By Sujit Singh, Partner Solutions Architect – AWS
By Gitika Vijh, Senior WW Data & 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
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| Impetus Technologies |
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The healthcare industry is evolving at a rapid pace, and so is the complexity and volume of the data it generates. It is estimated that around 30% of the world’s data volume is being generated by the healthcare industry. Imagine the possibilities if this data were effectively harnessed! Doing so could significantly enhance patient care and operational efficiency, and even save lives.
Such data-driven insights empower healthcare professionals, patients, and data consumers to provide better patient care, diagnose hidden health issues, promptly adjust treatment plans, and expedite insurance claims. This isn’t a distant future; it’s possible today with a robust data platform.
An effective data platform can save the healthcare sector millions of dollars in research and operational expenses. Moreover, it enables efficient collaboration with partners and vendors, building a strong reputation in the healthcare market, which could be a game-changer for improving patient care and operational efficiency if channeled effectively.
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 involves overcoming obstacles like data silos, interoperability issues, and privacy concerns. Addressing these issues is crucial to avoid delays in patient care, operational inefficiencies, and stifled innovation.
Data Silos: Healthcare organizations consist of various departments, systems, and business units that hold information in isolation. This restricts open collaboration between these systems and a comprehensive data view, hindering operational efficiency, innovation, and patient care.
Interoperability in Data Processing: Healthcare data is diverse, ranging from structured to unstructured formats. Different systems and applications generate data in various formats and versions, such as Health Level Seven (HL7), American National Standards Institute X12 (ANSI X12), and Fast Healthcare Interoperability Resources (FHIR). This data variety creates interoperability problems, such as issues related to sharing and exchanging healthcare data among systems.
Meeting Data Privacy and Security Requirements: Healthcare data is highly sensitive, and organizations must prioritize privacy and security to meet compliance and governmental 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: Healthcare data platforms must adhere to compliance laws such as Health Insurance Portability and Accountability Act (HIPAA) and General Data Protection Regulation (GDPR), in addition to ensuring data security and privacy.
Scalability and Performance Concerns: Healthcare data platforms must be highly scalable and performant to meet the ever-increasing data volume and real-time data processing demands.
Consequences of Unresolved Data Challenges: What’s at Stake?
Failure to address the challenges in managing healthcare data can lead to:
- Delayed patient care
- Increased operational overheads and manual interventions
- Stifled innovation efforts
Solve Your Healthcare Data Complexities with a Healthcare Data Platform
Impetus Technologies, with its deep expertise in AWS, data and cloud engineering, analytics, and AI/ML, offers a holistic solution to the challenges faced by the healthcare industry. With extensive experience in consulting and architectural 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 the Healthcare Data Platform
The Healthcare Data Platform is built on core principles such as efficient data ingestion, data access and utilization, interoperability, compliance, scalability, security, and data normalization.
Efficient Data Ingestion: The platform supports bulk uploads for batch use cases, real-time streaming, and ingesting data from external APIs.
Interoperability: The platform works with widely accepted healthcare standards like HL7, FHIR, and Digital Imaging and Communications in Medicine (DICOM), ensuring seamless data exchange.
Compliance and Governance: The platform adheres to AWS’s well-architected framework and HIPAA guidelines, ensuring data privacy through Identity & Access Management (IAM) and stringent security protocols.
Data Access and Utilization: A centralized data lake acts as a single source of truth, supporting querying, processing, and analytics, thus preventing data silos. The platform also supports machine learning, analytics, and search capabilities, as well as data export using APIs.
Scalability: The storage is designed to accommodate the ever-growing data, and the processing layer is designed to scale elastically in tandem with the workload.
Security, Privacy, and Auditing: The platform ensures data encryption at rest and in transit, governed by role-based access control (RBAC) policies. It logs and monitors all activities for audit trails.
Data Normalization: The platform standardizes and cleanses data attributes, creating organized FHIR resources for reporting, analytics, and ML pipelines.
Tailored Healthcare Data Solutions: A Flexible, Plug-and-Play Approach Overview
Impetus’s Healthcare Data Platform is based on a plug-and-play architecture that allows for building customized and tailored solutions for any healthcare organization, based on their specific business requirements.
Key Components of the Healthcare Data Platform
The platform is designed to provide all the essential capabilities of a data platform, with the following major components:
Figure 1: Key components of the Healthcare Data Platform
Architecture:
Figure 2: Solution overview of the Healthcare Data Platform
- Data Ingestion: Healthcare 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) acting as our Landing Zone. To start with, we have batch ingestion, (1a), where you can utilize services like AWS DataSync, AWS Transfer Family, and AWS Database Migration Service (AWS DMS) to move the data into the Amazon S3 bucket. Then we have HL7 ingestion (1b) that utilizes AWS Fargate containers which also act as HL7 message listeners. 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 helping with scheduled API-based ingestion (1d).
- Data Storage: Amazon S3 is the primary storage solution that is being used as the landing zone (2a), for metadata indexing, and storage (2b). The solution also utilizes AWS HealthLake (2c) for storing healthcare specific data and AWS HealthImaging (2d) for storing medical images.
- Data Import and Processing: The data is directly imported (3a) into HealthLake and HealthImaging. The processing and conversion (3b) of any unsupported format is carried 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 disease detection through analytics and operational cost reduction via 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 healthcare industry compliance.
- Logging and Monitoring: AWS CloudTrail is used for API call logging and Amazon CloudWatch is used for real-time metrics and monitoring.
Conclusion
The timely availability of healthcare data is crucial for patient care and organizational growth. Impetus unified data platform addresses the challenges of data silos, scalability, security, and compliance and helps healthcare providers to stay competitive.
Impetus Technologies , an Advanced AWS Consulting Partner, brings unparalleled experience in healthcare cloud and data platform engineering. Impetus helps healthcare organizations achieve transformational growth by designing and implementing robust data solutions. If you would like to learn more Impetus Healthcare Data Platform, please send an email to inquiry@impetus.com. You can also contact Impetus at https://www.impetus.com/about/contact/.
Impetus Technology – AWS Partner Spotlight
Impetus is an AWS Premier Tier Services Partner who enables the Intelligent Enterprise
with innovative data engineering, cloud, and enterprise AI services. By helping enterprises modernize workloads and leverage cutting-edge AWS technologies, Impetus empowers businesses to innovate, streamline operations, and unlock new opportunities.
Contact Impetus | Partner Overview | AWS Marketplace
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