Webinar: Why Are We Still Paying to Keep Legacy Systems Alive?
06 August 2026 | 11:00am AEST | Live Webinar
Retire legacy applications. Reduce risk. Unlock the value of historical healthcare data.
Many healthcare organisations continue to maintain outdated applications solely to access historical information. The result is rising costs, growing technical debt and increasing risk.
Join RLDatix experts for a practical discussion on how healthcare organisations are safely retiring legacy systems while preserving access to critical data and supporting future digital transformation.
Overview
Healthcare organisations are modernising rapidly, yet many continue to support applications that no longer serve clinical or operational needs.
Often, these systems remain active simply because the data inside them cannot be easily accessed elsewhere.
This webinar explores how leading organisations are reducing costs, simplifying their technology landscape and moving beyond traditional archiving approaches to make historical data accessible, secure and useful.
What You’ll Learn
- The true cost of legacy applications: Understand the financial, operational and cybersecurity impact of maintaining ageing systems.
- A modern approach to healthcare data retention: Learn how organisations are preserving access to critical information without keeping legacy applications running.
- Moving from data archiving to data activation: Discover how historical healthcare data can remain accessible, searchable and valuable long after systems have been retired.
- Practical strategies for application retirement: Explore real-world approaches to reducing technical debt while supporting compliance and future digital transformation.
Who Should Attend?
- CIOs and CTOs
- Digital Transformation Leaders
- IT Directors and Managers
- Clinical Informatics Teams
- Information Governance Leaders
- Healthcare Technology Executives
Stop maintaining yesterday’s systems.
Join us to learn how healthcare organisations are reducing risk, lowering costs and unlocking greater value from historical data.




