Population Impact Measures

Population Impact Measures (PIMs) are newly described measures of risk and benefit for use in epidemiology. Traditionally used measures of risk and benefit have been nicely summarised by Jerkel, Katz and Elmore. Described measures include the risk difference (attributable risk), rate difference (often expressed as the odds ratio or relative risk), Population Attributable Risk (PAR) and the Relative Risk Reduction (which is turned into a measure of absolute benefit, the Number Needed to Treat). Population Impact Measures extend these by creating measures of absolute risk at the population level producing numbers of people in the population who are at risk or who will benefit from Public Health interventions. They describe the population impact of health risks and benefits, to assist in health policy making. They are measures of absolute risk and benefit, producing numbers of people who will benefit from an intervention or be at risk from a risk factor within a particular local or national population. They provide local context to previous measures, allowing policy-makers to identify and prioritise the potential benefits of interventions on their own population. They are simple to compute, and contain the elements to which policy-makers would have to pay attention in the commissioning or improvement of services. They may have special relevance for local policy-making. They depend on the ability to obtain and use local data, and by being explicit about the data required may have the added benefit of encouraging the collection of such data.

To describe the impact of preventive and treatment interventions, the Number of Events Prevented in a Population (NEPP) is defined as "the number of events prevented by the intervention in your population over a defined time period". NEPP extends the well-known measure Number needed to treat (NNT) beyond the individual patient to the population. To describe the impact of a risk factor on causing ill health and disease the Population Impact Number of Eliminating a Risk factor (PIN-ER-t) is defined as "the potential number of disease events prevented in a population over the next t years by eliminating a risk factor". The PIN-ER-t extends the well-known Population Attributable Risk (PAR) to a particular population and relates it to disease incidence, converting the PAR from a measure of relative to absolute risk.

The components for the calculations are as follows: Population denominator (size of the population); Proportion of the population with the disease; Proportion of the population exposed to the risk factor or the incremental proportion of the diseased population eligible for the proposed intervention (the latter requires the actual or estimated proportion who are currently receiving the interventions ‘subtracted’ from best practice goal from guidelines or targets, adjusted for likely compliance with the intervention); Baseline risk – the probability of the outcome of interest in this or similar populations; and Relative Risk of outcome given exposure to a risk factor or Relative Risk Reduction associated with the intervention.

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