Purposes and goals

Modern technological innovations are continuing to suggest promising approaches to the digital operations of contemporary health systems. These approaches are enabling the next generation of learning health systems, with technologies such as real-time data streaming, clinical decision support, and robust artificial intelligence powering novel and innovative supporting improvements to health system care. However, the implementation of these modern systems remains challenging, often requiring complex restructuring of technical capabilities and capacities. The HeartAI team propose HeartAI as a modern approach to these contemporary challenges, promising best practice implementations and insights to support the modern digital health system. HeartAI has the potential to impact many areas of the South Australian health system, including:

  • Innovation of the South Australian digital health system.
  • Development of modern and high-performance data and analytics systems.
  • Providing supportive environments for technical experts and professionals.
  • Supporting digital approaches to clinical service innovation and delivery.
  • Supporting medical management at the clinical point-of-care.
  • Data and analytics resources for clinical audit and research.
  • Rigorous and well-managed information systems.
  • Digital platform capabilities for the support of health system care.
  • Evolving organisation processes with ongoing review and improvement.
  • Governance processes that uphold legal and ethical considerations.
  • Culture and principles that foster a supportive organisational and team environment.

Supporting digital health

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

The following platform potentials provide a representation of HeartAI opportunities to support digital health:

Clinical service innovation

HeartAI has the potential to innovate many areas of clinical service delivery and care, with enhanced implementations that enable:

  • Clinical information systems
  • Clinical service unit evaluation *GGatient diagnostics support
  • Patient outcome prediction systems
  • Length-of-stay modelling
  • Service unit activity forecasting
  • Patient flow systems
  • Service unit demand modelling
  • Clinical resource and supply chain management
  • Health system capacity planning
  • Patient deterioration monitoring systems
  • Integration with observation machines and biomedical devices
  • Processing of clinical signals and high-throughput data

Strategic 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.

Project implementations

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:

SA Virtual Care Service

The SA Health SA Virtual Care Service (SAVCS) is a multi-disciplinary health system service initiative that will provide clinicians, health system administrators, and supporting communities with innovative capabilities and improved care delivery by providing an interface between health system services, including:

SAVCS includes metropolitan and regional health services and represents a system-wide approach to virtual care within South Australia.

The service aims to improve many areas of health system service delivery and care, by providing innovations with:

  • Increased access and availability of emergency services.
  • Enhanced delivery of care.
  • Expedited times to triage.
  • Care pathways that avoid unnecessary emergency department admissions.
  • Potential reductions in ambulance ramping time.
  • Integration with modern digital and information systems.
  • Continuous monitoring and operational capabilities.

SAVCS currently provides four operational care pathways:

  • Virtual Emergency Service

The Virtual Emergency Service (VES) enables a point-of-contact for SA Ambulance Service clinicians by providing live telehealth integration and supporting services. This allows real-time paramedic and emergency care to be delivered while ambulance services are on the scene with a patient. These capabilities support clinical decision-making and may offer alternative services for care delivery, such as care-in-place service delivery, helping to alleviate emergency department and inpatient admissions.

  • Rural Virtual Care Service

The Rural Virtual Care Service (RVCS) provides virtual and remote access to clinical services for regional and remote health services and patients with potentially urgent medical conditions, by enabling virtual specialist and advanced services to be delivered to these sites on the basis of health system need. In addition, RVCS also supports regional transfers to metropolitan hospitals, including appropriate site transfer planning and bed allocation.

  • Health Navigator service

The Health Navigator service (HNAV) provides additional support to ambulance and paramedic services through the integrated capabilities of SAVCS. Through this service, paramedic support and liaisons on-site at SAVCS connect with SAAS paramedic staff at the patient location, and provide additional guidance to the treating team. This process also enhances SAAS services by utilising EMR capabilities within SAVCS, creating a more holistic view of the patient journey with additional information about history, medical management, and health system engagement. SAAS staff on-site at SAVCS may also request a clinical consultation, where the patient will be transferred to a SAVCS clinical for review.

  • Clinical Telephone Assessment service

The Clinical Telephone Assessment (CTA) service provides enhanced and integrated clinical care for patients in residential care facilities. This service supports nursing staff located at these facilities with SAAS paramedic services delivered via telehealth from SAVCS, including registration into the EMR and integration with the general patient journey. Through this process, the patient may receive supportive care remotely, or where beneficial the SAVCS team can coordinate the organisation of an on-site paramedic response.

SAVCS initiated in December 2021, with a multidisciplinary team of ~50 staff, including clinicians, paramedics, nurses, administrators, technologists, and analysts. The operational unit for the SAVCS is based at the Tonsley Innovation District.

