Estimating inequalities in unmet clinical need in patients living with obesity
Approved Research ID: 84685
Approval date: September 9th 2022
For years the obesity epidemic has been in the news, however we still see rising obesity and hence rising obesity-related illness. Because of this, providers of healthcare face increasing demands from increasingly complex patients who are living in poor health with multiple health conditions for longer. Understanding disease impacts and identifying patient groups with the highest unmet need can inform data-driven decisions on providing treatments and allocating health resources in the population. This is particularly important for obesity health given patients can have very different outcomes that vary over time. This complexity is best captured through the analysis of large-scale health databases that contain a rich variety of information, such as the UK Biobank.
The UK Biobank and a UK-based electronic health records database will be used to develop robust epidemiological analyses and statistical models, which identify patient characteristics that best predict obesity and general health (e.g. onset of heart attacks, diabetes and arthritis) and health care resource use. The effects of medical treatments on limiting poor health outcomes and reducing health care resource use in different groups of people will also be analysed. The results of this study will allow us to identify patient groups who will benefit the most clinically, so that targeting treatment to these groups result in the largest reduction in healthcare burden and more equitable health outcomes for the population.