Population Health Impact of Disease in Canada (PHI)

Policy perspective

• Need for summary measures
• New generation of summary measures
• Integrated strategies
• Dialogue between research and policy

Need for summary measures

Summary measures of health can be used as benchmarks for health planning and priority setting. They help identify issues that need attention by decision makers. They can also be used to assess potential interventions, both those targeted at a single disease outcome and those which affect several diseases at a time.

Policy decisions about investments in health must be both effective in improving health and fiscally responsible. In the Public Health Agency of Canada, summary measures of health are part of the criteria used in priority setting. The Auditor General of Canada has formally recognized the need for a structured approach to priority setting.

In an environment where accountability is vital, summary measures contribute to the evidence base required to establish the importance of health promotion and prevention of illness in improving the health of Canadians.

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New generation of summary measures

The tools available to policy analysts traditionally focused on simple measures of mortality or prevalence of diseases. Using mortality measures alone failed to address the loss of health-related quality of life in terms of functional limitations. This meant that diseases with fatal outcomes such as cancer often overshadowed those with non-fatal, but long-term consequences, such as asthma or depression. Disease prevalence, on the other hand, drew attention to diseases that affected many individuals, but failed to take into consideration the relative severity of these diseases.

Summary measures of health can address these shortcomings of the traditional approach to measuring the relative magnitude of health issues. Summary measures provide a full snapshot of the cumulative impact of mortality and morbidity in a common measure: they combine the premature loss of life attributed to a particular illness and the reductions in functioning while living with the illness. In addition, they can measure the impact of risk factors that contribute to them, allowing policy analysts to examine the potential impact of interventions, again in a common measure. This allows policy analysts and planners to specify health outcomes with measurable endpoints that are meaningful to individuals.

These measures can be used to examine both traditional risk factors such as lifestyle and physical environment, and broader determinants such as socio-economic conditions at the individual and the community level so that the relative contribution of each determinant to the overall health status of the population can be assessed. They can provide benchmarks for equity-based assessment that examines differential impacts by various socio-demographic characteristics, such as gender, age group, ethnic origin, geographic location, or socio-economic group. First, they allow comparison of different groups and the gap between them. Second, they provide independent benchmarks for each group in order to measure improvement over time.

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Integrated strategies

Health interventions often target one specific disease, identified and justified based on disease-specific benefits. Integrated strategies can address multiple diseases through their common determinants and/or risk factors, for instance, the effect of smoking on cancer and cardiovascular disease. They can also address a cluster of risk factors affecting the same population, for instance, smoking and diet among those of lower socio-economic status. These integrated strategies shift the focus towards broader goals of healthy living.

At the same time, policy analysts are increasingly concerned that the benefit achieved by reduction of one disease could be lost due to an increase in other diseases. When mortality is reduced for one disease, individuals will die from another cause. The critical questions become: How many years of life are added? What other health conditions will be experienced during these added years of life? When an intervention shifts the impact of disease from one cause to another, it increases years of life lived, but does the gain in years provide extended life in good health, or an extended period of life with reduced functioning?

The PHI will use microsimulation models - in addition to spreadsheet calculations - to provide policy analysts with a broader and more realistic context that considers how diseases (and risk factors) overlap and interact. Specifically, "what-if" scenarios can examine how a change in one disease or risk factor may affect others.

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Dialogue between research and policy

As a research program, the PHI provides evidence about the relative impact of diseases, injuries, and risk factors in a common measure; this helps to identify potential areas for intervention. While the role of the researcher is to provide evidence, the role of the policy analyst is to position these data in a larger context. Ongoing dialogue is essential to link these two roles.

The researcher establishes the relative magnitude of a disease impact, helping to draw attention to issues. Policy analysts then identify and assess possible interventions, in particular, their effectiveness in terms of cost and benefit. Summary measures are useful in this process because they contribute estimates of specific effects of interventions.

Policy decisions must also take into account societal context and ethics. Some interventions that affect fewer individuals or have a high cost may be viable policy priorities, for example in a disadvantaged population. In some cases, broader strategies that address upstream determinants of health such as education will be most appropriate. Consultations with those affected by potential policy decisions and the health experts responsible for them can provide more information about the broader impact of interventions. Policy analysts need to examine interventions in the context of other priorities with which they compete for resources. Other considerations that may come into play include social attitudes and economic impacts.

The PHI encourages ongoing dialogue between researchers and health policy decision makers through its advisory groups and ongoing communications such as those provided in this website. Translating research findings into policy requires information sharing, discussion, and consensus-building. Researchers can get input as to what information is required and how to best synthesize and present this information so it is readily available and easily understood. This dialogue encourages further development of data sources, which requires collaboration of many jurisdictions.

Considerable debate about this new generation of summary measures has raised many questions about their methods and use in policy development. Ongoing dialogue can facilitate understanding of the methods being used and how concerns about them are being addressed.

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