Elsevier

Public Health

Volume 120, Issue 12, December 2006, Pages 1140-1148
Public Health

Mini-Symposium
Predicting the impact of population level risk reduction in cardio-vascular disease and stroke on acute hospital admission rates over a 5 year period—a pilot study

https://doi.org/10.1016/j.puhe.2006.10.012Get rights and content

Summary

The brief for this study was to produce a practical, evidence based, financial planning tool, which could be used to present an economic argument for funding a public health-based prevention programme in coronary heart disease (CHD) related illness on the same basis as treatment interventions.

Objectives

  • To explore the possibility of using multivariate risk prediction equations, derived from the Framingham and other studies, to estimate how many people in a population are likely to be admitted to hospital in the next 5–10 years with cardio vascular disease (CVD) related events such as heart attacks, strokes, heart failure and kidney disease

  • To estimate the potential financial impact of reductions in hospital admissions, on an ‘invest to save’ basis, if primary care trusts (PCTs) were to invest in public health based interventions to reduce cardiovascular risk at a population level.

Study design

The populations of five UK PCTs were entered into a spreadsheet based decision tree model, in terms of age and sex (this equated to around 620,000 adults). An estimation was made to determine how many people, in each age group, were likely to be diabetic. Population risk factors such as smoking rates, mean body mass index (BMI), mean total cholesterol and mean systolic blood pressure were entered by age group. The spreadsheet then used a variant of the Framingham equation to calculate how many non-diabetic people in each age group were likely to have a heart attack or stroke in the next 5 years. In addition heart failure and dialysis admission rates were estimated based upon risk factors for incidence. The United Kingdom Prospective Diabetes Study (UKPDS) risk engines 56 and 60 were used to calculate the risk of CHD and stroke, respectively, in people with type 2 diabetes. The spreadsheet deducted the number of people likely to die before reaching hospital and produced a predicted number of hospital admissions for each category over a 5-year period. The final part of the calculation attached a cost to the hospital activity using the UK Health Resource Grouping (HRG) tariffs. The predicted number of events in each of the primary care trusts was then compared with the actual number of events the previous year (2004/2005).

Methodology

The study used a decision tree type model, which was populated with data from the research literature.

The model applied the risk equations to population data from five primary care trusts to estimate how many people would suffer from an acute CVD related event over the next 5 years. The predicted number of events was then compared with the actual number of acute admissions for heart attacks, strokes, heart failure, acute hypoglycaemic attacks, renal failure and coronary bypass surgery the previous year.

Results

The first outcome of the model was to compare the estimated number of people in each PCT likely to suffer from a heart attack, a stroke, heart failure or chronic kidney failure with the actual number the previous year 2004/2005. The predicted number was remarkably accurate in the case of heart attack and stroke. There was some over-prediction of chronic kidney disease (CKD) which could be accounted for by known under-diagnosis in this illness group and the inability of the model to pick up, at this stage, the fact that many CKD patients die of a CHD related event before they reach the stage of requiring renal replacement. The second outcome of the model was to estimate the financial consequence of risk reduction. Moderate reductions in risk in the order of around 2–4% were estimated to lead to saving in acute admission costs or around £5.4 million over 5 years. More ambitious targets of risk reduction in the order of 5–6% led to estimated savings of around £8.7 million.

Conclusions

This study is not presented as the definitive approach to predicting the economic consequences of investment in public health on the cost of secondary care. It is simply a logical, systematic approach to quantifying these issues in order to present a business case for such investment. The research team do not know if the predicted savings would accrue from such investments; it is theoretical at this stage. The point is, however, that if the predictions are correct then the savings will accrue from over 4000 people, from an adult population of around 185,000 not having a heart attack or a stroke or an acute exacerbation of heart failure.

Introduction

This study explores the extent to which a payer in the health system could estimate the potential benefit of investing in public health interventions to reduce risk of cardiovascular disease (CVD) in a population. The aim would be to reduce the cost of acute hospital admissions for conditions such as heart attacks, strokes and heart failure over a 5-year period.

Most guidelines for the prevention of coronary heart disease (CHD) recommend preventative measures to asymptomatic individuals at high risk. Risk assessment is performed using one of several risk tools that combine values for different risk factors into a global risk estimate. These tools are generally based upon multivariate risk prediction equations derived from large prospective cohort studies or randomized trials that estimate a patient's risk of having a CVD event over 5–10 years. The most commonly used risk prediction equations are based on the Framingham Heart Study. There are several concerns about the generalizability of Framingham data to European populations.1 These include the following:

  • Framingham possibly overestimates absolute risk in populations with lower coronary heart disease rates.2, 3

  • Framingham has been shown to overestimate CVD risk in British (middle aged male), Danish, German and Italian populations.4, 5, 6, 7

  • The definition of end-points used in Framingham differs from those used in most other studies including clinical trials.

The hypothesis for this study is straightforward. There is a proven link between the level of cardiovascular risk in an individual and the likelihood of them having a heart attack, stroke or other CVD related acute event. If an individual has certain levels of risk factors, i.e. systolic blood pressure, body mass index (BMI), cholesterol level, smoking status. then it is possible, using the Framingham equation, to estimate their risk of having a heart attack, stroke etc over the next 5 years. If they have a 10% chance of suffering a CVD related event in the next 5 years, it could be assumed that if a hundred people have the same mean level of risk then 10 of them would have a CVD event in the next 5 years.

Section snippets

Methodology

This study uses a ‘cost offset’ modelling approach. It brings together data and evidence from health promotion, epidemiology, clinical practice, accountancy, health policy and hospital coding systems, in a systematic way to attempt to understand the impact on future hospital costs of a systematic, evidence based approach to CVD reduction at a population level. It is in this combination of data that the greatest strength of modelling, and the greatest opportunity for error, probably lies. There

Predicted events vs. actual events

To test or validate the model, an exercise was carried out whereby the model was populated with data from five South Yorkshire PCTs. The predicted number of CVD-related admissions based on current risk factor levels was compared with the actual number of admissions for these conditions in 2004/2005. The result is shown in Fig. 1.

Clearly the predictive power of the model is reasonably accurate in high-risk populations such as PCT1, PCT 2, and PCT 3 and slightly overestimating the lower risk

Conclusion

‘Measures to tackle rising public health problems are being scrapped or postponed because the funds have not materialized, public health chiefs say: An extra £211 m was to be ploughed into projects in England this year to tackle smoking, obesity and sexual health. But public health directors say just a fraction was coming through because of the deficits crisis and the push risked ‘never getting off the ground’’.20 It is very difficult to argue for significant investment in health improvement

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