HeartAI

Ecosystems to support digital health

  • Comprehensive data integration
  • Real-time information systems
  • Continuous audit and assurance
  • High-performance analytics
  • Security everywhere
  • Always-on observability
  • Scalable infrastructure
  • Highly-available systems
  • Clinical decision support
  • Medical artificial intelligence
HeartAI montage
About HeartAI

HeartAI


HeartAI is a modern digital platform with best-practice implementations for data, information, and analytics. These capabilities are positioned to support the contemporary digital health ecosystem, and include support for real-time data availability, rigorous health information systems, and operational readiness suitable for both system-wide digital health and the clinical point-of-care. This includes extensive data integration, data processing, quality assurance and audit, platform and service capabilities, and research-grade analytics.


HeartAI is grateful for a maturing relationship with SA Health and has continued to collaborate with major implementation projects such as the SA Virtual Care Service. This has required significant efforts to ensure that HeartAI complies with SA Government and SA Health policies regarding the management of HeartAI as a digital system within the government and health environments. The current HeartAI deployment within South Australia provides a robust data services model that reconciles data from many sources including the statewide electronic medical records (EMR). HeartAI has implemented real-time observability and intelligence at the interface between ambulance and hospital services, including the development of a clinical information system and a suite of solutions to assess and understand patient flow.


The HeartAI team hopes to mature as core technology providers in partnership with the healthcare system, academia, industry, and the greater community.


HeartAI schematic

Supporting digital health


HeartAI hopes to support health system care by increasing the capabilities and capacities of digital health. HeartAI ecosystem development achieves this by providing modern approaches to resource management, platform orchestration, security implementations, data integration and access, reporting and visualisation, powerful and real-time analytics, and many opportunities to support clinical service delivery and health system management.

Platform


HeartAI is primarily a cloud-native reactive microservices architecture that is orchestrated with Microsoft Azure cloud resources and the Red Hat OpenShift container platform. These capabilities are enhanced with best-practice deployments for extensible software-defined networking, modern identity and access management, real-time logging, monitoring, and observability, modern service middleware, high-performance analytics, and robust deployment frameworks.

HeartAI platform Grafana example
HeartAI platform Kibana example

Software


HeartAI implements a variety of contemporary software solutions. This includes software to support cloud environment management, container orchestration platforms, logging and monitoring capabilities, identity and access providers, and software-defined networking, among others. The following documentation provides an overview and reference to these technologies within HeartAI ecosystems generally:

HeartAI software SAVCS Argo CD example
HeartAI software SAVCS Kiali example

Services


HeartAI services are core middleware implementations that support general digital functionalities. This includes service capabilities such as data interfacing, data processing, data linkage, and data aggregation and reporting. These services are also foundational in bringing together additional HeartAI capabilities, such as infrastructural, analytical, and application software. Corresponding service functionalities are typically deployed with well-defined and secure application programming interfaces that provide a standardised way for users to interact with service endpoints.


HeartAI services often implement reactive microservices architectures, follow concepts from The Reactive Manifesto, and benefit from modern design concepts such as reactive design patterns and event-driven architectures. Services often represent corresponding domain models, for example the HIB interface service implements domain functionality for the HeartAI interface with the SA Health Health Information Broker (HIB). HeartAI service implementations provide high-performance extensions to the digital ecosystem, supporting comprehensive data integration, data-streaming, and high-availability.


HeartAI services SAH API endpoints
HeartAI services SAVCS API endpoints

Applications


HeartAI applications provides users with interactive software with capabilities for clinical operations, situational awareness, health record management, and generalised reporting and visualisation. These applications readily integrate with health information systems and corresponding data services, allowing rigorous and real-time information to be accessible and operationalised. Thoughtful application design has allowed HeartAI applications to be well-managed at scale and rapidly adaptable to support health system needs. Additional support exists for data streaming and event-driven behaviour, allowing continuous engagement with clinically important information and activity.

HeartAI applications SAVCS overview
HeartAI applications SAVCS timeline

Analytics


Evolving approaches with probabilistic programming and computational statistics are promising powerful methods to define and create analytical systems. These methods can represent probabilistic models under a variety of conditions and constraints, and are capable of simulating new data from these states by the generative nature of these models. HeartAI deployments supports inference from a Bayesian perspective, such as by generating samples from a prior or posterior predictive distribution, where there may also be a conditioning or marginalisation of such a distribution. In addition to the creation of a representative probabilistic construct, these models may be used for the generation of new data under a variety of assumptions and hypothetical situations, and allow for the prediction and forecasting of future events and potential outcomes.


Supporting the SA Virtual Care Service, HeartAI has developed a variety of probabilistic approaches that model the service activity generally and specifically to support personalised patient care. This includes the creation of models for admissions to the service over time, including the patient population of admissions, the likelihood of potential outcomes for the individual patient, and the length-of-service for each episode of care.

HeartAI analytics example
HeartAI analytics example

Projects


HeartAI proposes to support the South Australian digital health system with an evolving ecosystem 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 are progressing with the following current exemplar project initiatives:

Development


HeartAI developers are supported with development environments that encourage a positive and productive development experience. HeartAI instances are deployable to a developer’s local machine with automated installation steps, and these instances are secure, lightweight, and reproducible. The HeartAI development environment is designed to be modular, with developers deploying corresponding components to support their development objectives and use-cases. This typically includes integrated development framework components, such as Git, Git LFS, Docker Engine, and Docker Compose, such that the developer may interact with the HeartAI source respository. These integrated deployment components also support pre-declared software module packaging and deployment and a variety of backing services including logging, monitoring, networking, database, and identity services.


In addition to local machine installations with a wide-variety of configuration options, HeartAI instances also deploy to Red Hat OpenShift with particular support for managed Microsoft Azure Red Hat OpenShift environments.

HeartAI GitHub home
HeartAI GitHub network

Policy


HeartAI operates in a variety of digital environments, including through engagement with health and government organisations. HeartAI is committed to maintaining a high-level of rigour and due diligence, particularly considering the responsibilities of managing potentially sensitive digital health information. To ensure commitment to these principles, HeartAI abides by an internal policy framework that governs how HeartAI must operate and the corresponding obligations of team members and collaborators. These commitments include an understanding of and alignment to state and federal laws, policies, regulations, and compliance standards.

Community


The HeartAI team have matured positive and productive relationships with key stakeholders locally within South Australia, nationally, and internationally. These engagements support the development of an ecosystem that hopes to bring together digital health, academia, industry, and the greater community.


Many friends and colleagues have supported the development of HeartAI. The HeartAI team are thankful and grateful for these relationships.


HeartAI v0.33.0
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