Accelerate healthcare insights with a healthcare data platform built on AWS

Sujit Singh, Partner Solutions Architect – AWS
by Gitika Vijh, Senior WW Data and AI Partner Solutions Architect – AWS
by Narendra Dubey, Senior Technical Architect – Impetus Technologies
by Deepak Motlani, Associate Architect – Impetus Technologies
by Kumar Gaurav, Senior Technical Architect, Impetus Technologies

Impetus Technologies

The healthcare industry is rapidly evolving, and the complexity and amount of data being generated is increasing. It is estimated that around 30% of the world's data That amount is generated by the medical industry. Imagine the possibilities if this data is effectively leveraged. Doing so can significantly improve patient care, operational efficiency, and even save lives.

These data-driven insights enable healthcare professionals, patients, and data consumers to provide better patient care, diagnose hidden health issues, quickly adjust treatment plans, and file insurance claims faster. You will be able to do this. This is not a story in the distant future. Today, a robust data platform makes that possible.

An effective data platform can save the healthcare sector millions of dollars in research and operational costs. Additionally, it allows you to collaborate more efficiently with partners and vendors and establish a strong reputation in the healthcare market. If leveraged effectively, this can be a game-changer in improving patient care and operational efficiency.

However, implementing an effective data platform for analytics and machine learning (ML) in the healthcare industry comes with its own set of challenges.

Are these challenges hindering your healthcare data management?

Managing healthcare data requires overcoming obstacles such as data silos, interoperability issues, and privacy concerns. Addressing these issues is critical to avoiding delays in patient care, operational inefficiencies, and stifling innovation.

Data silo: Healthcare organizations are made up of various departments, systems, and business units that keep information separate. This limits open collaboration and comprehensive data views between these systems, hindering operational efficiency, innovation, and patient care.

Interoperability in data processing: Medical data ranges from structured to unstructured formats. Different systems and applications generate data in different formats and versions, such as Health Level Seven (HL7), American National Standards Institute X12 (ANSI X12), and Fast Healthcare Interoperability Resources (FHIR). This data diversity creates interoperability issues, including issues related to sharing and exchanging health data between systems.

Meet data privacy and security requirements: Healthcare data is highly sensitive, so organizations must prioritize privacy and security to meet compliance and government requirements. Integrating multiple data sources while maintaining data security and privacy remains one of the biggest challenges in the healthcare industry.

Struggling to maintain industry compliance: In addition to ensuring data security and privacy, healthcare data platforms comply with compliance laws such as the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR). There is a need.

ScarabillCriticality and performance concerns: Healthcare data platforms must be highly scalable and performant to meet the demands of ever-increasing data volumes and real-time data processing.

Consequences of unresolved data challenges: What is at stake?

Unaddressed challenges in managing health data can result in:

Delays in patient care Increased operational overhead and manual intervention Stifling innovation efforts

Solve healthcare data complexity with a healthcare data platform

With deep expertise in AWS, data and cloud engineering, analytics, and AI/ML, Impetus Technologies provides comprehensive solutions to the challenges facing the healthcare industry. With extensive experience in consulting and architecture services, Impetus has designed a unified data platform specifically for the healthcare sector. This platform can enhance patient care, improve operational efficiency, and drive innovation.

Foundational Pillars of a Healthcare Data Platform

The Healthcare Data Platform is built on core principles such as efficient data ingestion, data access and usage, interoperability, compliance, scalability, security, and data normalization.

Efficient data ingestion: The platform supports bulk uploads for batch use cases, real-time streaming, and data ingestion from external APIs.

interoperability: The platform works in conjunction with widely accepted medical standards such as HL7, FHIR, and Digital Imaging and Communications in Medicine (DICOM). Ensure seamless data exchange.

Compliance and governance: This platform follows the AWS Well-Architected Platform. Framework and HIPAA Guidelines, Ensure data privacy through identity and access management (IAM) and strict security protocols.

Access and use of data: A centralized data lake prevents data silos by serving as a single source of truth to support querying, processing, and analysis. The platform also supports machine learning, analytics, and search capabilities, as well as data export using APIs.

Scalability: The storage is designed to handle ever-growing data, and the processing layer is designed to: Flexibly scale to match your workload.

Security, privacy and auditing: The platform is governed by role-based access control (RBAC) policies that ensure data encryption at rest and in transit. Log all activity and monitor audit trails.

Data normalization: The platform standardizes and cleanses data attributes to create organized FHIR resources for reporting, analytics, and ML pipelines.

Customized Healthcare Data Solutions: Overview of a Flexible Plug-and-Play Approach

Impetus' healthcare data platform is based on a plug-and-play architecture that allows you to build customized solutions for any healthcare organization based on specific business requirements.

Key components of a healthcare data platform

The platform is designed to provide all the essential features of a data platform and includes the following key components:

Figure 1: Key components of a healthcare data platform

Architecture:

Figure 2: Healthcare Data Platform Solution Overview

Data ingestion: Medical data is generated from disparate sources in a variety of formats. The platform leverages various AWS services and methods to ingest data from these sources into Amazon Simple Storage Service (Amazon S3), which acts as a landing zone. First, there is batch ingestion (1a), which allows you to move data to Amazon S3 buckets using services such as AWS DataSync, AWS Transfer Family, and AWS Database Migration Service (AWS DMS). Next, we have HL7 ingest (1b), which utilizes an AWS Fargate container that also acts as an HL7 message listener. Real-time and near real-time ingestion (1c) into the bucket is facilitated with the help of Amazon Kinesis Data Streams and Amazon Data Firehose. And finally, we have Amazon EventBridge and AWS Lambda to help with scheduled API-based ingestion (1d). Data storage: Amazon S3 is the primary storage solution used as a landing zone (2a) for metadata indexing and storage (2b). This solution also utilizes: AWS Health Lake (2c) to store medical-specific data; and AWS Health Imaging (2d) To store medical images.
Data import and processing: Data is imported directly into HealthLake and HealthImaging (3a). Unsupported format processing and transformation (3b) is performed by Amazon EMR or AWS Glue before loading the data into these services.

Data consumption: Analytics and machine learning AWS services Amazon Athena, Amazon QuickSight, and Amazon SageMaker enable early detection of disease through analytics and lower operational costs through data-driven insights (4a). HealthLake facilitates payer-to-payer (P2P) data transfer (4b). Additionally, HealthImaging powers the development of healthcare and diagnostic applications (4c). Security and Compliance: AWS Key Management Service (AWS KMS) is used for data encryption. HTTPS/TLS 1.2+ communication is used for secure connections. HIPAA-eligible AWS services are used for compliance in the healthcare industry. Logging and Monitoring: AWS CloudTrail is used for logging API calls, and Amazon CloudWatch is used for real-time metrics and monitoring.

conclusion

The timely availability of medical data is critical to patient care and organizational growth. The Impetus unified data platform helps healthcare providers stay competitive by addressing data silos, scalability, security, and compliance challenges.

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Impetus Technology – AWS Partner Spotlight