A computer model now links heart disease and dementia to predict how the UK population will age, and what that will cost the NHS. This matters because the UK population is getting older, and older people often have multiple long-term conditions like diabetes, heart disease, and dementia. Health planners need to know which prevention policies—such as lifestyle changes or new drugs—actually save money and improve lives, rather than just shifting costs elsewhere. Until now, models typically looked at one disease in isolation, missing the real-world overlap. If this succeeds, the model becomes a decision-support tool for the NHS and public health agencies. It can estimate the value for money of “healthy ageing” interventions, showing how a diabetes prevention programme, for example, might also reduce dementia cases decades later. This could reshape how the UK allocates its healthcare budget, prioritising policies that delay multiple diseases at once rather than treating them one by one. The model follows simulated patients from midlife until death, tracking costs, clinical outcomes, and whether they end up in institutional care.
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There is a need to estimate the impact of population ageing for efficient planning of healthcare resources, taking comorbidities into account. 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. For modelling the cardiovascular disease outcomes, the SPHR Diabetes prevention model is used, which is an individual patient level model developed to evaluate the value for money of a broad range of public health policies. The progression of risk factors such as BMI, systolic blood pressure, HbA1c, Total Cholesterol and HDL cholesterol over time were estimated from existing datasets. These risk factors information used describe individual patient’s risk of type 2 diabetes, microvascular outcomes, cardiovascular disease, congestive heart failure, cancer, osteoarthritis, depression and mortality. The model follows the patients until they die, estimating the impact of interventions on healthcare costs, clinical outcomes, and life expectancy. A dementia computer model that can address incidence, diagnosis, and disease progression issues is also developed. Each patient is assumed to have a certain progression path in their metabolic risk factors as they age and this can be modified with pharmacological and lifestyle interventions. These are used describe the probability of getting dementia, which is conditional on the individual characteristics of each subject in the model. This probability is used to determine if/when the individual is diagnosed with dementia. The dementia disease progression over time is also estimated to capture on healthcare costs, clinical outcomes, institutionalisation and life expectancy. These two models are linked to form a single model to estimate the impact of different prevention policies on both cardiovascular and dementia outcomes in the United Kingdom. The framework can be used as a decision support tool to evaluate the value for money of different “healthy ageing” interventions.
NIHR School for Public Health Research - Public Health
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