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So last weeks blog focused on anchoring bias.  Remember Phillip with the ‘flu’ who unfortunately ended up with meningococcal meningitis?  This week we are going to explore Information and availability bias.

Information bias is the belief that the more information you can gather to support your decision the better.  Now it is fair to say that we do need to enquire enough to support our diagnosis, but we need to ensure that our history-taking is valuable and avoid gathering information for it’s own sake, or because we are curious.    Availability bias is our tendency to assume a diagnosis is more likely or frequent if it readily comes to mind, e.g. a recent missed diagnosis of meningitis.    If there is a condition we haven’t seen for a long time, (i.e. less available) we might be less likely to diagnose it, even if it’s common.  The availability cascade occurs when a belief becomes more plausible when it is reiterated from several sources, e.g. the rumour is more likely to be true the more people it is heard from.

It is interesting to reflect how much we rely upon availability bias.  We continually use it in our clinical work to reach a ‘quick’ diagnosis.   A patient presents with a recognisable pattern of symptoms, we match it to the bank of  ‘illness’ scripts in our head, and make the diagnosis.   This method of diagnosis is efficient and reliable, BUT only if we always check for the diagnoses not to be missed.   We need to gather enough information to not only confirm our diagnosis, but also to rule out the other diagnoses that we should be considering, especially the serious ones not to be missed.  When reflecting on the information we have to make a decision, we need to ensure that it is truly relevant, rather than just available.

Jill Klein, in her paper on the pitfalls of diagnosis and prescribing, suggests a useful set of rules for good decision-making:

  • Be aware of base rates
  • Consider whether data are truly relevant, rather than just salient
  • Seek reasons why your decisions may be wrong and entertain alternative hypotheses
  • Ask questions that would disprove, rather than confirm, your current hypothesis
  • Remember that you are wrong more often than you think.

Availability bias is particularly relevant for those GPs working within a focused scope of practice.  When you are seeing more presentations in a particular area, e.g. women’s health, mental health, skin cancer medicine, be aware that these diagnoses are more ‘available’ to you.   Yes, you are more likely to have enhanced expertise in these areas, but it doesn’t mean that patient is more likely to have a particular diagnosis.  Similarly, consider your patient demographic profile and scope of practice if you are studying for exams.  Think about how what you see in your clinical work will inform how you answer the exam questions.  Remember that the  Fellowship exams are assessing your competence to practice unsupervised in GP in any context within Australia.

Set yourself a challenge this week to think a little about Information and Availability Bias – particularly the latter.   How much do you rely on pattern recognition rather than generating and testing an hypothesis – when do you use each approach and why?

Consider these biases when approaching patients and feel free to engage in the clinical reasoning challenge on my  Facebook page. Perhaps you’d like to share your thoughts  on what availability biases influence your practice?

Next week we’ll be looking at Overconfidence and how it influences our decision-making (or maybe we’re all so awesome that we don’t need to consider it)!

References:

Croskerry, P. (2015). 50 Cognitive and Affective Biases in Medicine. In. Dalhousie University: Critical Thinking Program.

Elstein, A. S., & Schwarz, A. (2002). Clinical problem solving and diagnostic decision making: selective review of the cognitive literature. BMJ : British Medical Journal, 324(7339), 729-732.

Klein, J. G. (2005). Five pitfalls in decisions about diagnosis and prescribing. BMJ : British Medical Journal, 330(7494), 781-783.

2 thoughts on “When you can’t see the forest for the trees…”

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