Understanding the risk

Risk statistics can be used persuasively to present health interventions in different lights, say researchers.

Health professionals and consumers may change their choices when the same risks and risk reductions are presented using alternative statistical formats, a new study has found. And, choosing the appropriate way to present risk statistics is key to helping people make well-informed statistics.

Risk statistics can be used persuasively to present health interventions in different lights, said authors of the Cochrane Systematic Review.

The different ways of expressing risk can prove confusing and there has been much debate about how to improve the communication of health statistics.

For example, one statistic could read that a drug cuts the risk of hip fracture over a three year period by 50 per cent. At first sight, this would seem like an incredible breakthrough. However, what it might equally mean is that without taking the drug 1 per cent of people have fractures, and with the drug only 0.5 per cent do.

Now the benefit seems to be much less. Another way of phrasing it would be that 200 people need to take the drug for three years to prevent one incidence of hip fracture. In this case, the drug could start to look like an expensive option.

Statisticians have terms to describe each type of presentation. The statement of a 50 per cent reduction is typically expressed as a relative risk reduction (RRR). Saying that 0.5 per cent fewer people will have broken hips is an absolute risk reduction (ARR). Saying that 200 people need to be treated to prevent one occurrence is referred to as the number needed to treat (NNT). These effects can also be shown as a frequency, where the effect is expressed as one out of 200 people avoiding a hip fracture.

In the new study, Cochrane researchers reviewed data from 35 studies assessing understanding of risk statistics by health professionals and consumers. They found that participants in the studies understood frequencies better than probabilities. Relative risk reductions, as in "the drug cuts the risk by 50 per cent", were less well understood. Participants perceived risk reductions to be inappropriately greater compared to the same benefits presented using absolute risk or NNT.

"People perceive risk reductions to be larger and are more persuaded to adopt a health intervention when its effect is presented in relative terms," said Elie Akl, first author on the review and assistant professor of Medicine at University at Buffalo.

"What we don't know yet is whether health professionals or policymakers might actually make different decisions based on the way health benefits are presented."

Although the researchers say further studies are required to explore how different risk formats affect behaviour, they believe there are strong logical arguments for not reporting relative values alone. Relative risk statistics do not allow a fair comparison of benefits and harms in the same way as absolute values do, said lead researcher Holger Schünemann of the Department of Clinical Epidemiology and Biostatistics at McMaster University in Ontario, Canada.

"If relative risk is to be used, then the absolute change in risk should also be given, as relative risk alone is likely to misinform decisions," he said.

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