Extending the IMPACT coronary heart disease model to different policy contexts
Lead Research Organisation:
University of Liverpool
Department Name: Population Community and Behavioural Sci
Abstract
Coronary heart disease (CHD) remains a top policy priority in the UK, and elsewhere.
In Britain, almost three million people suffer from CHD, and over 110,000 die every year. Nearly half these deaths are premature. Worse still, premature CHD is THREE times more common in deprived communities, making CHD an important cause of health inequalities.
The good news is that firstly, 90% of premature CHD is PREVENTABLE. Secondly, CHD death rates in Britain have halved in the last two decades. But why has this decline happened, and can things improve further?
We have investigated this important subject using a computer-based statistical model called IMPACT. We found that about 40% of the recent fall in CHD deaths was due to medical treatments and about 60% to people stopping smoking and eating healthier food.
Our IMPACT model has now helped to explain CHD trends in a variety of populations including England and Wales, Scotland, Ireland, Finland, New Zealand, and China.
IMPACT is the only CHD policy model that has been convincingly calibrated for the UK population of 60 million. It is comprehensive, covering all the important groups of CHD patients, all the standard treatments and all the major risk factors such as smoking, exercise and obesity. Our results have been reassuringly consistent with other studies in different countries.
However, our current model is complicated to use. It is only appreciated by a small number of researchers. The people making decisions in the NHS and in the Department of Health would obviously like a more ?user friendly? version of the model.
We are therefore requesting funding to work with decision-makers at national and local levels; obtain their views and suggestions, discover how they interact with the model, revise the model, then let them test it out again, before making further improvements.
This new, improved IMPACT model would be more efficient and user friendly; a decision support system to help answer different questions about reducing heart disease. For instance, deciding which future health programmes are likely to be most successful (and best value for money). For instance, comparing the advantages and costs of new treatments (like defibrillators) and new ideas for prevention (like smoke free restaurants or healthier school meals).
Creating a web-based version of the improved model would then enable us to share it with people trying to control epidemics of heart disease in other countries.
In Britain, almost three million people suffer from CHD, and over 110,000 die every year. Nearly half these deaths are premature. Worse still, premature CHD is THREE times more common in deprived communities, making CHD an important cause of health inequalities.
The good news is that firstly, 90% of premature CHD is PREVENTABLE. Secondly, CHD death rates in Britain have halved in the last two decades. But why has this decline happened, and can things improve further?
We have investigated this important subject using a computer-based statistical model called IMPACT. We found that about 40% of the recent fall in CHD deaths was due to medical treatments and about 60% to people stopping smoking and eating healthier food.
Our IMPACT model has now helped to explain CHD trends in a variety of populations including England and Wales, Scotland, Ireland, Finland, New Zealand, and China.
IMPACT is the only CHD policy model that has been convincingly calibrated for the UK population of 60 million. It is comprehensive, covering all the important groups of CHD patients, all the standard treatments and all the major risk factors such as smoking, exercise and obesity. Our results have been reassuringly consistent with other studies in different countries.
However, our current model is complicated to use. It is only appreciated by a small number of researchers. The people making decisions in the NHS and in the Department of Health would obviously like a more ?user friendly? version of the model.
We are therefore requesting funding to work with decision-makers at national and local levels; obtain their views and suggestions, discover how they interact with the model, revise the model, then let them test it out again, before making further improvements.
This new, improved IMPACT model would be more efficient and user friendly; a decision support system to help answer different questions about reducing heart disease. For instance, deciding which future health programmes are likely to be most successful (and best value for money). For instance, comparing the advantages and costs of new treatments (like defibrillators) and new ideas for prevention (like smoke free restaurants or healthier school meals).
Creating a web-based version of the improved model would then enable us to share it with people trying to control epidemics of heart disease in other countries.
Technical Summary
Coronary heart disease (CHD) remains a top policy priority in the UK, and elsewhere. Almost three million Britons suffer from CHD, and over 110,000 die each year - many prematurely. Furthermore, premature CHD is THREE times more common in deprived communities, representing an important cause of health inequalities.
