A clinician's journey to thinking systemically about digital transformation

Amy Bowman"Rather than focusing solely on improving the immediate program, I deliberately zoomed out to consider the full lifecycle of the data—how it could be used not only to support individual patient care, but also to inform longer-term service planning and future procedural risk prediction models."

Amy Bowman
Allied Health Digital Health Partner, The Royal Children's Hospital
Learner in the Centre's Learning Health Systems short course

  • Who: Amy Bowman is the Allied Health Digital Health Partner at The Royal Children's Hospital, combining clinical expertise as a physiotherapist with digital systems and quality improvement leadership.
  • The challenge: Amy was delivering improvements at the project level but was seeking a structured framework to design, evaluate, and scale digital transformation across systems.
  • Standout moment: The Learning Health Systems course shifted Amy's perspective from viewing digital health as discrete projects to understanding it as an ongoing cycle of learning, measurement, and improvement embedded in clinical practice.
  • Key outcomes: 
    • Deliberate integration of data quality, governance, clinician engagement, and evaluation frameworks
    • Planning for long-term technological changes, not just short-term workflow optimisations
    • Critically considering where AI and emerging technologies add genuine value
Motivating question: How do you move from fixing problems one at a time to changing the system itself?

Amy Bowman has spent her career bridging two worlds: clinical practice and systems thinking.

As a physiotherapist, she saw firsthand how poorly designed digital systems create extra work, frustration, and safety risks. But she also saw the flip side – when systems were designed well, they freed up time and improved care.

That insight drew her into digital health. Today, as the Allied Health Digital Health Partner at The Royal Children's Hospital, she works with clinicians to redesign digital systems, so they actually support the work clinicians do.

Yet despite her growing experience, Amy recognised a gap. She was delivering improvements at the workflow level, but without a consistent framework to guide long-term system design and evaluation.

"My goal was to strengthen my understanding of digital transformation in healthcare – particularly how concepts such as learning health systems can be operationalised in real-world settings."

The shift: from projects to systems

Amy enrolled in the Centre for Digital Transformation of Health's Applied Learning Health Systems course.

One concept stood out: how to evaluate whether digital health initiatives are actually delivering impact.

The sessions on evaluating digital health initiatives particularly resonated with me. I frequently return to my notes from this topic and have applied these frameworks across my projects to assess impact in a more structured and meaningful way.

The course also introduced critical perspectives on artificial intelligence. There's a lot of hype around AI in healthcare, and it's easy to get caught up in what's possible rather than what's useful.

"These discussions provided a valuable gateway to understanding the potential and implications of AI in healthcare, helping me think more critically about where emerging technologies can add genuine value rather than novelty."

But the most significant shift was conceptual, in how Amy thought about digital health itself.

"The course shifted my perspective from viewing digital health as a series of discrete projects to understanding it as an ongoing cycle of learning, measurement, and improvement that is embedded into everyday clinical practice and organisational culture."

Real-world application and impact

The course has changed how Amy approaches her work. This includes:

  • Stronger data quality and consistency
  • Improved ability to track outcomes and reuse data over time
  • Supporting future service planning
  • Enabling downstream analytics and risk prediction models
  • Positioning the workflow as part of a broader Learning Health System
  • Foundations for future AI and predictive analytics integration

For example, in a prehabilitation workflow project, instead of focusing on individual system changes, she now considers implementation, measuring how it's working, learning from findings, and continuous improvement as standard process.

"The course influenced me to think differently about sustainability and scalability, prompting design decisions that would support reuse of data across years and contexts."

"This approach strengthened data quality, positioned the workflow to contribute to learning health system objectives, and laid the groundwork for future analytics and algorithm development beyond the initial project scope."

Why it matters

Amy’s journey reflects a broader shift across healthcare: the challenge is no longer implementing digital tools, but designing the broader systems that can continuously learn and improve.

Through its workforce education programs, the Centre for Digital Transformation of Health enables clinicians and health professionals to move from project-based thinking to system-level transformation, grounded in evidence, data, and real-world application.

If you are a clinician or health leader, the Centre’s education offerings provide the frameworks and practical capability to lead that transformation.

Explore our course offerings and find the learning pathway that fits your goals.

Next course starts early 2027. Learn more and register now →