologies, implementation, benefits, and challenges.
Understanding Microservices in Healthcare
Microservices follow a modern software design approach, offering small, independent, and loosely coupled services. Each service caters to a specific business requirement and uses APIs to communicate with other services. This enables higher flexibility, scalability, and maintainability compared to monolithic architectures.
Why Microservices are Important for Healthcare Systems?
Patients' evolving expectations pave the way for rapid digital transformation in the healthcare industry. With advancements in treatments, diagnostics, and medical procedures, implementing robust technology is the need of the hour.
The inherent limitations of monolithic architectures often prevent them from adapting to these changing needs. Systems integrating seamlessly with emerging technologies like electronic healthcare systems (EHR), telemedicine, wearables, and AI-based diagnostics are direly needed. Microservices provide healthcare systems with the agility to meet growing demands.
Key Technologies Supporting Microservices
Here is a brief list of technologies that assist with implementing microservices.
1. OpenAPI (Swagger)
It’s a comprehensive framework that provides consistency and ease with integration when designing, developing, and documenting RESTful APIs.
2. GraphQL
A query language that offers flexibility and accurate data retrieval to address changing client requirements.
3. Docker
Containerization techs make deployment consistent across different environments by packaging the application and its dependencies.
4. Kubernetes
An orchestration platform that simplifies microservices deployment by managing containerized applications using automated scaling, deployment, and management.
5. Apache Kafka
A distributed streaming platform that ensures reliable communication between microservices for real-time data pipelines and streaming applications.
6. RabbitMQ
A message broker that provides data exchange and seamless communication between microservices.
How to Implement Microservices for Healthcare Interoperability?
Before commencing your implementation journey, you must know that transitioning from an existing monolith to microservices can be costly. It requires architects and developers to closely examine whether decomposing monolith architecture is the right decision and whether transitioning to microservices is a holistic solution.
Having cleared this, let’s observe some essential practices while implementing microservices for healthcare companies.
1. Decouple Core Healthcare Functions
As a primary step, it’s essential to identify service boundaries based on business capabilities.
- Begin by analyzing domain-driven designs. This helps separate functionalities like appointments, billing, and patient records.
- Start incrementally replacing the monolith components using the ‘Strangler Fig Pattern.’
- Implementing API gateways while ensuring a secure data flow is crucial.
- Maintain consistency by carefully executing shared databases or database-per-service.
- Introduce automation with monitoring, fault tolerance, and CI/CD.
- Make security and compliance a high priority with service interactions.
These adjustments make healthcare systems more performant and maintainable while facilitating scalability, resilience, and quick updates.
2. Implement FHIR & HL7 Standards
Fast Healthcare Interoperability Resources (FHIR) and Health Level Seven (HL7), built as interoperability standards, are well-suited for microservice architectures. Here’s how they offer assistance.
a) Seamless Data Exchange Using FHIR
Offering a standardized interoperability framework, FHIR facilitates seamless data exchange.
- It ensures consistency across systems presenting pre-built resources like Patient, Encounter, and Observation.
- In addition, it offers customization with enhanced compatibility.
- FHIR enables accurate data sharing with standards like CT, SNOMED, ICD-10, & LOINC.
- Efficient data retrieval and updates are conducted using the RESTful API model.
- It maintains data integrity and prevents partial updates with transactional support.
- It enhances care coordination with a subscription framework that provides event-driven communication. This ensures that medication changes or lab results are instantly reflected on the platform.
b) Efficient Data Exchange With HL7 Messaging
HL7 enables secure, structured data exchange between different platforms, critical in integrating healthcare systems.
- It facilitates interoperability between EHRs, billing systems, and clinical applications with standardized messaging formats, such as ADT for admissions and ORU for lab results.
- HL7 v2 ensures timely patient data synchronization by offering real-time updates.
- Clinical Document Architecture and HL7 improve structured document sharing.
When used with FHIR, HL7 fosters seamless communication between modern applications and legacy systems. It enhances healthcare systems' interoperability by supporting efficient workflows like medication orders, care transitions, and patient referrals.
3. Build Secure & Compliant Microservices
Data about an individual's health can reveal a lot about them. If it falls into the wrong hands, it can result in malpractice. Here’s how to plan and create a safe and compliant microservice architecture for healthcare systems.
a) Ensuring Compliance in Distributed Systems with HIPAA, GDPR, and HITECH
Frameworks like HITECH, HIPAA, and GDPR exercise stringent practices when storing, sharing, or accessing patient data. Organizations should enforce secure architecture designs and robust policies to achieve compliance in distributed systems.
