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Modelling the potential economic impact of investment in Public Health Professor Malcolm Whitfield Director of The Centre for Health & Social Care Research.

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Presentation on theme: "Modelling the potential economic impact of investment in Public Health Professor Malcolm Whitfield Director of The Centre for Health & Social Care Research."— Presentation transcript:

1 Modelling the potential economic impact of investment in Public Health Professor Malcolm Whitfield Director of The Centre for Health & Social Care Research Sheffield Hallam University, UK

2 The Key Problem

3 “In the most industrialized countries of North America, Europe and the Asian Pacific, at least one-third of all disease burden is caused by tobacco, alcohol, blood pressure, cholesterol and obesity”. “More than three-quarters of cardiovascular disease (the world’s leading cause of death) results from tobacco use, high blood pressure or cholesterol, or their combination”. “Overall, cholesterol causes more than 4 million premature deaths a year, tobacco causes almost 5 million, and blood pressure causes around 7 million” WHO 2002 The health problem

4 Issue If we can get people to change their lifestyle i.e. diet, exercise, smoking and alcohol consumption we could reduce the burden of disease in society by up to 33% and reduce the cost of healthcare by over 70% Questions How much would we have to change the risk factors to reduce the burden of disease? What order of savings could we achieve on healthcare costs in the first five years? How much could we realistically invest in getting lifestyle change? The model idea

5 The model

6 The risk factors Demographic profileFramingham Population smoking ratesFramingham Mean total and HDL Cholesterol (mmol/l)Framingham Mean systolic blood pressureFramingham Mean Body Mass Index (BMI)Diabetes / Heart Failure Mean HBA1c levelsUKPDS Measures of CKD prevalence eGFR etcNanes II

7 Does it work? To validate the model, we estimated how many people in five Primary Care Trusts (n=620,000 population) would have a heart attack, stroke, heart failure, kidney failure and heart surgery. We then compared the predicted number with the actual number NB The models has since been tested in 15 PCTs

8 The validation – S/Yorks Admission data 2005/06 for 5 PCTs

9 The validation - Liverpool

10 The validation - Birmingham

11 Admissions avoided ( 364,912 pop) ScenarioAnnual acute admission events avoided after 5 years 5 year cumulative acute admission events avoided Current risk 0 0 Scenario 1 1,707 5,120 Scenario 2 1,075 3,225

12 Deaths avoided ( 364,912 pop) ScenarioAnnual premature deaths avoided after 5 years 5 year cumulative premature deaths avoided Current risk 0 0 Scenario ,470 Scenario

13 Revenue savings ( 364,912 pop) ScenarioAnnual acute admission costs avoided after 5 years 5 year cumulative admission costs avoided Current risk 0 0 Scenario million 19.8 million Scenario million 12.5 million

14 Estimated impact of health determinants on population health Key 10% Physical Environment 15% Genetic endowment 25% Health System 50% Socio-economic environment

15 Linkage to Decipher model Original model

16 North Karelia Main risk factors in North Karelia between 1972 and 2007 among men and women aged years Deaths Rate in Rate in 2006 Change from to 2006 All causes % All cardiovascular % Coronary heart disease % All cancers % Lung cancers % Age-adjusted mortality rates of coronary heart disease in North Karelia and the whole of Finland among males aged 35 – 64 years from 1969 to 2006.

17 Nuffield Bio-Ethical

18 Public health intelligence (case finding) Pathway to equality EPHP's Engagement Social marketing Health- literacy Informed choice Environmental initiatives Lifestyle change: Health Trainers Smoking Cessation Five a day Healthy schools meals Housing Green spaces Etc… Primary care: Statins Hypotensives Obesity treatments PH IntelligencePublic Health InterventionsPrimary care TE AE (Example) - CVD Cardiac risk checks Disease registers TE

19 / Decipher model


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