The health benefits of prevention: a simulation approach

Health Policy. 1989 Jul;12(1-2):1-255.

Abstract

In 1986 the Health 2000 Report, a long term health policy document, was presented to the Dutch parliament. This document is part of shift in interest in public health towards health rather than health services planning. There are two interesting features in this shift. The one is the tendency to measure the effectiveness of a policy, and intervention or a technology in terms of health, the outcome rather than the input, output or process. The other is the acceptance that political choices need to be made, since however large the budget for health is, it will always be limited. One of the choices to make will be whether or not to invest in preventive interventions. Preventive interventions can be defined as deliberate changes in the prevalence of risk factors in a population. To be able to weigh the costs and the benefits of such preventive interventions, an estimate will have to be made of their effect on the health of the population. Furthermore changes in risk factor prevalence may also occur autonomously. An estimate of the changes in the health status of the population as a result of these shifts in risk factor prevalence, will be important for the planning of health services and for the setting of realistic targets, as proposed by WHO. Prevent is a tool that will estimate the health effects of changes in risk factor prevalence in a population, as a result of trends or interventions. Its results can either be used directly in health policy making to formulate targets or quantify different scenario's on changes in risk factor prevalence in the future, or its results can be used as input for formal decision making processes such as for instance cost effectiveness studies. In epidemiology an analysis of the distribution of disease incidence and risk factor prevalence in different populations is used to confirm the hypothesis of a causal relationship between risk factor and disease. The strength of the relationship is often expressed as the ratio of incidence between exposed and non exposed, the Incidence Density Ratio (IDR). The importance of a risk factor for the incidence of a certain disease in a population is usually expressed as the Etiologic Fraction (EF), the proportion of the total incidence of the disease that can be attributed to the prevalence of that risk factor in the population. The EF is sometimes used as an indication of the proportion of incidence that could be prevented by the total elimination of that risk factor in the population.(ABSTRACT TRUNCATED AT 400 WORDS)

MeSH terms

  • Disease
  • Epidemiologic Methods
  • Forecasting
  • Health Policy*
  • Health Services Research / methods*
  • Health Status Indicators
  • Models, Statistical*
  • Netherlands
  • Planning Techniques
  • Preventive Health Services / statistics & numerical data*
  • Risk Factors