Depending on a software’s functionality and potential risks, it should be approved by regulatory authorities like the FDA. In addition, they must perform timely audits and continuous monitoring to protect sensitive patient data.
b) Access Control Using OAuth 2 and OpenID Connect
Securing authentication and access control is imperative in microservice architectures. OAuth2 and OpenID Connect facilitate Single Sign-On (SSO) across multiple devices, facilitating centralized authentication.
OAuth2 uses access tokens to offer delegated access. OpenID Connect adds an identity layer to offer user verification and profile information retrieval. Together, these protocols ensure interoperable, fine-grained, and scalable access control, strengthening security for distributed healthcare systems.
5 Key Benefits of Microservices for Healthcare Systems
The healthcare industry relies on seamless data exchange between systems, including EHRs, billing platforms, and clinical applications. Traditional monolithic architectures struggle with scalability, integration, and compliance.
Microservices offer a modular approach, breaking down large systems into smaller, independent services. This enhances interoperability, security, and efficiency in healthcare IT infrastructure.
Below are the 5 key benefits of microservices for healthcare systems.
1. Improved Scalability
Microservices help healthcare systems scale efficiently. It allows components, such as patient records, billing, or diagnostics, to operate independently.
Unlike monolithic architectures, where scaling requires upgrading the entire system, microservices facilitate on-demand scaling. For example, a telemedicine module can be expanded during peak hours without affecting other services.
2. Seamless Communication
Microservices support healthcare interoperability with seamless communication between different applications via APIs.
Standards like FHIR and HL7 exchange patient data securely across platforms. This ensures that hospitals, clinics, and pharmacies can share and access real-time patient information, reducing duplication and improving care coordination.
3. Faster Development & Deployment
With microservices, healthcare applications can be updated, deployed, and maintained independently. This modular approach allows development teams to implement changes in one service without disrupting the entire system.
This agility reduces downtime and accelerates the rollout of new features, such as AI-driven diagnostics or mobile health applications.
4. Better Security & Compliance
It enhances security by implementing role-based access and encrypted communication for each service.
Compliance with regulations such as HIPAA and GDPR becomes more manageable as security policies can be applied at a granular level. Data breaches are minimized since sensitive information is compartmentalized rather than stored in a single, vulnerable system.
5. Resilience & Fault Tolerance
Unlike monolithic systems, microservices isolate failures to specific components. For instance, if the billing service crashes, the patient record system remains operational.
This ensures higher system availability and minimizes disruptions in critical healthcare workflows.
Challenges of Monolith to Microservice Transition
Here are the top 4 most prevalent challenges observed when switching from monolith to microservice architecture.
1. Data Management
Challenge:
In monolith systems, all components share a single database. On the contrary, microservices have individual databases to ensure decoupling. This demands reshaping the entire application’s data architecture.
Solution:
Execute a thoroughly planned data migration strategy. You can start by breaking monolithic databases into smaller, service-specific databases.
Implement data synchronization and database refactoring techniques where required. Manage cross-service interactions using API endpoints. Additionally, data across services can be managed using methods like eventual consistency.
2. Service Communication
Challenge:
Usually, method calls within the same codebase facilitate inter-component communication in monolith systems. As these services are separate entities running in different environments with microservices, it is crucial to determine how they will interact.
Solution:
Conduct service-to-service communication using well-defined APIs. Manage complex interactions using choreography patterns or service orchestration.
Asynchronous communication can be performed using messaging queues or protocols like HTTP/REST. Leveraging service discovery mechanisms facilitates the dynamic location of services within the systems.
3. Deployment & Monitoring
Challenge:
Microservice-based applications are complex to deploy. Each microservice may have its deployment pipeline. Therefore, the system's distributed nature can pose a real challenge when monitoring multiple services.
Solution:
Standardize deployment and scaling with orchestration tools like Kubernetes and use containerization technologies like Docker. Utilize centralized logging and monitoring tools to monitor overall system health.
Reduce human errors and enhance efficiency by maximizing automation with deployment and monitoring.
4. Updating Legacy Systems
Challenge:
Transitioning to microservices can be challenging for legacy systems that are scarcely documented and difficult to grasp. If not managed well, this switch can pose significant risks.
