How do medical students learn Clinical Reasoning

1
How do medical students learn Clinical Reasoning?
Professor John Boulton and Dr Stephanie
Oak Faculty of Health. The University of Newcastle
2

• Students taught by
• Paper cases, video, PBL tutorials which stress
  hypothetico-deductive approach
• bedside small group and individual tuition
• apprenticeship

3
How do we measure competence in clinical
reasoning?

• Underlying knowledge base by written papers and
  MEQ
• Formative clinical assessments within tutorial
  process
• Assessments on short case presentations
• Assessments on long case presentations

4
Problems in the measurement of competence

• Inter-observer variation not known
• Questionable validity of clinical assessment as
  measure of competence in patient care
• Teacher-centred not student-centred
• Tolerance of exam stress becomes an independent
  variable

5
Problems in the measurement of competence

• There is difficulty with setting
  criterion-referenced competencies for cognitive
  process versus practical skills eg
  cardio-pulmonary rescusitation
• What objective measures of stage of expertise in
  clinical reasoning do we have other than accuracy
  of diagnosis?
• We have no valid objective measures of early
  differences in clinical reasoning which could be
  addressed by extra tuition

6
Problems in the measurement of competence

• Different levels of competency reached by
  different students after same duration of
  clinical attachment
• There is no adjustment in duration of clinical
  attachment according to the rate of development
  of competency

7
A challenge for medical educatorsthe cognitive
steps on the pathway to expertise in clinical
reasoning are unknownwe are unable to diagnose
barriers to clinical reasoningwe cannot apply
specific educational treatment to cause of
barrierSo how can we approach the problem?
8
What I observed in year 3 students

• Questions in history-taking were asked in the
  framework of the medical model
• But in an interrogatory style rather than in a
  narrative style
• What is wrong with you?
• Where do you come from?
• How old are you?
• Despite teaching in communication skills from
  the beginning of Year 1

9
Conscious focus by student on need to cover all
topics, regardless of context. So..

• Do you smoke?
• Do you take medication?
• Do you drink alcohol?
• Do you drink a lot?

10
In other words...The student first assembles
the data gathered from the history and then
applies deductive reasoning as learned in
problem-based tutorials as a tool post-hoc
11
One view of the steps in clinical reasoning from
novice to expert (Schmidt and Boshuizen Educ
Psychol Rev 19935205)

• Stage 1 Novice
• Stage 2 Intermediate
• Stage 3 Expert

12
Stage 1 Novice Elaborated causal networks
Clotting mechanism
CVS physiology
Symptoms of AMI
CVDepidemiology
Hypothesis 1a
Signs of AMI
HDR
Hypothesis 1b
13
Stage 1 Novice Elaborated causal networks

• Encapsulated knowledge (after Schmidt 1990)
• Clusters do not overlap
• Basic science application low knowledge base
• Hypothetico-deductive reasoning applied post hoc

14
Problems with novice stage of clinical reasoning
1

• Student fails to integrate communication skills
  into dynamic process of taking a history
• Result low level of affective interaction
• ie insensitive to patients unspoken messages

15
Problems with novice stage of clinical reasoning
2

• The student focusses on covering all the topics
  in the history at the cost of generating
  hypotheses in parallel with the interview
• Result few or no hypotheses generated during
  the history taking

16
Problems with novice stage of clinical reasoning
3

• The student fails to ask discriminating questions
  during the history taking
• The student fails to prioritise problems
  according to probability

17
Stage 2 Intermediate Abridged causal networks
Clotting mechanism
CVS physiology
thrombosis in AMI
Symptoms of AMI

CVDepidemiology
Signs of AMI

Hypothesis 1a

Discr Qs P/E
overweight male smoker
Hypothesis 1b
clinical features AMI
18
Stage 2 Intermediate Abridged causal networks

• Clusters overlap knowledge in use
• Create simplified causal model Mental model
  of family of disease
• Basic science application High intermediate
  effect
• (this describes the greater use of basic science
  concepts at the intermediate than at the novice
  or expert stages)

19
Stage 3 Expert Integration of Knowledge Clusters
Pattern recognition

Illness script
P/E Ix
Confirm diagnosis
20
Stage 3 Expert Integration of Knowledge Clusters

• Direct link between history, examination and
  hypothesis
• Illness scripts emerge
• Basic science application low

