Aims: to give clinicians tools they can use to improve their ability to reflect on a differential dx and aid in correct diagnosis Objectives:  -- define a dual process cognitive model used when making a diagnosis -- recognize common heuristics and their related cognitive errors and biases -- apply a systematic, routine method for differential diagnosis generation.

1. Metacognition:
Tricks and Traps in
Differential Diagnosis
Clinton Pong
Tufts/Cambridge Health Alliance
PGY-3 Family Medicine
Grand Rounds 1/2013

2. Aims and Objectives
• Aims: to give clinicians tools they can use to
improve their ability to reflect on a differential
dx and aid in correct diagnosis
• Objectives:
– define a dual process cognitive model used when
making a diagnosis
– recognize common heuristics and their related
cognitive errors and biases
– apply a systematic, routine method for differential
diagnosis generation

3. Challenges
• Diagnosis
• “It is every doctor’s measure of his own
abilities; it is the most important ingredient in
his professional self-image.”
– Dr. Sherwin Nuland
• It requires CONSTANT VIGILANCE!
(Croskerry, A Universal Model of Diagnostic Reasoning,
Academic Medicine, Vol. 84, No.8, August 2009;
Nulund, SB. How We Die: Reflection on Life’s Final Chapter.
New York, NY: Alfred A Knofp;1994)

4. DeGowin’s Quotable:
• Disease is a four-dimensional story,
– which follows the biologic imperatives
of its particular pathophysiology in
specific anatomic sites as influenced by
the unique characteristics of this
patient
• Your task is not verbal, but
cinematic;
– construct a pathophysiologic and
anatomic movie of the onset and
progression of the illness:
– the words are generated from the
images, not the images from the words

5. Managing One’s Own Thinking
• Metacognition
– the act of “thinking about thinking (and feeling)”
– Of one’s own and another’s
• Heuristic
– Greek: "Εὑρίσκω", "find" or "discover"
– strategies using readily accessible, though loosely
applicable, information to control problem solving
– Rules of Thumb
• “Better safe than sorry”

6. Some examples to get us going.
HEURISTICS

7. Simple Heuristics That Make Us Smart:
Gaze Heuristic
• Sports analogy Airplane analogy
• http://www.youtube.com/watch?v=PIsNt_7sah4&context=C424eec3ADvjVQa1PpcFNro-9j28igPaz8S5f7gha2qiN_6PrMWIc
– 7:00, 8:45/9:30
Marewski, J et al. Good judgments do not require complex cognition. Cognitive
Processing. May 2010, Volume 11, Issue 2, pp 103-121.

8. HDPI vs Fast and Frugal Tree
• http://www.youtube.com/watch?v=PIsNt_7sah4&context=C424eec3ADvjVQa1PpcFNro-
9j28igPaz8S5f7gha2qiN_6PrMWIc
• 19:00
Wegwarth O, et al. Smart strategies for doctors and doctors-in-training: heuristics in
medicine. Med Educ. 2009 Aug;43(8):721-8.

9. HDPI vs Fast and Frugal Tree
• http://www.youtube.com/watch?v=PIsNt_7sah4&context=C424eec3ADvjVQa1PpcFNro-
9j28igPaz8S5f7gha2qiN_6PrMWIc
• 19:00
Wegwarth O, et al. Smart strategies for doctors and doctors-in-training: heuristics in
medicine. Med Educ. 2009 Aug;43(8):721-8.

10. Fast and Frugal Tree: CAP in Kids
Typical vs Atypical?
Wegwarth O, et al. Smart strategies for doctors and doctors-in-training: heuristics in
medicine. Med Educ. 2009 Aug;43(8):721-8.

11. http://hlwiki.slais.ubc.ca/index.php?title=Long_tail#Impact
http://www.medrants.com/?p=3629 _in_medicine

12. When Heuristics Fail
• Cognitive “Dispositions to Respond”
• Cognitive biases
– Predictable patterns of deviation in judgment that
occur in particular situations
– Sometimes lead to perceptual
distortion, inaccurate judgment, illogical
interpretation, or irrationality
• Cognitive Errors

13. Cognitive Biases/Errors
1. Anchoring/adjustment A. First Impressions
2. Availability B. Previous experience
3. Base-rate neglect C. “Mountains out of
Molehills” or vice versa
4. Premature closure D. Lock-it in. Prejudice
5. Representativeness & E. Typical vs atypical
Representativeness
restraint
6. Search satisficing F. Call off the search
7. Unpacking principle G. Call off the dogs
8. Context errors H. Red herring

