The problem of psychological noise

In this blog post we will round up our review of cognitive biases and their influence on clinical judgment. Noise is the title and theme of a book by three giants of cognitive psychology – Daniel Kahneman, Olivier Sibony, and Cass Sustein. In the book, the three leading experts on the psychology of judgment and decision-making highlighted a group of subconscious processes which impairs human judgment in very subtle but significant ways. They labelled these collectively as ‘noise‘ – a concept they defined as ‘the unwanted variability of judgments’.

CC BY-SA 3.0, Link

To illustrate noise, they gave such examples as the following:

  • Two doctors arriving at different diagnoses for the same patient
  • The same doctor arriving at different conclusions when faced with the same situation but at different times
  • When decision-making is influenced by such factors as stress, hunger, fatigue, mood, the time of the day, the weather, or other unrelated events that preceded the decision-making.
  • When factors such as habits, personality, and values influence the decisions individual doctors make
  • When different people arrive at different opinions at performance appraisals
  • When social factors such as who speaks first in a group influences the judgments of those who speak subsequently – the result of what they called an ‘information cascade
Static noise. Douglas Cootey on Flickr. https://www.flickr.com/photos/darkstream/3404310598

With regard to Medicine, a factor that featured prominently in the book is what the authors referred to as the ‘sheer magnitude‘ of noise plaguing the profession. Whilst they lauded the differences of opinions that exist between doctors as valuable sources of diversity, they argued that clinical judgments are different from opinions because they are not expected to be subject to the whims of individuals. They further stressed that good decision-making requires professionals to separate their values from the facts of the matter, adding that ‘good decision-making must be based on objective and accurate predictive judgments that are completely unaffected by hopes and fears, or by preferences and values‘. They also emphasised that ‘failing to make the correct judgment can have serious consequences‘ such as not prescribing the correct treatments.

Worley noise. Somon Strandgaard on Flickr. https://www.flickr.com/photos/12739382@N04/2564255320

To mitigate the malign influence of noise, the authors proffered several recommendations which came under the general remit of decision hygiene. The most important suggestion they made is for institutions to adopt rules, guidelines, and algorithms which have been shown to be effective in minimising the effect of individual proclivities in decision-making. They illustrated the efficacy of this approach with the example of the success of the Apgar score in providing uniformity in the assessment of newborn babies. Indeed they predicted that ‘the medical profession is likely to rely on algorithms more and more in future‘ because ‘they promise to reduce both bias and noise and to save lives and money in the process’.

Blue noise. Stinging Eyes on Flickr. https://www.flickr.com/photos/martinlatter/7332341812

Another important recommendation they made was to incorporate the ‘wisdom of crowds‘ approach to decision-making processes. This strategy involves selecting diverse highly-skilled professionals, and then aggregating their independent judgements. Examples of this approach is the seeking of second opinions, and the implementation of the Delphi technique of collating opinions of group members independently. A related approach is adopting what they termed ‘the crowd within‘ technique whereby professionals reassess complex cases at a later time, or reassess the cases by ‘actively trying to argue against’ themselves.

Noise. Jon-Rellin on Flickr. https://www.flickr.com/photos/jonrellim/28129950217/

We have now completed our review of cognitive biases and will next explore the impact of memory, and its failures, on patient safety.

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