Australia has spent years working towards a more connected health system but there is a significant change happening at the point of care: clinicians are increasingly being presented with health information generated continuously outside the healthcare system.
For people living with diabetes, continuous glucose monitoring (CGM) is one of the clearest examples. A traditional pathology result gives a clinician a measurement at a particular point in time. HbA1c provides a valuable view of average glycaemic exposure over the preceding two to three months. CGM is different. It can generate a continuous picture of glucose levels, trends and patterns between consultations.
That creates an opportunity for healthcare specialists but also exposes a problem because Australia’s clinical workflows are still largely designed around snapshots, while patients are increasingly generating streams of data.
The question is no longer simply whether we can collect that information. It is whether clinicians and their patients can make it useful.
The problem is data analysis
The expansion of CGM use now means a health care provider can potentially see much more about what is happening between patient appointments.
Instead of relying solely on an HbA1c result and a patient’s recollection of what happened over recent weeks, clinicians can see recurring patterns such as glucose changes overnight, rises following meals, periods of lower glucose, and how activity or treatment may coincide with those changes.
RACGP guidance already recognises the role of CGM in supporting people living with type 2 diabetes who use intensive insulin therapy, noting that the technology can provide greater insight into glycaemic variability and patterns.
However, a report containing more information is not automatically more useful. If a clinician must navigate another platform, interpret a large volume of data, or manually reconstruct a patient’s pattern, the technology risks creating another layer of work rather than reducing uncertainty. This is a familiar problem across digital health.
Australia has invested heavily in making health information more available. The next challenge is making that information actionable within existing clinical workflows.
CGM is a test case for patient-generated health data
Much of the information in a patient’s medical record has traditionally been generated inside the health system: pathology, imaging, prescriptions, diagnoses and clinical observations.
What makes CGM so significant is that it reverses this model.
The patient generates the information in their everyday environment, and the clinician can use it to understand what is happening outside the consultation.
For example, seeing a recurring rise in glucose after a particular meal is potentially more useful than seeing hundreds of individual glucose readings. Equally, seeing a repeated overnight pattern may prompt a different conversation from seeing an isolated high reading.
The technology’s job should therefore be to help surface meaningful patterns, not simply expose clinicians to more data.
The consultation needs to change with the data
There is a risk that we approach CGM as though the objective is to teach clinical specialists how to read another report – but that misses a bigger opportunity.
The most useful CGM consultation may be less about reviewing every metric and more about identifying one or two patterns that can inform a conversation with the person living with diabetes.
For example, CGM data may help clinicians identify why glucose is repeatedly changing at a specific time of day and whether this coincides with medication, food, exercise or sleep. This is where the technology can complement and support clinical judgement.
Modern CGM systems can provide real-time glucose information, trend information, alerts and digital reports that allow data to be reviewed over time. But those capabilities only become clinically valuable when they fit into the way clinicians actually work.
Interoperability cannot stop at moving the data
The digital health sector has rightly spent considerable effort on interoperability by getting information from one system to another to help streamline clinical workflows, but the tougher challenge is to address what happens to the information once it arrives.
If CGM data sits in a separate application from the patient’s clinical record, their health care provider may still have to switch between systems to understand the full picture.
If the information arrives without context, the clinician may have more data but not necessarily more insight. And if every new connected device creates its own workflow, the cumulative burden on primary care could become significant.
The objective should therefore be selective integration: getting the right information to the right clinician at the right time, in a form that supports a decision.
A new role for the patient-generated record
There is a broader opportunity here for Australian digital health.
People living with chronic conditions are already generating enormous amounts of health information through wearables, home blood pressure monitoring, symptom tracking, and other connected devices that are expanding that pool.
The healthcare system will increasingly need to decide which of that information belongs in clinical workflows, how it should be presented and who should be responsible for acting on it.
As access to CGM expands, the healthcare system will need to think beyond the sensor itself.
The question should be how continuous information can become part of routine, connected care.
That means designing technology around clinical workflows, making useful information easier to interpret, supporting appropriate information sharing and avoiding the creation of new data siloes.
HbA1c will continue to provide an important longer-term measure. CGM adds something different: visibility into what happens between those measurements.
The opportunity for primary care is not simply to see more. It is to see what matters, at the right time, and use it to have a better conversation with the person living with diabetes. That is the real test of whether continuous health data has made its way into connected care.
Weekend Viewpoint articles are the author’s opinion, produced without payment or sponsorship.
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