Impact Numbers
1. Description
Impact numbers are a group of metrics that generalise the NNT concept to the population level instead of focusing on only those patients who receive treatment.[1][2][3] By considering the baseline event probabilities in the population of interest, estimates of the number of individuals that will be affected by a disease and/or an intervention can be derived. These metrics therefore describe the "impact" of treatments from the public health perspective. The three most useful impact numbers are EIN (Exposure Impact Number), NEPP (Number of Events Prevented in the Population) and PIN-ER-t (Population Impact Number of Eliminating a Risk factor over time t).
2. Evaluation
2.1 Principle
- Conceptually similar to NNT (EIN is simply NNT)
- The interpretation is in terms of counts or number of people.
- Impact numbers emphasise the importance of justifying data sources, and therefore are more transparent than NNT.
2.2 Features
- Impact numbers provide public health perspective
- Their applications provide decision makers direct measures of public health impact in the population of interest.
2.3 Visualisation
- Visualisations similar to the one used in NNT may be used.
2.4 Assessability and accessibility
- The interpretations are straightforward and may appeal to many.
- It may only give a crude measure of the "impact" of a risk factor (e.g. a treatment), and therefore may not be suitable for formal regulatory decision-making.
3. References
[1] Attia J, Page J, Heller RF, Dobson AJ. Impact numbers in health policy decisions. J Epidemiol Community Health 2002 Aug;56(8):600-5.
[2] Heller RF, Buchan I, Edwards R, Lyratzopoulos G, McElduff P, Leger SS. Communicating risks at the population level: application of population impact numbers. BMJ 2003 Nov 15;327(7424):1162-5.
[3] Heller RF, Dobson AJ, Attia J, Page J. Impact numbers: measures of risk factor impact on the whole population from case-control and cohort studies. J Epidemiol Community Health 2002 Aug;56(8):606-10.