14. Example of Representative Restraint:
Many diagnostic errors occur because we try
to fit the data to our hypothesis rather than
fitting the hypothesis to our data.
http://www.medrants.com/archives/4917
http://www.flickr.com/photos/epublicist/

15. Two Approaches to Decision-Making
• Cognitive processing
– What goes on in our brains when we are
developing a differential diagnosis and how do we
arrive at our final diagnosis?
• We use two types of thinking:
– Type I heuristic
– Type II analytic

16. General properties of Type I and Type II
Property System 1 System 2
Intuitive Analytical (“two/too” analytical)
Heuristic Normative
Reasoning style
Associative Deductive
Concrete Abstract
Cost/Effort Low/Minimal High/Considerable
Awareness/Automaticity Low/Automatic High/Deliberate
Speed Fast Slow
Channels Multiple, parallel Single, linear
Propensities Causal Statistical
Action Reflexive, skilled Deliberate, rule-based
Prototypical Yes No, based on sets
Errors Common Few
Reliability Low, variable High, consistent
Vulnerability to bias Yes Less so
Affective valence Often Rarely
Context importance High Low
Predictive power Low High
Scientific rigour Low High

17. IS IT A TYPE I OR TYPE II
SYSTEM PROCESS?
What do you think?

18. House, MD. White board
http://differentialdiagnosi.proboards.com/index.cgi?

19. Sherlock Holmes
• "When you have
eliminated the
impossible, whatever
remains, however
improbable, must be
the truth."

20. Watson, the IBM
Question Answering Computer

21. Malcolm Gladwell

22. Occam’s Razor:
The Quest for the Holy Diagnostic Parsimony
Pluralitas non est
ponenda sine
necessitate
• “Plurality should not be
posited without necessity.”
• Develop a ‘unifying
diagnosis’ to explain all the
patient’s problems
http://en.wikipedia.org/wiki/William_of_Ockham

23. Hickam’s Dictum:
The Anti-Razor Cognitive Balance
Patients can have
as many diseases
as they damn well
please
• A continuous flow of hypothesis
and testing of that
hypothesis, then modifying the
hypothesis, and retesting and so
on…
• At no stage should a particular
diagnosis be excluded solely
because it doesn’t appear to fit
the principle of Occam’s razor.
http://medicine.iupui.edu/DoM/about/history/

24. Dual Process Theory
• Dual process models:
– Type I heuristic vs. Type II analytic
– Associative vs. Rule-Based
– Mindless vs. Mindful
• Cognitive Balanced Model
• Fuzzy Trace Model

25. Croskerry’s Dual-process Model
A System 1 response may proceed directly to a diagnosis, or the outputs
from both systems pass into a calibrator where interaction occurs to produce
the final diagnosis. A ‘cognitive miser’ function prevails—the tendency to
default to a state that consumes fewer cognitive resources.
Croskerry P. A universal model of diagnostic reasoning. Acad Med. 2009
Aug;84(8):1022-8.

26. How the Two Systems Interact
• Rational Override
– A Type 1 response is inappropriately triggered
• The pattern isn’t matching the data bank
• The decision maker subsequently sets up a Type 2 analytical
approach
– The monitoring capacity of Type 2 over Type 1
allowing it to reject the latter
• Dysrationalia Override
– dysrationalia, the key diagnostic criterion for which is
• ‘…a level of rationality, as demonstrated in thinking and
behavior, that is significantly below the level of the
individual’s intellectual capacity…’
– Cognitive lassitude aside, these ‘irrational’ behaviors
account for significant diagnostic failure

27. Cognitive Balanced Model
and “Fuzzy Trace Model”
++++
+- ----
++
-+-+
-+
Lucchiari C. Cognitive balanced model: a conceptual scheme of diagnostic decision
making. J Eval Clin Pract. 2012 Feb;18(1):82-8.

