Clinical decision making Flashcards

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1
Q

Describe the effect of extraneous factors on clinical decision-making using an example.

A

Junior-senior relationship may lead to the wrong decision being made

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2
Q

What is Confirmatory Bias?

A

The tendency to search for or interpret information in a way that confirms one’s preconceptions, often leading to errors

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3
Q

What is the Sunk Cost Fallacy?

A

Rationally, the only factor affecting future action should be future cost/benefit ratio BUT humans do not always act rationally
Often, the more we have invested in the past, the more we are prepared to invest in a problem in the future

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4
Q

What is the Anchoring Effect?

A

People start with an implicitly suggested reference point (the anchor) and make adjustments to it to reach their estimate – it influences the way people intuitively assess probabilities
In other words, it is a cognitive bias that describes the tendency to rely too heavily on the first piece of information offered when making decisions. Once the anchor is set, future decisions are made by adjusting away from that anchor

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5
Q

What is Gambler’s Fallacy?

A

A logical fallacy involving the mistaken belief that past events will affect future events when dealing with independent events

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6
Q

Define conditional probability.

A

Measures the probability of an event happening given that another event has occurred

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7
Q

What is Bayes’ theorem and what is it used for?

A

It is a theorem that measures conditional probability

It is used in screening that involves false positives and false negatives such as mammograms/breast cancer

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8
Q

State some strategies for improving clinical decision-making.

A
  • Recognise that heuristics and biases may be affecting our judgement even though we may not be conscious of them
  • Counteract the effect of top-down processing by generating alternative theories and looking for evidence to support them rather than just looking for evidence that confirms our preferred theory (confirmatory bias)
  • Understand and employ statistical principles e.g. Bayes’ theorem
  • Use of algorithms and decision support systems
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