HeartAI has continued to support the SA Virtual Care Service with the provision of real-time and robust information systems, empowering service visibility and operations. This has enabled a broad variety of service measures to be continuously consolidated and made available for clinical operations and service evaluation. This has included the consolidation of service measures for:

  • Calls received by the service
  • Emergency department presentations and transfers
  • Inpatient admissions
  • Patients treated in regional health networks
  • Patient demographics
  • Direct ward admissions
  • Regional transfers
  • Triage information
  • Clinical presentations
  • Service decision-making and outcomes
Projects: SA Virtual Care Service

Further information about HeartAI support for the SA Virtual Care Service may be found with the following documentation:

HeartAI also provides operational and analytical support for the SA Virtual Care Service through modern front-end applications that are integrated with rigorous health information systems, allowing real-time data and information to be provided for the purposes of:

  • Insight and value from high-performance, real-time, and rigorous health data and information systems.
  • Operational constructs and practices that support rapid response to health system needs.
  • Real-time capable visualisation software with support for data streaming and event-driven behaviour.
  • Mature processes and practices to rapidly respond to clinically important information and activity.
Applications: SA Virtual Care Service

Further information about the HeartAI application for the SA Virtual Care Service application may be found with the following documentation:


To assist with the medical management of patients presenting to the emergency department with potential acute coronary syndrome (ACS), the RAPIDx AI project will integrate clinical care with validated real-time data and modern analytical methods to better support clinical decision-making and help establish the South Australian health system as an effective learning health system. The RAPIDx AI project will deploy an AI-based diagnostic algorithm for patients with potential Type I or Type II myocardial infarction (MI) and myocardial injury within the emergency departments (EDs) of six South Australian hospitals, and will provide protocolised recommendations for medical management of these patients. The RAPIDx AI project is administered by Flinders University, South Australia. The HeartAI system provides the digital platform to enable real-time data and analytical methods. In a supporting partnership with the RAPIDx AI project, Siemens will deploy the RAPIDx AI Clinical Interface Prototype to provide a robust interface at the clinical point-of-care. Modern analytical capabilities are developed in partnership with the Australian Institute for Machine Learning, University of Adelaide, South Australia.

Projects: RAPIDx AI

Further information about the RAPIDx AI project may be found with the following documentation:


The PHenotyping Outcomes for clinical Care, Quality, and Service (PHOCQUS) is an exemplar initiative of Health Data & Clinical Trials (HDCT), Flinders University, South Australia, to develop a modern data integration platform to enhance capabilities for clinical audit and research, service innovation, and operationalisation of digital implementations. The PHOCQUS project provides data system capabilities through an automated data retrieval and collation process by linking currently collected routine clinical health service for opt-out consenting patients under the custodianship of the involved institutions and clinical areas. These approaches will allow the development of digital phenotypes of a range of diseases and therapeutic care, patient co-morbidities, social determinants of health, and health service characteristics. HeartAI provides the platform implementation to support the PHOCQUS project, with a modern best-practice deployment of cloud infrastructure, high-performance data systems, and enhanced platform management and operation.

Projects: PHOCQUS

Further information about the PHOCQUS project may be found with the following documentation:


The South Australian Hospital Alerting Via Electronic Noticeboard (HAVEN SA) project aims to develop and implement digital solutions to support the medical management of deteriorating patients within South Australian hospital care environments. The project primarily aims to deploy modern real-time capable data and analytics systems to detect and respond to patients before the occurrence of serious adverse events. A comprehensive clinical, research, economic, and behavioural framework is proposed to support project implementation. This project is inspired by and implemented in partnership with the University of Oxford HAVEN project with adaptions for the South Australian health system. The HAVEN SA project is administered by (proposed) the South Australian Health and Medical Research Institute, South Australia, and the Central Adelaide Local Health Network, SA Health, South Australia. The HeartAI system provides the implementing platform for the project, powering modern and scalable data integration, secure and robust deployment operations, and platform approaches for analytical development.

Projects: HAVEN SA

Further information about the HAVEN SA project may be found with the following documentation:


The HeartAI command, operations, and analytics centre (HAI CAP) project proposes to establish modern command and operations centre capabilities that are integrated with rigorous health information systems and powerful analytics. These capabilities will be deployed both in systems and clinical environments to support the enablement of service delivery and innovation across the health system and at clinical point-of-care.