28. Dysrationalia override
• “I should have known
better!”
– Sleep
– Hunger
– Irritability
– Inattentiveness
– Distractions
– Fear
– Prior experience
• Rational overrides
– Externalities (e.g. other
staff, EPIC Hard Stops)
– Internalities (checklists)

29. Clustering of approaches on an
intuitive-analytical continuum
Type I Type II

30. Judging Probabilities
• Bayes’ Theorem
– Attributed to the Reverend Thomas Bayes
– For the simple case of a binary hypothesis (H and not-
H, such as cancer and not cancer) and data D (such as
a positive test), the rule is:
• p(H|D) = p(H)p(D|H)/[p(H)p(D|H) + p(not-H)p(D|not-H)]
– where p(D|H) is the * Test result = Post Test Probability
• Pretest Probability posterior probability, p(H) is the prior
probability, p(D|H) is the probability of D given H, and p(D|not-H)
is the probability of D given not-H.
• Bayesian Reasoning
– A procedure for updating the probability of a
hypothesis in light of new evidence

31. Bayes’ Theorem
Pre- and post-test probabilities of anaemia for 3 categories of conjunctival
appearance: pale (little or no red colour), borderline (neither clearly red nor clearly
pale), and normal
An Excel spreadsheet for calculating post-test probabilities for dichotomous tests.
Glasziou, P. Which methods for bedside Bayes? Evid Based Med 2001;6:164-166
http://ebm.bmj.com/content/6/6/164.full

32. Bayes’ Theorem and Natural Frequencies
• http://www.harding-center.com/fact-boxes/mammography
• http://www.harding-center.com/fact-boxes/psa-screening Gigerenzer, G. et al. (2008). Helping Doctors and Patients make Sense of Health
Statistics. Psychological Science in the Public Interest, 8(2), 53-96.

33. DISCOVERING THE REASONING OF
INTUITION
How do we know what we know?

34. NDM method vs Heuristics and biases
Naturalistic decision making
(NDM) method Heuristics and Biases
• Gary Klein • Daniel Kahnemann
• Intuitive marvels • Scientific skeptics
• “Demystifying
intuition” • “Illusion of validity”
• Research on • “Overconfidence bias”
– Chess players • Research on
– Firefighters – Clinical judges
– Military Commanders • Clinical psychologist vs computer
– Nurses algorithms
• Cognitive Task Analysis – Sample size for psychological
– Semi-structured retrospective experiments
interviews • Methodologists and statisticians
– Investigating cues, context and • Computation vs intuition
strategies that skilled decision-
makers apply • Head to Head Studies

35. Field vs Laboratory
• We are human. • We are not Gods.
– Bounded rationality – Unbounded “demon”
rationality
• Our world is complex and
messy. • The lab is a sterile system
with only one variable.
• There are all sorts of
obstacles, time pressures • We can’t study
and distractions. EVERYTHING up the Yin-
– Trade-offs Yang!
– Subject to cognitive
overload

36. BALANCING SNAP JUDGMENTS
AND DELIBERATIVE RUMINATION
Because something’s gotta give.

37. Checklists
• Four checklists (for checks and balances)
– Croskerry’s General
– Diagnostic Time-Out
• Heuristics & Biases / Cognitive Dispositions to Respond
• Differential Diagnosis
– Organizational Communication

38. Croskerry's General
• Obtain your own complete medical History
• Perform a focused and purposeful Physical
• Generate initial hypotheses and differentiate
these with additional H&P and testing
• Take a Diagnostic timeout
– Am I comprehensive?
– H&B check-in?
– Pre-mortem M&M “crystal ball analysis”
• Plan and follow up

39. • http://links.lww.com/ACADMED/A38

40. Heuristics and Biases
1. Anchoring/adjustment A. First Impressions
2. Availability B. Previous experience
3. Base-rate neglect C. “Mountains out of
Molehills” or vice versa
4. Premature closure D. Lock-it in. Prejudice
5. Representativeness & E. Typical vs atypical
Representativeness
restraint
6. Search satisficing F. Call off the search
7. Unpacking principle G. Call off the dogs
8. Context errors H. Red herring

41. Organizational Communication of
Intuitive Decisions
Karl Weick’s Steps (My Medical Version)
1. Here's what we face 1. Here’s what we face
1. What do you think we face?
2. Here's what I think we 2. What should we do?
should do 3. What’s the evidence?
3. Here's why 4. Let’s pause now.
1. What if we’re wrong?
4. Here's what we should 2. Have we made any cognitive
keep our eye on errors?
3. Let’s look at our diagnostic
5. Now, talk to me checklist
5. Now, let’s talk about our
action plan and to-do list

