Tangible Impact
Our collaboration led to a comprehensive cost-benefit analysis for a digital dietary education program aimed at reducing weight and aiding type 2 diabetes (T2D) remission. By applying a robust decision-analytical model, we demonstrated that the program could deliver significant cost savings over time. The results highlighted the potential for improved health outcomes, including reduced rates of T2D, which translated into long-term financial benefits for healthcare systems. This evidence empowered the innovators to focus their efforts on critical program development priorities, ultimately enhancing the program’s effectiveness and cost-efficiency.
The analysis conducted by HTE has been instrumental in showing the impact on cost of our innovation. The study has crucially highlighted areas where we should focus on building more evidence data; this insight will guide our future studies, enabling us to gather key data points and that further strengthen the quantitative evidence supporting the cost-effectiveness of our technology. David Oliver, CEO of Freshwell
Assessing the Challenge
The challenge was to evaluate the potential cost benefits of a digital dietary education program targeting adults with a BMI greater than 25. The aim was to determine whether using this program could lead to a reduction in weight and type 2 diabetes remissions, resulting in cost savings for healthcare systems. Health Innovation East approached Health Tech Enterprise to assess whether the intervention would have a sustainable financial impact.
Tailored Approach
To address this challenge, we first conducted an extensive literature review to solidify the connection between weight loss and type 2 diabetes reversal. This review provided essential data points, which were then used to build a decision tree model simulating the program’s budgetary impact over a five-year horizon. We ensured the model accounted for uncertainties by incorporating a probabilistic sensitivity analysis using a Bayesian approach. This allowed us to model various scenarios and project cost impacts based on different variables, such as target population size and adherence rates. Additionally, we provided strategic recommendations for future data collection in clinical trials to further strengthen the health economics evaluation.
