Latest guest blog is from Professor Kath Barnard @DrKathBarnard
It has been an exciting year for diabetes related technology, particularly for those with type 1 diabetes. There have been widely reported leaps forward in the development of the artificial pancreas with research teams around the world conducting clinical trials outside of hospital and laboratory settings. Summer camps and ‘at home’ trials are ongoing around the world with some very positive results thus far.
New self-monitoring of blood glucose devices are becoming available which add explanation and context to the numbers presented on standard meters. Such devices present an evolutionary development away from simple ‘snapshot’ finger prick testing, to support systems for users and furthermore to flash monitoring systems. This is where retrospective trend data can provide more detailed information about patterns of blood glucose and help the user fine-tune their basal and bolus insulin delivery to best match their needs.
So, it’s all good one would think on the technologies front and before too long we should be able to report significantly improved outcomes for people living with type 1 diabetes using this advanced technology. Or perhaps it’s a little early for such optimism.
Where is the evidence-base? How do we actually know that new, ‘whizzier’, faster and more detailed are actually beneficial? How do we know whether there are any specific groups of people with type 1 diabetes who would benefit most from these from these devices and, if there are any for whom the potential for additional burden and increased anxiety associated with these devices could result in unintended detrimental health outcomes?
This is the thing with evidence-based medicine, as practiced in the NHS. It very much relies on a critical appraisal of the evidence-base, and for these new devices this currently seems to be lacking somewhat. How then are we able to assess the clinical, psychosocial and cost effectiveness of these new devices? Taking this argument a step further, what outcomes should be we evaluating in such a critical appraisal? By knowing this, we can then design the clinical trials required to provide the evidence-base that we require.
There is no doubt that glycaemic control, as assessed by HbA1c is a key outcome. As much as it may pain me as a psychologist, it is difficult to get around the argument that with even the best psychological outcomes, sub-optimal glycaemic control remains the gold standard marker of risk of long-term diabetes related complications. I would obviously counter that argument with the overwhelming evidence that improved psychosocial and psychological functioning are associated with improved glycaemic control and therefore are of equal importance but this does not always wash with my medical colleagues.
So let’s look at technologies currently available to support diabetes management for people with type 1 diabetes. There is undoubtedly engineering excellence associated with these devices and on paper they should support optimal glycaemic control for users ….. so why is it that so many users still have sub-optimal glycaemic control? That’s where I come in. The simple answer that I always give is ‘because life gets in the way’. On paper, type 1 diabetes seems a ‘not too challenging’ mathematical problem, particularly with the devices available to facilitate optimal self-management. In reality however, it could not be further from that. Everything impacts on diabetes control, everything. Even a maths genius would be hard-pushed to achieve perfect glycaemic control (whatever that is!) without sacrificing other aspects of their psychosocial well-being. Whilst this may be acceptable in the short term, diabetes is not a short-term condition and for even the most persistent personality, it will eventually become onerous and unreasonable.
Insulin pump therapy for example is associated with numerous quality of life benefits such as increased independence, fewer injections, greater food related freedom and improved psychosocial functioning, as well as biomedical benefits such as reduced frequency and severity of hypoglycaemia. Yet there are also a number of downsides including constant attachment to the device, potential increased visibility of disease state, cost and risk of occlusion and pump failure. Continuous glucose monitoring devices are associated with improvements in glucose control, however evidence shows that this is dependent upon regular use. Psychosocial benefits include increased confidence about diabetes control, ability to identify trends and act to remedy patterns of hypo- or hyperglycaemia, and reassurance for parents whilst their child is at school. Alarm fatigue (particularly false alarms), technical failure and accuracy problems are limiting factors to ongoing engagement, with lack of trust in the devices and irritation with technological failure cited as key reasons for cessation of use. These factors may contribute to the low uptake of CGM use at around 6% at best.
So, the new self-monitoring of blood glucose meters have a lot to live up to. There is no doubt that SMBG is a crucial aspect of diabetes self-management for people with type 1 diabetes and many people with type 2 diabetes, however previous research shows that SMBG is associated increased anxiety and depression for some users. How do we know that this will not be the case with the new SMBG systems and flash monitoring devices? The ability to simply ‘swipe the device over the sensor’ is clearly very tempting and enables users to frequently check their blood glucose without having to conduct a finger prick test. I wonder whether this ability for more frequent, non-invasive checking rather than engaging in the recommended testing frequency of 4-6 times a day is reassuring or whether it contributes to increased anxiety and worry for users. The truth is that currently we are unable to answer that question. Nor will we be able to do so until robust clinical trials have been conducted to find out.
Whilst I still maintain that the future is very bright for technologies in the support of diabetes self-management, I equally believe that these must fill a real need. They must be evidence-based and theory driven, developed with people with diabetes as equal members of the clinical research team and meet the needs of the end users from an engineering, biomedical and psychosocial perspective. Only when we can genuinely say that we have achieved this goal will a device be truly fit for purpose.