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Data Sources
Patients can use personal wearables, connected with
a custom mobile (lifestyle or a companion mobile)
application to transfer data events. Other smart sensors
can optionally be connected to the mobile application.
Clinical Applications
Data can be ingested through various clinical applications
like Electronic Medical Records, health information
exchanges, and customer commercial applications.
Real-time Data Ingestion
The mobile application sends data and events to Amazon
Pinpoint, authenticating through Amazon Cognito.
Batch Data Ingestion
Data replication from relational database sources is
performed through AWS Database Migration Service.
AWS Batch is used to consume data from public/private
APIs. AWS DataSync is used to automate data movement
from on-premises storage to Amazon Simple Storage
Service (Amazon S3). AWS Glue is used for managed
ETL and process the incoming data.
Data Preparation
AWS Lake Formation is used to set up a centralized,
curated, and secure repository in days, for storing raw and
curated data.
Storage and Archival
Amazon S3 acts as the central storage layer and
leverages life cycle policies to move data to Amazon S3
Glacier for archival purposes, saving costs.
Data Analytics and Visualization
Amazon Redshift is used as a data warehouse to store
curated data. Semi-structured and unstructured data can
be processed by Amazon EMR and Amazon Athena is
used for ad-hoc querying. Amazon SageMaker is used
to build custom ML driven predictive models to drive
effective outcomes. Amazon Quicksight provides a rich
visualization layer.
Event Driven Tasks and Alerts
Amazon DynamoDB and AWS Lambda are used for
hosting a rules engine to drive effective outcomes.
Custom machine learning models can be used to
automatically create rules which can be reviewed by a
team of care coordinators. Amazon Pinpoint is used to
deliver on demand messages to patients through email,
SMS, push notifications, and voice technology.
Digital therapeutics and precision medicine
AWS reference architecture
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