Assessing the effectiveness and cost-effectiveness of population / community public health interventions and targeted identification and screening interventions for type-2 diabetes prevention, using a common modelling framework to support translation of knowledge into action.
Research Team: Professor Jim Chilcott, Professor Alan Brennan, Dr Penny Breeze, Dr Hazel Squires, Dr Chloe Thomas, Dr Louise Preston, Mike Gillett, Professor Peter Diggle, Dr Eric Brunner, Dr Adam Tabak & Professor Colin Greaves
Who's involved: University of Sheffield, LiLaC & University College London
April 2012 - March 2014
Type-2 diabetes is becoming increasingly common in the UK. A diabetes diagnosis reduces the quality of life of affected individuals, whilst costing society a huge amount in treatment of the disease and its complications.
A number of different public health policies have been proposed to help prevent type-2 diabetes. These include screening programmes in which individuals are tested for diabetes, lifestyle interventions (e.g. advice about nutrition and exercise) for those at high risk of developing diabetes, and national policies such as taxation of sugary drinks. To ensure that public money is used in the best way, it is necessary to decide which policies are most effective and most value for money.
Health economic models are computer models that are designed to predict the likely effect of different health interventions. They are used to help health professionals make decisions about treatments and health policy.
The research developed a model to look at a wide range of different public health policies for type-2 diabetes. The researchers involved doctors, diabetes researchers and lay members in the model design, in order to ensure that they had accurately represented the causes of diabetes, the care of patients and the outcomes of having the disease.
The model enabled researchers to follow the health journeys of individual people over time. For each person, their weight, cholesterol levels, systolic blood pressure and HbA1c (a
measure of diabetes) fluctuate from year to year, representing natural changes as people age. Individuals can develop diabetes, cardiovascular disease (e.g. heart disease or stroke), diabetes-related complications, cancer, depression or osteoarthritis over the course of their lifetime. Each disease results in a particular cost to society and a reduction in quality of life for the individual.
The model developed in the research is a useful tool and can estimate how different health policies can reduce the costs of diabetes and improve health for patients.
The findings showed for high risk individuals, the screening programmes followed by lifestyle education provided the most health benefits and cost savings. Sugary drink taxation or community interventions to promote healthy diets lead to smaller improvements in health and smaller cost savings.
Thomas C, Sadler S, Breeze P, Squires H, Gillett M, Brennan A. Assessing the potential return on investment of the proposed UK NHS Diabetes Prevention Programme in different population subgroups: an economic evaluation. BMJ Open 2017
Breeze PR, Thomas C, Squires H, Brennan A, Greaves C, Diggle PJ, Brunner E, Tabak A, Preston L & Chilcott J. The impact of Type 2 diabetes prevention programmes based on risk-identification and lifestyle intervention intensity strategies: a cost-effectiveness analysis. Diabetic Medicine 2017 34:5.
Breeze PR, Thomas C, Squires H, Brennan A, Greaves C, Diggle P, Brunner E, Tabak A, Preston L & Chilcott J. Cost-effectiveness of population-based, community, workplace and individual policies for diabetes prevention in the UK. Diabetic Medicine 2017 34:8.
Dunkley A, Tyrer F, Spong R, Gray L, Gillett MJ, Doherty Y, Martin-Stacey L, Patel N, Yates T, Bhaumik S, Chalk T, Chudasama Y, Thomas C, Sadler S, Cooper S, Gangadharan S, Davies M & Khunti K. Screening for glucose intolerance and development of a lifestyle education programme for prevention of Type 2 diabetes in a population with intellectual disabilities: the STOP diabetes research programme. NIHR Journals Library 2017.
Breeze P, Squires H, Chilcott J, Stride C, Diggle PJ, Brunner E, Tabak A, Brennan A. A statistical model to describe longitudinal and correlated metabolic risk factors: the Whitehall II prospective study. Journal of Public Health 2015 38:4.
Watson P, Preston L, Squires H, Chilcott J, Brennan A. Modelling the Economics of Type 2 Diabetes Mellitus Prevention: A Literature Review of Methods. Applied Health Economics & Health Policy 2014 12:3.
Penn L, Rodrigues A, Haste A, Marques MM, Budig K, Sainsbury K, Bell R, Araújo-Soares V, White M, Summerbell C, Goyder E, Brennan A, Adamson AJ, Sniehotta FF. NHS Diabetes Prevention Programme in England: formative evaluation of the programme in early phase implementation. BMJ Open (2018).
The aim of this project was to assess whether an existing community-based diabetes prevention programme was more successful than the usual care received by those who are risk of developing diabetes to lose weight, modify other diabetes risk factors and improve their health.
July 2014 - December 2016
This project developed computer models to estimate the value for money of interventions for cardiovascular diseases and dementia, and the impact these interventions on healthcare demand.
April 2014 - March 2017
