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How correct data can give wrong answers

Published on 24 March 2021

How correct data can give wrong answers

We can learn a huge amount about the interpretation of data when reading articles about Covid19. Unfortunately, we see a lot of examples of bad practice and a classic example of that is when we saw the news last week and somebody had observed that 37 people had suffered a blood clot after receiving the AstraZeneca vaccine. This led to widespread panic and a number of countries putting their vaccination program on hold. Every word and fact in the original article may have been correct with the exception of the conclusions drawn. When we share data people will expect a conclusion and if they don’t get one they will draw their own. If we don’t give them all the necessary information then they are likely to come to the wrong conclusion.

There were 3 big problems with the way that the message was communicated.

  1. When somebody draws our attention to a correlation we tend to assume causation – somebody has the jab they subsequently got a blood clot so it is natural to assume that the jab triggered the blood clot even if this is not the case. Some people who have had the jab may have subsequently won the lottery this doesn’t mean the jab is lucky.
  2. They didn’t give baseline or point of comparison, we  should never report data in isolation. When these figures were reported in comparison with people that hadn’t had the jab it was revealed that clot rates were in fact slightly lower.  The data was actually telling us a very different story to the one reported.
  3. If we put all our focus on one side of the equation and ignore the other our decisions are biased. We were focussing on the risks of having the jab but not balancing these with the risks of delaying. Countries put their jabs on hold in the interest of caution, however all the data available at that time strongly indicated that the risks of delaying strongly outweighed the risk of continuing. So the cautious approach had the higher risk. This problem can be exacerbated with a blame culture. When we are held responsible for anything that goes wrong as a result of an action we take then it is natural to focus on that side of the equation and to favour inaction even if that is the higher risk option. So even with everything we know could we honestly say we wouldn’t take the same decision.

Author: Ian Robertson

Date Published: 24th March 2021

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