In the context of HealthTech platforms, scalability refers to the ability of the platform to accommodate growth and increased demand while maintaining performance, reliability, and efficiency. A scalable HealthTech platform can seamlessly handle growing numbers of users, data volumes, and transactions without experiencing significant degradation in performance or service quality. This scalability enables HealthTech platforms to effectively support a larger user base, expand into new markets, and adapt to evolving healthcare needs without compromising functionality or user experience. In today’s post-COVID healthcare climate, preparedness for the unprecedented is no longer a bonus, but a necessity, making scalability a must-have feature of any new medical startup.

Let’s take a closer look at why investing in scalability when building your HealthTech platform is a good decision.

• Meet Growing Demand. As HealthTech solutions gain popularity and adoption increases, the demand for these platforms grows. Scalability ensures that companies can handle this increased demand without compromising performance.
• Adapt to Market Changes. The healthcare industry is constantly evolving. Scalable platforms can adapt to these changes quickly and help companies to meet the needs of their customers.
• Cost-Efficiency. Scalability enables companies to optimize resource utilization and minimize costs. Instead of over-provisioning resources to handle peak loads, scalable platforms can dynamically allocate resources based on demand, resulting in more efficient use of infrastructure.
• Facilitate Innovation. Scalable platforms provide a solid foundation for innovation and experimentation. Companies can quickly deploy new features, test new ideas, and iterate based on user feedback without being constrained by limitations in scalability.
• Attract Partnerships. Investors and potential partners often look for scalability as a key factor when evaluating tech companies, and HealthTech startups are no exception. A scalable platform demonstrates the company’s ability to grow and adapt, making it more attractive for investment and collaboration opportunities.
• Enhancing User Experience. A scalable platform ensures that users have access to reliable and responsive services, even during periods of high traffic or increased demand. This enhances user satisfaction and builds trust in the platform, leading to user loyalty.

As the modern healthcare faces the necessity of digitalization, scalability, too, gradually becomes a baseline expectation rather than a perk. After all, if you are already committing to building a HealthTech platform, why not make it scalable from the start?

So you decided to build a scalable platform. How does one go about that? Foster Capital remarked on the necessity of a holistic interdisciplinary approach to scalable platform development. With this in mind, we’ve compiled a step-by-step guide on how to design scalable HealthTech architecture:

1. Begin by identifying the key components and services that make up the HealthTech platform. This can include everything you deem important in the upcoming platform: user interfaces, application logic, data storage, analytics, security, integrations with external systems, and more.
2. Decouple components of the architecture. The traditional most common infrastructure is also known as “coupled”. Tiiny Host article describes how for Content Management Systems (CMS), the “couple” is the unity of backend and frontend that serves to “manage both the content and the presentation of that content”. A change in one component will trigger incongruities in the other, so you will need to alter both components even when intending to change just one. To increase scalability, you need to design your system with components or services that are independent of each other from the start. This will minimize dependencies and enable independent scaling. Adopt a microservices architecture, where each component is developed as a separate service with its own codebase, data store, and communication protocols.
3. Leverage cloud services and infrastructure to achieve scalability and flexibility. Cloud providers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform offer a wide range of scalable services, including compute, storage, databases, and analytics. We will get into the best tools for scalable platform development later.
4. Implement Horizontal Scaling. Horizontal scaling involves adding more instances of a component, such as servers or databases, to distribute the load and enhance capacity. This contrasts with vertical scaling, which increases the capacity of a single instance. For maximum scalability, design the architecture to specifically support horizontal scaling and use load balancers to distribute incoming traffic across multiple instances of services.
5. Choose appropriate data storage solutions based on the nature of the data and scalability requirements. Consider using NoSQL databases like MongoDB or Apache Cassandra for flexible, horizontally scalable data storage, or traditional relational databases with sharding and partitioning capabilities. Sharding splits the database across multiple servers, each holding a subset of the data. Partitioning divides a single database into segments based on certain criteria (e.g., range, list, hash), making queries faster and more efficient by allowing access to specific data segments instead of the entire dataset.
6. Cache frequently accessed data. Implement caching mechanisms to improve performance and reduce latency for frequently accessed data. Use in-memory caches like Redis or Memcached to store frequently accessed data closer to the application for faster retrieval.
7. Implement Asynchronous Processing. Asynchronous processing allows tasks to run independently of the main program flow, enabling the system to handle other operations while waiting for the task to complete. Use it for tasks that can be offloaded from the main application flow. Implement message queues and background processing systems to handle tasks such as data processing, notifications, and long-running operations without blocking the main HealthTech platform.
8. Implement monitoring and auto-scaling capabilities to dynamically adjust resource allocation based on demand. Use monitoring tools to track key performance metrics and trigger auto-scaling actions to provision or de-provision resources as needed.
9. Design the architecture to be fault-tolerant and resilient to failures. Invest in failover mechanisms and distributed architectures to minimize the impact of failures and ensure continuous availability of critical services.
10. Regularly review and refine the architecture based on performance metrics, user feedback, and evolving requirements. Continuously optimize the architecture to ensure it remains scalable, efficient, and aligned with the needs of the HealthTech platform.