21
Contemporary debate is framed according to two
interpretations
1. High level of skill in recall from large
library of illness scripts a function of
knowledge
2. A different pattern of clinical reasoning
explains why experts perform better
OR
But is this the whole story? Maybe not We
suggest that there is another dimension to
clinical reasoning called Abduction
22
Abduction

• The ability to produce meaningful
  interpretations from a variety of experiences
  based on a mixture of perceptions and memory
• Peirce C. The philosophical writings of
  Peirce. New York. Dover 1955
• In other words Inference to the best explanation

23
Abduction the default mode of cognition

• The clinician sifts through the data to find the
  explanation that best fits
• then deduction and induction deal with the
  process of hypothesis evaluation

24
If medical teachers assume that clinical
reasoning begins with the generation of
hypotheses rather than with detection of patterns
/ meaning in data, then students will be given
little guidance in the generation of their
initial hypotheses
25
ABDUCTION
Diagnostic hypotheses
Clinical evidences to be explained
Deduction
Induction
Observed/expected data
abstraction
Epistemiological model of diagnostic
reasoning from Magnani, L. 1997
26
Deduction and Induction involve linear forms of
reasoning from general statements (hypotheses) to
observations, or from observations to general
statements (hypotheses) In contrast, in
Abduction the reasoning process involves a
lateral step into a general store of knowledge
that introduces new ideas not contained in either
pre-existing theory or the data themselves
27
Our proposal that the current discourse neglects
the primary effects of

• The setting where, when, with whom you see the
  patient
• The semiotics the meaning of the silent language
  of signs from both the patient and the situation
• The affective dimension
• the patients emotional response to the doctor
  and the doctors emotional response to the
  patient
• PLUS the level of empathy of the doctor

28
Implications for teaching

• 1. Theoretical
• Abduction is qualitatively different from the
  deductive-inductive cycle we teach students
• Abduction is in tension with the
  deductive-inductive cycle
• How does insight into abduction fit with learning
  theory?

29
Implications for teaching

• 2. Practical
• Can abduction be taught? ..Or does it only come
  from experience?
• Can the transition to abductive reasoning be
  identified?
• Can we identify barriers to abductive reasoning ?
• How can we improve the tempo of learning of
• abductive reasoning in students who progress
  slowly?

30
Further implications for teaching

• Move away from blind generation of hypotheses in
  deductive reasoning eg in PBL tutorials
  encouraging students to brainstorm.
• ..to a more focussed teaching of data gathering
  and its interpretation within that semiotic
  context
• ie an explicit integration of knowledge base,
  illness scripts, communication and clinical
  skills from Year 1

31
Further implications for teaching

• As abduction is the default mode for all human
  cognition, are we inhibiting its expression
  through teaching PBL-type deductive reasoning?
• By reinforcing the process of abduction through
  an emphasis on the integration of the semiotic,
  affective and knowledge dimensions, can we
  achieve expertise in clinical reasoning in less
  than 10 000 hours??

32
An empirical approach to the identification of
abductive reasoning
33
An empirical approach to the identification of
abductive reasoning

• This work is being done in collaboration with
  Kirsti Lonka, Professor of Medical Education. The
  Department of Learning, Informatics, Management
  and Ethics (www.lime.ki.se)
• Karolinska Institutet. Stockholm.

34
Aim of current research proposal

• To design a reliable and valid measure of the
  presence of abductive clinical reasoning
• To identify how abductive clinical reasoning can
  be taught within a PBL curriculum framework
• Identify barriers to the emergence of abductive
  clinical reasoning in medical students
• Design ways to overcome barriers to abductive
  clinical reasoning in medical students

35
Proposed methodological approach to the
identification of abductive reasoning

• Analyses of students interviews with virtual
  and standardised patients using think aloud
  protocols , stimulated recall, and observational
  methodologies.
• Proposed measures for use in pilot studies
• Speed to initial concept of working hypothesis
• Accuracy of initial diagnostic concept ie
  validity of cognitive process
• Focus and pattern of questions use of
  discriminating questions to rule in / rule out
• Focus of physical examination and investigations

36
Future Directions

• 1. Expand the theoretical basis of abduction in
  expert clinical reasoning
• 2. Explicit link with educational theory
• in collaboration with
• Kai Hakkarainen and Sami Paavola
• The Centre for Research on Networked Learning and
  Knowledge Building.
• Department of Psychology.
• Helsinki University.