HAI CAP proposes to establish maturity across many core operations:

  • System operations
  • Network operations
  • Data and information operations
  • Security operations
  • Service and application operations
  • Clinical operations

By developing holistic operational capability, HAI CAP deployments address many of the challenges of current operationalisations of health system data. In particular, by supporting foundational platform-based approaches for development and deployment, the fundamental technical solution is deployable both for rapid response to business and clinical needs, while also supporting frameworks for long-term iterative improvement.

This continual innovation of foundational capabilities allows for health information services that are reliable and purposeful. The practical implementations of these approaches are command centre deployments that are highly-available, secure, powerful, and able to rapidly respond to health system need.

HAI CAP supports modern health system operations, innovating healthcare services with:

  • Observability over platform operations.
  • Insight and value from high-performance, real-time, and rigorous health data and information systems.
  • Operational constructs and practices that support rapid response to health system needs.
  • Real-time capable visualisation software with support for data streaming and event-driven behaviour.
  • Mature processes and practices to rapidly respond to clinically important information and events.

A flagship implementation of HAI CAP supports the operational and analytical development of the SA Health SA Virtual Care Service, a multi-disciplinary service at the Tonsley Innovation District that will provide clinicians with visibility and operational capabilities across the South Australian health system.

Projects: HAI CAP

Further information about the HAI CAP project may be found with the following documentation:

Architecture and design principles

HeartAI development considers modern architecture and principles that follow best practice concepts and implementations from systems architecture, solution engineering, and software design. These capabilities allow HeartAI to deliver important platform qualities that support the rigour expected across digital health generally. Many of these architecture and design principles may be considered as cross-cutting concerns of digital health platform deployments, and include the following important capabilities:

  • Computational resources are cloud-native and reactively scaled in response to demand. Efficiency is increased through optimised resource management.
  • Real-time observability and management of resources. Deployments can dynamically adapt to changes in state and environment.
  • Continuous logging and monitoring of provisioned infrastructure. Reporting and visibility of resource cost and usage patterns.
  • Orchestration that is rigorous and compliant. The HeartAI implementation of Red Hat OpenShift allows containerised resources to be managed robustly.
  • Real-time monitoring of operational environments with a broad collection of metrics. Smart alerting and integration with messaging and notification systems.
  • Integrations that support sensor-based and event-based log collection and processing. Further enhanced by event log aggregation and observability frameworks.
  • Continuous monitoring of platform components to evaluate security and risk severity. Policy systems that assess and report compliance to international standards.
  • Extended network implementations with support for software-defined networking and complex network topology management.
  • Identity management with OAuth 2.0 and OpenID Connect implementations with comprehensive attribute-based access control.
  • Service design and architecture that follows best-practices in reactive microservices architecture and event-sourced data systems.
  • Generic interfacing capabilities with a variety of data systems, including relational and non-relational databases and high-throughput message streams.
  • Software-defined networking between platform services that allow powerful service mesh functionalities
  • Modern and best-practice approaches to the management of the HeartAI source code and the general coordination of projects and products.
  • Dynamic and automated deployment pipelines with support for CI/CD and well-defined testing methodologies
  • Readily deployable development environments with supportive tooling and integrated development frameworks.
  • Comprehensive data integration across many modes of health system data. Secure and self-service approaches for data access.
  • Clinical innovation that is supported by rigorous and real-time information systems. Continuous and reactive monitoring of health service activity.
  • Powerful analytics that implement probabilistic programming paradigms. Modern approaches for generative and predictive modelling.
  • Digital systems that support clinical service delivery and patient care. Continuous health system innovation.
  • Data acquisition and processing for high-throughput streams such as observation machines and medical sensors. Adaptive and dynamic monitoring systems.
  • Productive engagements with health system users, academia, industry, and the greater community.
  • HeartAI promotes a culture of support and guidance. Positive organisational and personal growth is encouraged.

Platform capabilities

Further information about HeartAI platform capabilities may be found with the following documentation:

Stakeholder engagement

The HeartAI team have matured positive and productive relationships with key stakeholders both locally within South Australia, nationally, and internationally. These engagements support the development of a system that hopes to bring together health system service delivery, academic research, and industry innovation. The HeartAI team are thankful for the support from:

  • SA Health
  • Southern Adelaide Local Health Network
  • Central Adelaide Local Health Network
  • Northern Adelaide Local Health Network
  • Commission on Excellence and Innovation in Health
  • Office for the Chief Medical Information Officer
  • Digital Health SA
  • Health Translation SA
  • South Australian Health and Medical Research Institute
  • Flinders University
  • The University of Adelaide
  • University of South Australia
  • Australian Institute for Machine Learning
  • Flinders Cardiac Surgery Research
  • Microsoft
  • Red Hat
  • Altera Digital Health

Further information

Further information about HeartAI may be found with the following documentation: