For more information on Real World Evidence and other ways AWS can help your organization,visit us at:
https://aws.amazon.com/health
STEP 1: User initiates a query on a dataset. In the context of Real
World Evidence, this is largely analyzing a cohort in the context of
a specific indication (drug response, etc)
STEP 2: AWS Step Functions invokes an AWS Lambda function
to query the Data Catalog and build a manifest of data
STEP 3: The manifest is passed to a subsequent Lambda
functions, which orchestrate the data analysis through different
AWS services
STEP 4: These analyses may include Amazon EMR for
population-scale genomics, Amazon EC2 for high-performance
computing and machine learning, and/or Amazon Redshift for
your healthcare data warehouse
STEP 5: Results from each analysis is stage back in Amazon S3
and logged in the data catalog
STEP 6: Business intelligence tools, such as Amazon Quiksight or
Tableau, or data analysis workbooks, such as Jupyter, can query
Amazon S3 to visualize results, such as through Amazon Athena
Amazon
Elasticsearch Service
Amazon EMR
AWS Lambda
AWS Lambda
Amazon DynamoDB
Amazon Athena
Amazon EC2
Amazon S3
Amazon
Redshift
4
4
4
3
2
1
Amazon API
Gateway
AWS Step
Functions
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5
5
6
Data Consumption
Real World Evidence (RWE)
Using AWS Services
