Building a Scalable Data Infrastructure for Healthcare

Healthcare organisations are investing significantly in advanced technology to extract valuable information from vast amounts of data. However, a whopping 80% of healthcare data remains unstructured and untapped.

The sector needs to create a scalable data infrastructure to address this challenge and boost efficiency. But why is scalability important? And how can we build a scalable data infrastructure for healthcare? Let’s find out.

Understanding Scalability in Healthcare

The healthcare system comprises data from millions of people. This ever-increasing number, coupled with an ageing population and the introduction of new medical technologies, can significantly burden the system. However, there aren’t enough doctors and medical professionals to meet these challenges.

As a result, healthcare organisations need to implement scalable solutions to optimise resources without compromising the quality of care.

How to Build a Scalable Healthcare Data Infrastructure?

Here’s a step-by-step guide to building a scalable healthcare data infrastructure:

• Identify Key Components

Start by identifying key components of the HealthTech platform. These include the user interface, data storage, integration with existing systems, etc.

• Decouple Components

Traditional systems often have tightly coupled components, where changes in one part also require adjustments in another. To create a scalable infrastructure, it’s essential to design the platform with independent components so each part of the system can be scaled without impacting other areas.

• Utilise Cloud Services

Leverage cloud providers like AWS or Microsoft Azure to access a variety of scalable tools and services. This will help you scale the platform seamlessly without needing physical hardware.

• Implement Horizontal Scaling

Implementing horizontal scaling instead of vertical allows you to distribute the workload across multiple servers and improves the system’s capacity to handle increased traffic and data.

• Choose the Right Data Storage Solutions

Opt for NoSQL databases like MongoDB, which provide flexible and scalable storage options.

• Implement Caching

Implement in-memory caching solutions like Redis or Memcached to store data closer to the application. This lowers the burden on the primary database, enabling quicker retrieval.

• Use Asynchronous Processing

Asynchronous processing enables the system to handle multiple tasks simultaneously. It can help optimise background tasks like data processing or sending notifications and run independently of the main application flow.

• Monitoring and Auto-Scaling

It’s essential to continuously monitor the platform’s performance for scalability. Use tools to track performance indicators and adjust your resources accordingly.

• Design for Fault Tolerance

While building a scalable infrastructure, it’s also important to ensure it is resilient to failures. So, design the system to be fault-tolerant to ensure it can continue running smoothly even if some components fail.

• Regular Review and Optimisation

Continuously review and refine the system to ensure it remains efficient and scalable with evolving demands.

The Future of Scalable Data Infrastructure in Healthcare

As the healthcare sector advances, building a robust and scalable data infrastructure has become more important than ever. It helps manage the growing patient load and enables healthcare providers to deliver quality care efficiently.

Looking to scale your healthcare system? Book a consultation with the experts at DCT. We offer specialised solutions to help you build a scalable, resilient infrastructure tailored to your needs.