John presents Pathling, Apache Spark implementation of ViewDefinition runner. John shows demo of real-time analytics using FHIR subscriptions, Pathling and Spark streaming, with live-dashboards on PostgreSQL & Superset.
Pathling utilizes Apache Spark to facilitate scalable, distributed processing of FHIR data and streaming features via multiple programming languages (such as Java, Python, R). This allows for innovative architectures in FHIR processing for analytical purposes. We will explore several methods for establishing this capability in conjunction with operational systems and integrating it with current analytics and business intelligence tools.
Pathling leverages Apache Spark to enable scalable, distributed processing of FHIR data and streaming capabilities through multiple language interfaces (e.g. Java, Python, R). This enables interesting architectures for processing FHIR for analytic use cases, and we will cover various ways that this capability can be set up alongside operational systems and integrated with existing analytics and business intelligence tools.
John is an engineer and researcher working at the intersection of standards and health data analytics at CSIRO, the Australian national science agency. He is the primary contributor to Pathling, a set of tools for using clinical terminology and FHIR with Apache Spark and a member of the FHIR Analytics collaborative and a key contributor to the SQL on FHIR project
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