HeartAI proposes to support the South Australian digital health system with a maturing platform implementation and deployment, with functionalities for real-time data integration and processing, adaptive and intelligent data linkage, dynamic and interactive data reporting, powerful modern analytics, and user-interfacing applications and dashboards. The HeartAI team also propose to enable exemplar project implementations, with the following projects progressing with active development:

HeartAI implements best practice solutions for systems that are extensible, scalable, reactive, performant, secure, resilient, and tolerant to failure. In relation to the eHealth Strategic Plan 2016-2020, the following HeartAI approaches align with SA Health Digital Strategy:

  • Interoperability with legacy systems through generic and extensible interfacing with existing health data resources.
  • Modern and scalable methods to share digital information, allowing greater collaboration with the health system and health system users.
  • Secure and transparent systems that follow best practice implementations with data security, privacy and confidentiality, and process documentation.
  • Implementation projects that support patient needs, supporting health system care and reducing unnecessary patient burden.
  • Improved efficiency and effectiveness of clinical care through enhanced clinical informatics, improved health system resource usage, and innovation with digital system capabilities and capacities.
  • Systems that support the continuity of care through improved integration with clinical practice.

Development of HeartAI considers modern architecture and principles following best practice concepts and implementations. HeartAI provides:

  • Dynamic and adaptive system components that are containerised and virtualised, allowing reproducible, scalable, maintainable, and modular systems that are readily deployable on many systems, including cloud and on-premises distributed clusters.
  • Implementation solutions that follow best practice methodologies for agile, maintainable, and scalable systems. The deployment to Microsoft Azure and Microsoft Azure Red Hat OpenShift represents an implementation strategy that follows best-in-practice hyper-converged technologies.
  • Highly available and resilient systems through the orchestration of system components with replication and delegation of responsibilities. System deployment with the OpenShift orchestration platform and the Akka actor-based concurrency system allows for decomposed and highly reliable systems.
  • Generic and extensible interfacing with existing health data systems, with the implementation of modern interfaces to these data systems, including thin-layer APIs and performant message buses.
  • Continuous logging and monitoring of environments operations at the system, network, data, information, security, service, application, and clinical levels. This provides ongoing and rapid observability and allow for system users and automated services to reactively respond to this information, such as by generating an alert or trigger a message to be sent to a device.
  • Rapid and scalable real-time processing of health system data, including write-side and read-side optimised data systems and natively distributable computational services.
  • Methods for data transmission that favour asynchronous and reactive data streaming with support for the Reactive Streams specification including support for non-blocking backpressure propagation.
  • Modern and robust security implementations that support authentication, authorisation, identity brokering, identity federation, encryption, credentialing, mitigation of denial-of-service, and real-time threat detection.
  • Powerful and modern analytics that follow best practices in computational statistics and artificial intelligence. The implementation of these analytics is developed with the Stan probabilistic programming language and allows for real-time analysis.
  • Modern data and analytics systems for general audit and monitoring, business and research support, and clinical support at the point-of-care.
  • A supportive and iterable development environment that provides unit- and behaviour-driven testing, continuous integration and development, software version control, and robust documentation.
  • An iterative and maintainable system that may support the South Australian health system in a way that is ongoing and evolving.