Solution:
Learn the intricacies of legacy systems by understanding their codebase and reviewing documents. Then, plan a stepwise transition to microservices using strategies like the strangler pattern and incremental refactoring.
Without documentation, understanding legacy systems and preventing unexpected behavior are cumbersome tasks. Mitigate these issues by implementing reverse engineering or an Anti-Corruption layer.
Examples of Data Interoperability in Healthcare
Here are some of the key examples of data interoperability in healthcare.
1. Health Data Exchange (HDE) and Digital Health Records (DHR)
DHR is used to share patient information with other care providers. Moving patient data across healthcare ecosystems helps create a connected care environment.
HDE allows the transfer of patient data across various systems. It eliminates redundant testing and reduces administrative burden while ensuring continuity in care. Overall, DHRs contribute to creating efficient and cohesive healthcare systems.
2. FHIR Protocol
FHIR is a standard that facilitates communication between disparate systems and electronic data sharing. It also helps integrate health information from sources like wearables and mobile apps.
It eases interpreting and using data for healthcare systems using web-based standards. In addition, it fosters accurate and timely decision-making, increasing the accessibility of patient health information. It empowers patients by giving them the convenience of portable data.
3. Telemedicine Platforms
Connected healthcare platforms are essential to streamline data sharing between patients and providers and facilitate remote monitoring. This eliminates in-person visits for doctors and allows virtual consultations to manage chronic conditions.
Telemedicine platforms improve patient engagement and care coordination, offering real-time data by integrating with electronic healthcare systems. It’s also possible to link heart rate and glucose monitors and send data directly to healthcare providers, offering continuous care management.
4. Clinical Decision Support Software (CDSS)
Advanced CDSS offers healthcare professionals instant access to medication alerts, patient-specific recommendations, and evidence-based guidelines.
By integrating with EHRs, they offer safer and more personalized treatment plans. CDSS improves clinicians' decision-making by sharing crucial insights at the point of care. In addition, it optimizes clinical workflows and streamlines patient delivery.
How Maruti Techlabs Optimized Workflows for a Digital Insurance Platform?
One of our clients, Medigap Life, a Florida-based online insurance aggregator, faced challenges managing vast customer data due to rigid, interdependent workflows in its vTiger CRM. This led to performance issues and inefficiencies.
Our experts at Maruti Techlabs addressed this by migrating critical workflows to Apache Airflow, enhancing flexibility and scalability. They integrated real-time notifications from vTiger and implemented Twilio for efficient SMS communications.
This solution resulted in an 88% reduction in SMS campaign execution time and a 50% decrease in CRM page load times, enhancing decision-making with timely and accurate data.
Conclusion
Embracing data interoperability in healthcare is a necessity that offers significant benefits, including timely data exchange, enhanced scalability, security, and compliance.
Implementing microservices architecture is crucial for developing personalized, patient-centric, and connected healthcare ecosystems. It enables independent, modular services that enhance agility and responsiveness.
Healthcare organizations aiming to adopt microservices should begin by assessing their current infrastructure, investing in staff training, and collaborating with experienced technology partners who are experts in Microservice Architecture Development to ensure a seamless transition.
By taking these steps, organizations can position themselves to deliver more efficient, secure, and patient-focused care in an increasingly digital healthcare landscape. Get in touch with us today to start your transformation journey.
FAQs
1. How can interoperability in healthcare be improved?
Improve healthcare interoperability by adopting microservices, standardizing data formats (FHIR, HL7), using APIs for seamless integration, ensuring security compliance, and fostering collaboration between providers, tech firms, and regulatory bodies.
2. Why is interoperability important in healthcare?
Interoperability in healthcare enables seamless data exchange, improves patient outcomes, enhances efficiency, reduces errors, supports informed decision-making, ensures regulatory compliance, and fosters innovation in digital health solutions.
3. What are the 4 pillars of interoperability?
The four pillars of interoperability are foundational (basic data exchange), structural (standardized data formats), semantic (shared meaning of data), and organizational (policies, governance, and workflows ensuring seamless integration and use).
4. What is meant by data interoperability?
Data interoperability is the seamless exchange, integration, and use of data across different systems, ensuring accuracy, consistency, and accessibility for improved collaboration and decision-making.
5. What is the biggest challenge facing healthcare today?
The biggest challenge in healthcare today is ensuring affordable, accessible, and high-quality care while addressing interoperability, data security, workforce shortages, rising costs, and integrating advanced digital health technologies.
