The aim of new technologies, such as the PREVENTOMICS interventional studies, is often to improve health outcomes. However, these technologies might also incur costs. By combining these costs and benefits in a cost-effectiveness analysis, we can see how much money will have to be spent to achieve a particular health outcome. The results of this kind of analysis can help to see whether or not the costs of implementing personalised nutrition are acceptable, given the health outcomes it achieves.
Short term results costs and effects
As part of the PREVENTOMICS project, we analysed the costs and outcomes of the different interventions in Denmark, Spain and Poland. Data on the cost-effectiveness of the UK pilot have not yet been analysed. Outcomes of two different intervention groups (personalised nutrition with behavioural program and personalised nutrition without behavioural program (only in Poland and Spain) were compared with a control group.
As expected, we saw higher intervention costs in the personalised intervention groups compared to the control groups. The use of PREVENTOMICS interventions comes with different additional costs, such as the costs of testing, the use of different smartphone apps, and special food ingredients. However, in Denmark the intervention also improved some outcomes, such as participants’ BMI and bodyweight. The pilot in Spain showed similar results, since both the personalised group without behavioural program and the personalised group with behavioural program showed better health outcomes than the control group. However, in Poland, opposite results were found, were the intervention groups showed worse outcomes that the control group. Many uncertainties around these effect estimates still exist.
Long term results costs and effects
Since the benefits of a personalised intervention may appear after several months or years, we also analysed the costs and effects over a lifetime, since even slight improvement in clinical outcomes (like some weight loss) can lead to important health benefits in the future. This is because weight loss can reduce the risk of diet related diseases such as diabetes, which would in turn increase life expectancy or ‘healthy life expectancy’.
If we compare the health benefits with the total costs over this lifetime period, we may see that the benefits are too small to justify an increase in total costs. However, if we look at the highest possible effect that was measured during the pilots, we see that the intervention in Denmark appeared to be cost-effective compared to the control group. This was also true for the personalised intervention with behavioural program in Poland. This means that the costs of implementing personalised nutrition might be acceptable in these cases.
What can we conclude about the cost-effectiveness of personalised nutrition interventions based on the results?
First of all, we can conclude that personalised nutrition interventions will certainly increase short-term costs, mainly because they require tests and additional costs (like software). However, if the personalised nutrition intervention reduces BMI and other relevant risk factors, it can reduce long-term healthcare costs by reducing the risk of diabetes and other obesity-related diseases.
Moreover, if the risk of diabetes and other obesity-related diseases is reduced, we can expect an improvement in healthy life expectancy. This is a win-win situation, you could say, since healthcare costs will go down while health will go up. Unfortunately, there are two ‘downsides’ here. First of all, people who live longer (because of a lower risk of these diseases) will eventually incur other healthcare costs, so long-term cost-savings from personalized nutrition may not be achievable. More importantly, payers will need to be willing to incur the initial higher costs to achieve the long-term health benefits.
What can be done in the (near) future?
In the future, we will also analyse the costs and effects (and the cost-effectiveness) of the UK pilot. Moreover, we would also like to see if results differ between sub-groups. In other words, will the personalised intervention be more (cost-)effective in participants with severe obesity compared to people with overweight?
Milanne Galekop
PhD student in Health Technology Assessment at the Erasmus School of Health Policy and Management at the Erasmus University in Rotterdam. She has a background in Health Economics and her PhD research focuses on the PREVENTOMICS project and the cost-effectiveness of the different interventions.
Ken Redekop, Ph.D.
Associate professor at the Health Technology Assessment, Erasmus University Rotterdam, The Netherlands. He is a clinical epidemiologist with more than 20 years of experience in observational research, clinical trial analysis, and medical technology assessment and an author of over 100 papers in the medical literature. Current studies include early-stage cost-effectiveness analyses of medical devices and tests, RCT-based economic evaluations, economic evaluations in the Diagnostics Assessment programme of the National Institute for Health and Clinical Excellence (NICE, UK) and outcomes research studies to determine the effectiveness and cost-effectiveness of expensive medicines in daily practice. Most studies relate to diabetes, cardiovascular disease, and cancer, and most involve modelling and evidence synthesis.