42. Take Home Points
• Tricks:
– Heuristics are “Type I” mental shortcuts that “thin-slice” intuitive first
impressions
– They are excellent tools for diagnosis when checks and balances are in
place
• Traps:
– Heuristics are prone to cognitive biases and therefore, error
– Use checklists to use avoid these pitfalls
• Checklists
– Croskerry’s General
– Diagnostic Time-Out
• Heuristics and Biases / Cognitive Dispositions to Respond
• Differential Diagnosis
– Organizational Communication

43. References
• Croskerry, P. Clinical cognition and diagnostic error: applications of a dual • Books
process model of reasoning. Adv in Health Sci Educ (2009) 14:27–35 • DeGowin's Diagnostic Examination, Ninth Edition (Paperback) by Richard
– http://www.ncbi.nlm.nih.gov/pubmed/19669918 LeBlond (Author), Donald Brown (Author), Richard DeGowin (Author)
• Croskerry P. The importance of cognitive errors in diagnosis and strategies • Groopman, Jerome. How Doctors Think. Mariner Books © 2008.
to minimize them. Acad Med. 2003 Aug;78(8):775-80. • Kassirer, Jerome. Learning Clinical Reasoning. Williams and Wilkins. ©
– http://www.ncbi.nlm.nih.gov/pubmed/12915363 1991.
• Croskerry P. A universal model of diagnostic reasoning. Acad Med. 2009
Aug;84(8):1022-8.
• Lectures
– http://www.ncbi.nlm.nih.gov/pubmed/19638766
• Lecture: The Art of Critical Decision Making” Professor Michael A. Roberto,
• Ely JW, et al. Checklists to reduce diagnostic errors. Acad Med. 2011
Mar;86(3):307-13. • Lecture: Gerd Gigerenzer on "Simple heuristics that make us smart“
– http://www.ncbi.nlm.nih.gov/pubmed/21248608
Harding Center for Risk Literacy
– http://www.youtube.com/watch?v=PIsNt_7sah4&context=C424eec3ADvjV
• Marewski, J et al. Good judgments do not require complex cognition. Qa1PpcFNro-9j28igPaz8S5f7gha2qiN_6PrMWIc
Cognitive Processing. May 2010, Volume 11, Issue 2, pp 103-121.
– http://link.springer.com/article/10.1007/s10339-009-0337-0/fulltext.html
• Websites
• Gigerenzer, G. et al. (2008). Helping Doctors and Patients make Sense of
Health Statistics. Psychological Science in the Public Interest, 8(2), 53-96. • Baye’s Theorem definition
– http://www.psychologicalscience.org/journals/pspi/pspi_8_2_article.pdf – http://www.harding-center.com/wichtige-begriffe/terms/a-d
• Glasziou, P. Which methods for bedside Bayes? Evid Based Med • Occam’s Razor and Hickam’s Dictum
2001;6:164-166 – http://lifeinthefastlane.com/2010/06/funtabulously-frivolous-friday-five-
– http://ebm.bmj.com/content/6/6/164.full 016/
– http://en.wikipedia.org/wiki/William_of_Ockham
• Graber M, et al. Reducing diagnostic errors in medicine: what's the goal?
Acad Med. 2002 Oct;77(10):981-92. • DB’s Medical Rants on the Long Tail
– http://www.ncbi.nlm.nih.gov/pubmed/12377672 – http://www.medrants.com/archives/3637
• Kahneman D, Klein G. Conditions for intuitive expertise: a failure to – http://www.medrants.com/archives/3629
disagree. Am Psychol. 2009 Sep;64(6):515-26. doi: 10.1037/a0016755. • “Separating clinicians from automatons: the long tail”
– http://www.ncbi.nlm.nih.gov/pubmed/19739881 – http://doctorrw.blogspot.com/2008/08/separating-clinicians-from-
automatons.html
• Kassirer JP. Teaching clinical reasoning: case-based and coached. Acad
Med. 2010 Jul;85(7):1118-24.
– http://www.ncbi.nlm.nih.gov/pubmed/20603909
• Lucchiari C. Cognitive balanced model: a conceptual scheme of diagnostic
decision making. J Eval Clin Pract. 2012 Feb;18(1):82-8.
– http://www.ncbi.nlm.nih.gov/pubmed/21999310
• Wegwarth O, et al. Smart strategies for doctors and doctors-in-training:
heuristics in medicine. Med Educ. 2009 Aug;43(8):721-8.
– http://www.ncbi.nlm.nih.gov/pubmed/19573016