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    Case study · Health

    Rebuilding a patient flow app that had slowed as its use grew

    EMHS's Long Stay Tracker follows patients who are medically cleared for discharge but cannot leave. As its use grew it slowed down, so we rebuilt it for reliable data and twice the load speed.

    East Metropolitan Health Service (EMHS) logo

    Outcomes

    • 2× faster load times after the rebuild

    The challenge

    Hospitals face an ongoing challenge with patients who are medically cleared for discharge but stay in hospital because they have nowhere to go or lack the support they need. These extended stays strain resources and reduce the beds available for incoming patients. East Metropolitan Health Service (EMHS) built the Long Stay Tracker, a Power App, to make these patients visible and help staff act sooner.

    A citizen developer had built the app. As more departments used it and the original developer moved on, it degraded: load times slowed, data became unreliable and maintenance became difficult. The EMHS Data and Digital Innovation team asked us to rebuild its failing components while keeping its look and feel, so staff could keep using it without disruption.

    Our approach

    We rebuilt the Long Stay Tracker to Microsoft's best practices for stability, scalability and performance.

    All data queries are now fully delegable and target SQL views. A full set of SQL stored procedures handles create, update and delete operations. Key parts of the app became reusable Power Apps components, which reduces maintenance and keeps it consistent. We kept interface changes to a minimum, so the familiar experience stayed while the back end became more efficient.

    The outcome

    The rebuilt Long Stay Tracker delivers accurate, reliable and fast data, so staff have what they need to act quickly on discharge planning. Load speeds have doubled, and users report a smoother, more intuitive experience.

    The app is also a foundation for further work: the EMHS team is developing a Power BI dashboard on its data to find trends in discharge times and support improvements to hospital flow and resource management.

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