Clinical Reasoning
Clinical Reasoning in
Differential Diagnosis
Experts use 3 main methods or a
combination:

Analytic or Hypothetico-deductive

Non-analytic or Pattern recognition

Pathognomonic signs and symptoms
Analytic Process
Presenting
Clinical
Features
Diagnostic
Hypotheses
Posterior
Probability
A
Dx1
Pr (Dx1)
B
Dx2
Pr (Dx2)
C
Dx3
Pr (Dx3)
Elstein, 1978
Non-analytic Process
Presenting
Clinical
Features
A
Filter
through prior
episodes
A,B,D,F
Diagnostic
Hypotheses
Pr (Dx1)
B
C
D
B,D,G,R
C,F,G,H
Pr (Dx2)
Pr (Dx3)
Combined Model
of
Clinical Reasoning
Both analytic and non-analytic processes combined
Patient
Presents
Case
Representation
Non-analytic
Interactive
Hypotheses
Tested
Analytic
Eva et al.,2002
Implications for Clinical Teachers

Teach around examples

Few, complex examples - suboptimal

Provide many examples

Represent range of presentations of specific
conditions
Implications for Clinical Teachers

Practice with cases should mimic eventual use of
knowledge

Working through textbook cases is NOT enough

Mixed practice with multiple categories mixed together
Implications for Clinical Teachers

Do NOT rely on students to make comparisons
across problems spontaneously

Allow students to identify similarities in underlying
concepts of distinct problems

Relate principles in new examples with those in past
examples

Provide learners with an opportunity to reveal
idiosyncratic mistakes
Implications for Clinical Teachers
Encourage learners to use both analytical
rule knowledge and experiential
knowledge
Cognitive sciences- based training

Research study

2 different methods for training 2nd year
medical students

Traditional classroom based lecture

Cognitive sciences-based approach (KBIT)
Papa et al. 2007
Cognitive sciences- based training

Similarities

Common problem

Identified differentials for problem

Introduced each case via use of prototype
and case example
Cognitive sciences- based training

Differences




KBIT group - 4 example cases per disease
FS group - 1 case example per disease
KBIT group - actively required to apply
knowledge base towards diagnosis of
practice cases (35)
FS group - 4-5 cases, with no control over
students’ active engagement in the cases
Cognitive sciences- based training

Differences

KBIT - immediate online formative and
contrastive feedback tailored to each student

FS - not possible to deliver tailored feedback
Cognitive sciences- based training

Results

KBIT group diagnosed correctly more test
cases than FS group
74.2% vs 59.9%
(P < 0.001; effect size = 1.42)
Cognitive Biases






Representativeness heuristic - overestimating
similarity between people and events
Availability heuristic - too much weight to easily
available info
Overconfidence
Confirmatory bias - bias toward positive and
confirming evidence
Illusory correlation - perceiving two events as
causally related when there is none
Putting initial probability at too extreme a figure
and not adjusting for subsequent info
Klein, 2005.
Summary



Expertise is not a matter of acquiring a
general, all-inclusive reasoning strategy
No one kind of knowledge counts more
than any other
Expertise in medicine derives from both
formal and experiential knowledge
Norman, 2007