The price of poorly designed platform is user dissatisfaction, damaged reputation, and lost opportunities, but we have already established that scalable platform development is no easy feat. It is advisable to get some help from time-tested solutions that will simplify and accelerate the process.

Cloud environments are ideal for scalable platform development because they offer flexible resource allocation, allowing developers to easily scale up or down based on demand. They provide cost-efficiency through pay-as-you-go models, reducing the need for upfront infrastructure investment, and give developers access to an enormous treasure trove of additional services. The leading cloud providers on the market are AWS, Azure, and GCP.

• Amazon Web Services (AWS) offers a wide range of scalable services like EC2 for computing, S3 for storage, and RDS for managed databases. Read our recent article to find out more about the data security for HealthTech cloud deploymemt that AWS provides.
• Microsoft Azure provides services for computing, analytics, storage, and networking, along with strong integration with Microsoft products.
• Google Cloud Platform (GCP) is known for its machine learning capabilities, Kubernetes support, and data services like BigQuery.

Containerization simplifies your HealthTech platform and app deployment by packaging software and its dependencies into isolated containers, ensuring consistency across environments. Orchestration tools manage these containers, automating deployment, scaling, and management tasks. This combination enhances scalability by allowing seamless distribution and replication of containers across multiple servers. In terms of specific solutions, Docker is a popular choice for containerization, while Kubernetes dominates orchestration.

• Docker simplifies application deployment by containerizing applications and their dependencies. It provides a platform to create, deploy, and manage containers themselves, but later integrates with Kubernetes to manage the apps inside the containers.
• Kubernetes is an orchestration platform for containerized applications across clusters of machines. It automates their deployment, scaling, and management.

Microservices frameworks improve scalable platform development by decomposing applications into independent, loosely-coupled services, each handling a specific function. This approach allows individual services to be scaled independently, enhancing flexibility and resilience. It enables teams to use diverse technologies suited to each service, streamlining updates and maintenance.

• Spring Boot is a Java-based framework for building microservices that are easy to deploy and scale.
• Django and Flask (Python) are popular frameworks for building scalable web applications with RESTful APIs. RESTful APIs work by using standard HTTP methods (GET, POST, PUT, DELETE) to enable communication between clients and servers. Clients send requests to specific endpoints, and servers respond with the requested data or perform actions. This stateless interaction ensures simplicity, scalability, and easy integration.
• Node.js with Express enables building scalable network applications using JavaScript on the server side.

Message queues and streaming platforms facilitate communication between components by storing and forwarding messages. Queues maintain message order and ensure reliable delivery, while streaming platforms handle continuous streams of data. Clients produce messages to topics or queues, and consumers subscribe to these topics to receive messages asynchronously. This decouples sender and receiver, enabling scalable, fault-tolerant healthcare systems. They improve scalable platform development through this asynchronous communication between components that creates a smooth data flow.

