How healthcare startups are building a modern data platform using AWS

AWS experts and customers share insights into using the platform to make the best use of data for modern healthcare purposes.
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The entry of private players in healthcare services has put the spotlight on digitising health records. From medical reports to insurance claims and health history, most of the data is unstructured and unorganised. To streamline and make the best use of this data, AWS provides a cloud platform with state-of-the-art features and 360-degree support.

AWS in association with YourStory hosted a webinar on the theme ‘Building modern healthcare data platform on AWS’ focused on helping healthcare providers with tips and techniques to streamline healthcare data and build an advanced platform with the help of AWS.

Held on December 9, 2021, the 90-minute session included exclusive AWS customer testimonials where AWS experts and customers discussed various use cases of AWS’ data platform. Ajay Tiwari, CTO, HealthKart spoke at length on ‘Building real-time analytics pipeline using AWS’ and Shafeeq Ahmed, Director - Data & Infrastructure, Mfine shared his expertise on ‘Secure and scalable healthcare services on AWS’.

Building a data platform for personalisation

With over 3 million monthly users, HealthKart is a leading D2C sports nutrition company. Talking about how the company leveraged AWS’ platform, Ajay explained, “As an omni-channel D2C brand, we have to take special care of personalisation for our customers. From real-time analytics to pushing relevant offers, a lot of our business depends on how we collect huge data and process it in real-time.”

HealthKart opted for Amazon Pinpoint services to use as a data platform because they found it the most cost-effective as compared to other services. “There was no monthly minimum payment contract as payment is purely based on the events consumed. Moreover, the first 100 million events are free of cost,” shared Ajay.

“AWS also provided us with an SDK to help with features like capturing session count, page views, and number of unique users,” he added.

Ajay explained the detailed architecture implementation of AWS Pinpoint services. The AWS Pinpoint setup enabled HealthKart to add new application groups, use data to create segments, process data to personalise services, and much more.

A low-cost storage platform

MFine is a startup making health consultations accessible on the go. For those with hectic schedules, the MFine app enables you to consult a doctor from any location or situation.

The platform is scaling at the rate of 20 percent every month and uses real-time data analytics to reach out to a wide number of customers. Shafeeq, while explaining the need for a data platform, said, “The platform helps us derive insights from the data and it reduces dependencies on the data team. It enables self-service for a diverse range of users. Moreover, it allowed us to build a real-time data warehouse.”

Mfine leveraged big data concepts to build a low-cost data storage platform. AWS services like Amazon S3, Amazon Athena, presto etc were used to build analytics dashboard and day-to-day business operations.

AWS experts were present throughout the session to answer queries in regards to building a modern data platform using their services. Healthcare providers and data enthusiasts were able to interact, learn, and gain valuable insights.

Healthcare Data Lake

Kousik Rajendran, Solutions Architect, Healthcare and Life Sciences Specialist, AISPL spoke at length about building a healthcare data platform. Explaining how a simple data lake can look like, Kousik says, “Healthcare data platform is built by ingesting data using standardized formats like FHIR®, custom formats, and securely stored into centralized data lake like Amazon S3.” He further added, “It is crucial for healthcare organization to adapt standard formats like FHIR® which is recommended by Ayushman Bharat Digital Mission (ABDM)”

“Lake House architecture on AWS enables our customers to connect Data Lake, Data Warehouse and other data services. Lake House approach consists of scalable Data Lake using Amazon S3 as central storage. It also leverages Relational Databases like Amazon RDS, purpose-built data services like Amazon DynamoDB. Lake House facilitates seamless data movement, unified governance and performance while keeping cost optimized.”

Once data is stored and processed, it caters to various use cases such as real-time monitoring, disease prediction, unified governance by leveraging seamless data movement.

In the webinar, Kousik talks in detail about how AWS can help healthcare providers build a secure and scalable data platform at the same time.

On the process of signing up for training with AWS as a healthcare provider, Abhinav Jain, Client Relationship Manager, AISPL says, “There is a generic data analytics platform learning path available. It is a 17-hour comprehensive course at no cost. Healthcare platforms can follow this link to take up training for the same.” https://aws.amazon.com/health/


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