We investigated this issue using a computer-based statistical model called IMPACT. Approximately 40% of the recent, substantial fall in UK CHD deaths was due to medical treatments, and 60% to risk factor improvements, particularly smoking.
IMPACT is the only comprehensive CHD policy model that has been convincingly calibrated for the UK population. It is truly comprehensive, including all patient groups, all standard treatments and all major risk factors. Conceptually simple, but methodologically sophisticated, all assumptions are explicit, transparent, and subjected to rigorous sensitivity analyses.
Published model outputs include deaths postponed, life-years-gained, and cost effectiveness of different interventions. Policy issues explored include the potential benefits from (surprisingly small) decreases in particular risk factors versus increases in specific treatments.
Our IMPACT model has helped to explain CHD trends in diverse populations including England and Wales, Scotland, Ireland, Finland, New Zealand, and China. Our findings have been reassuringly consistent with other studies using contrasting methods in different countries.
However, the current IMPACT Model is complicated to use. Decision makers in the NHS and policy makers in the UK Department of Health and elsewhere would prefer a more ?user friendly? version. One that could answer different questions about reducing CHD. For instance, comparing the advantages and costs of new treatments (like defibrillators or rimonabant) and new prevention approaches (for instance, smoke free restaurants or healthier school meals).
AIM
We therefore wish to extend the IMPACT CHD Model, in order to maximise its value to policy makers and decision makers.
OBJECTIVES
EXTEND THE IMPACT MODEL BY
1. Undertaking further refinements and incorporating diverse methods and approaches;
2. Creating additional epidemiological outputs (including population-based rates for mortality,
hospital admissions, need for revascularisation, changes in life-expectancy, population impact number, quality of life, cost effectiveness etc);
3. Using simulation to improve the precision of the estimates and explore the uncertainty;
4. MAXIMISE THE MODEL?S POLICY VALUE BY
Working with policy makers and decision makers to
i) Create a user-friendly interface for the model,
ii) Offer a range of different populations to examine at national, regional and local levels, and
iii) Be able to address current and future policy issues.
We investigated this issue using a computer-based statistical model called IMPACT. Approximately 40% of the recent, substantial fall in UK CHD deaths was due to medical treatments, and 60% to risk factor improvements, particularly smoking.
IMPACT is the only comprehensive CHD policy model that has been convincingly calibrated for the UK population. It is truly comprehensive, including all patient groups, all standard treatments and all major risk factors. Conceptually simple, but methodologically sophisticated, all assumptions are explicit, transparent, and subjected to rigorous sensitivity analyses.
Published model outputs include deaths postponed, life-years-gained, and cost effectiveness of different interventions. Policy issues explored include the potential benefits from (surprisingly small) decreases in particular risk factors versus increases in specific treatments.
Our IMPACT model has helped to explain CHD trends in diverse populations including England and Wales, Scotland, Ireland, Finland, New Zealand, and China. Our findings have been reassuringly consistent with other studies using contrasting methods in different countries.
However, the current IMPACT Model is complicated to use. Decision makers in the NHS and policy makers in the UK Department of Health and elsewhere would prefer a more ?user friendly? version. One that could answer different questions about reducing CHD. For instance, comparing the advantages and costs of new treatments (like defibrillators or rimonabant) and new prevention approaches (for instance, smoke free restaurants or healthier school meals).
AIM
We therefore wish to extend the IMPACT CHD Model, in order to maximise its value to policy makers and decision makers.
OBJECTIVES
EXTEND THE IMPACT MODEL BY
1. Undertaking further refinements and incorporating diverse methods and approaches;
2. Creating additional epidemiological outputs (including population-based rates for mortality,
hospital admissions, need for revascularisation, changes in life-expectancy, population impact number, quality of life, cost effectiveness etc);
3. Using simulation to improve the precision of the estimates and explore the uncertainty;
4. MAXIMISE THE MODEL?S POLICY VALUE BY
Working with policy makers and decision makers to
i) Create a user-friendly interface for the model,
ii) Offer a range of different populations to examine at national, regional and local levels, and
iii) Be able to address current and future policy issues.