Intro Flashcards

1
Q

Twomey

A

Clinical decision making: combination of implicit and learned characteristics

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2
Q

Wainwright

A

directive vs informative factors

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3
Q

Sackett/Guyatt

A

Evidenced based practice, vs evidence informed practice

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4
Q

EBP

A

Deduction: CDM based on studies designed to answer clinical questions, but diminishes clinical experience, patient values, anecdotal/empirical evidence

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5
Q

EIP

A

induction, abdication, deduction, clustering

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6
Q

Sackett: 3 legged stool

A

clinical experience, research, patient characteristics

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7
Q

Pathways of thinking

A

Sackett

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8
Q

Algorithms

A

step by step protocol, arboization: A+B=C

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9
Q

Exhaustion

A

gathering all patient info before sifting through

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10
Q

Hypothetico-deductive reasoning

A

forming a short lift of potential diagnoses and then performing tests to rule in or out based on subjective

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11
Q

Pattern recognition

A

recognizing condition from past patient scenarios: quick, but can be wrong

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12
Q

Sense making and small wins

A

breaking down complex problems into smaller parts to address individually

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13
Q

Occam’s Razor

A

the simpler explanation, all things equal, is better than a more complex one.

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14
Q

Cognitive Biases: clinical delusional

A

overconfident in your judgements

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15
Q

Cognitive biases: sunk-cost effect

A

following a course of action after a lot of investment in it.

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16
Q

Cognitive biases: recency effect

A

over emphasis on info most readily available to use of what we’ve seen most often lately

17
Q

Cognitive biases: confirmation bias

A

gathering and believing in info that confirms or existing views and not considering what challenges those views (most common)

18
Q

Cognitive biases: anchoring bias

A

allowing an initial reference point to distort our estimations

19
Q

Cognitive biases: illusory correlation

A

drawing a relationship between 2 variables that doesn’t exist

20
Q

cognitive biases: hindsight bias

A

looking at past outcomes as easily predictable when they were not easy to foresee. over crediting ourselves with an outcome

21
Q

Prognosis

A

Qualitative (options), Quantitative (probability), temporal (time)

22
Q

Likelihood ratio

A

tells us how the odds of having a disorder change with either a positive or negative test. Mathematically combines sensitivity and specificity of a test. Spin and Snout

23
Q

Fagan-Baye’s Theorem

A

Describes the probability of an event based on the conditions that might be related to that event - why clustering is important.