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Impact numbers in health policy decisions
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  1. J Attia1,
  2. J Page2,
  3. R F Heller3,
  4. A J Dobson4
  1. 1Centre for Clinical Epidemiology and Biostatistics, Faculty of Medicine and Health Sciences, The University of Newcastle, New South Wales, Australia
  2. 2Department of Epidemiology, Harvard School of Public Health, Boston, USA
  3. 3Evidence for Population Health Unit, The Medical School, The University of Manchester, UK
  4. 4School of Population Health, The University of Queensland, Queensland, Australia
  1. Correspondence to:
 Professor R Heller, The Medical School, The University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK;
 Dick.Heller{at}man.ac.uk

Abstract

Objective: To outline the major methodological issues appropriate to the use of the population impact number (PIN) and the disease impact number (DIN) in health policy decision making.

Design: Review of literature and calculation of PIN and DIN statistics in different settings.

Setting: Previously proposed extensions to the number needed to treat (NNT): the DIN and the PIN, which give a population perspective to this measure.

Main results: The PIN and DIN allow us to compare the population impact of different interventions either within the same disease or in different diseases or conditions. The primary studies used for relative risk estimates should have outcomes, time periods and comparison groups that are congruent and relevant to the local setting. These need to be combined with local data on disease rates and population size. Depending on the particular problem, the target may be disease incidence or prevalence and the effects of interest may be either the incremental impact or the total impact of each intervention. For practical application, it will be important to use sensitivity analyses to determine plausible intervals for the impact numbers.

Conclusions: Attention to various methodological issues will permit the DIN and PIN to be used to assist health policy makers assign a population perspective to measures of risk.

  • impact numbers
  • risk
  • policy
  • PIN, population impact number
  • DIN, disease impact number
  • NNT, number needed to treat
  • CHF, congestive heart failure

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Footnotes

  • * Levin ML. The occurrence of lung cancer in man. Acta Unio Int Contro Cancrum 1953;9:531–41.

  • Rothman KL, Greenland S. Modern epidemiology. 2nd edn. Philadelphia: Lippincott-Raven, 1998:58.

  • Funding: none.

  • Conflicts of interest: none.

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