• Apache Kafka is a distributed streaming platform capable of handling large-scale message processing and real-time data feeds.
• RabbitMQ is a message broker that supports complex routing and has plugins for extended functionality.

In HealthTech development API Gateways serve as a single entry point for user requests. They direct these requests to backend and streamline communication between clients and services. They can be described as a type of digital middleman or a receptionist, connecting clients to a group of backend services. This process contributes to even distribution of resources and therefore simplifies scalability management.

• Kong is an API gateway that provides features like load balancing, logging, monitoring, and authentication.
• Amazon API Gateway easily creates, publishes, maintains, monitors, and secures APIs at any scale.

Load balancers distribute incoming traffic across multiple servers, preventing overload on any single server and improving scalability. Reverse proxies handle client requests on behalf of servers, shielding them from direct client connections and providing additional security features like SSL termination. Together, they enhance the overall scalability of a platform by efficiently managing traffic and reducing server load.

• Nginx is widely used as a web server, reverse proxy, load balancer, and HTTP cache.
• HAProxy is a reliable, high-performance load balancer for TCP and HTTP applications.

Content Delivery Networks (CDNs) cache content on edge servers (ervers that store and deliver content closer to end-users and minimize the distance data needs to travel) distributed globally, traffic from origin servers. By serving content from the nearest edge server to users, CDNs improve performance and scalability. They also mitigate traffic spikes and distribute load, enhancing the platform’s ability to handle increased demand.

• Cloudflare provides CDN services, DDoS protection, and security features to ensure fast and secure content delivery.
• Akamai offers comprehensive CDN solutions with a focus on performance and security.

Building a scalable platform has its difficulties, but building a scalable HealthTech platform specifically adds an overlap of technological challenges and health and patient-specific concern. Here’s a list of factors you should consider during the development process.

• Healthcare systems often have complex and diverse requirements. Managing these complexities while designing a scalable architecture can be challenging.
• HealthTech platforms generally serve diverse user groups, including healthcare providers, patients, administrators, insurers, and researchers. If you want to design a platform that caters to the needs of all these stakeholders while ensuring scalability, the development process is likely to be long and complex.
• Compliance with strict requirements for data privacy and security is a must in the world of medicine. Building a scalable platform that complies with these regulations requires careful planning and implementation.
• Healthcare platforms deal with large volumes of sensitive data, the complexity of which can be too much for regular IT infrastructures. Handling it requires robust data management practices and technologies that agree with scalable infrastructure.
• Your platform may need to integrate with existing systems and interoperability standards to exchange data seamlessly across different healthcare settings. Ensuring interoperability while designing a scalable platform can be challenging due to disparate systems and standards.
• Building a scalable platform often requires significant resources, including time, expertise, and investment. Startups and smaller organizations may face resource constraints that make it difficult to build and maintain a scalable platform.
• Scalable HealthTech platforms often involve complex technologies, architectures, and infrastructure. Managing this technological complexity while ensuring scalability will take skilled and experienced professionals.
• Healthcare is a rapidly evolving industry with changing requirements and market trends. Designing a scalable platform that can adapt to these dynamic changes requires flexibility and agility.
• At the end of all of these challenges lies a risk of over-engineering a scalable platform by introducing unnecessary complexity or over-optimization. Finding the right balance between scalability, simplicity, and maintainability is crucial to avoid over-engineering.

HealthTech platforms need scalability. By design, the healthcare industry is meant to accommodate the ever-increasing numbers of patients, and to grow along with the technological progress. As we see the steady increase in digitalization of medical services, healthcare providers face the need to ride this wave and adapt to the changing landscape. The process might be tedious, but the end result will be modern technology, satisfied users, and a slightly less strained healthcare system.

Innovecs is currently growing its expertise in HealthTech development, and we appreciate any and all contributions. If this article has inspired you to expand or inquire, feel free to reach out. Our experts will gladly answer your questions or schedule an interview to quote you in one of our next articles.