Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Oct 28, 2025
Open Peer Review Period: Nov 5, 2025 - Dec 31, 2025
Date Accepted: Aug 12, 2026
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Implementing A Health Informatics System in The South Australian Public Health Network
ABSTRACT
Background:
South Australia’s public hospitals transitioned to the Sunrise (Altera Digital Health) electronic medical record (EMR) from 2010 but the new system lacked tools for near-real-time secondary use of data to support clinical care, operations, and research.
Objective:
To design, implement, and evaluate a scalable Health Informatics System (HIS) within the Central Adelaide Local Health Network (CALHN) that securely integrates live EMR data and enables user-centred digital tools across clinical, coding, and operational domains.
Methods:
A cloud-native Health Informatics System (HIS) was developed on Microsoft Azure and Red Hat OpenShift using Terraform and ArgoCD for secure, reproducible deployment. Services employed CQRS, event-sourcing, and Apache Kafka for real-time data processing, with applications built in Scala.js and D3.js for responsive clinical interfaces. Governance frameworks aligned with SA Health’s Security Impact Assessment and Information Asset Classification processes and ensured compliance and safety. Clinical, corporate, and ethical committees oversaw EMR integration, data access, and research use. AI models were trained in secure, GPU-enabled environments with full audit trails. Sustainability was achieved through commercial agreements between CALHN, AusHealth, and HeartAI Pty Ltd, and was further supported by blended grant, professional services and equity funding.
Results:
Three sequential projects demonstrated coverage across key user groups: 1. Critical Care Informatics System extracted live EMR data for ward/bed-level displays, automated registry submissions and underwent iterative usability testing 2. CODEXA Clinical Coding Software system applied a custom Transformer based AI model to associate likely diagnostic codes using patient notes and estimate reimbursement amounts 3. The Patient Flow project is in the planning phases to establish a data-driven command centre for use in the Network Operations Centre
Conclusions:
A secure, scalable HIS can be deployed in a complex public health network through layered architecture, rigorous governance, and co-design with end users. The platform enabled real-time clinical displays, AI-assisted coding, and enterprise flow planning while maintaining safety and compliance. Clinical Trial: This trial is not registered.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.