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Differential diagnosis

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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.

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Differential diagnosis

  1. 1. Metacognition: Tricks and Traps in Differential Diagnosis Clinton PongTufts/Cambridge Health Alliance PGY-3 Family Medicine Grand Rounds 1/2013
  2. 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. 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. 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. 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. 6. Some examples to get us going.HEURISTICS
  7. 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. 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. 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. 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. 11. http://hlwiki.slais.ubc.ca/index.php?title=Long_tail#Impacthttp://www.medrants.com/?p=3629 _in_medicine
  12. 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. 13. Cognitive Biases/Errors1. Anchoring/adjustment A. First Impressions2. Availability B. Previous experience3. Base-rate neglect C. “Mountains out of Molehills” or vice versa4. Premature closure D. Lock-it in. Prejudice5. Representativeness & E. Typical vs atypical Representativeness restraint6. Search satisficing F. Call off the search7. Unpacking principle G. Call off the dogs8. Context errors H. Red herring
  14. 14. Example of Representative Restraint:Many diagnostic errors occur because we tryto 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. 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. 16. General properties of Type I and Type IIProperty System 1 System 2 Intuitive Analytical (“two/too” analytical) Heuristic NormativeReasoning style Associative Deductive Concrete AbstractCost/Effort Low/Minimal High/ConsiderableAwareness/Automaticity Low/Automatic High/DeliberateSpeed Fast SlowChannels Multiple, parallel Single, linearPropensities Causal StatisticalAction Reflexive, skilled Deliberate, rule-basedPrototypical Yes No, based on setsErrors Common FewReliability Low, variable High, consistentVulnerability to bias Yes Less soAffective valence Often RarelyContext importance High LowPredictive power Low HighScientific rigour Low High
  17. 17. IS IT A TYPE I OR TYPE II SYSTEM PROCESS?What do you think?
  18. 18. House, MD. White board http://differentialdiagnosi.proboards.com/index.cgi?
  19. 19. Sherlock Holmes• "When you have eliminated the impossible, whatever remains, however improbable, must be the truth."
  20. 20. Watson, the IBMQuestion Answering Computer
  21. 21. Malcolm Gladwell
  22. 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. 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. 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. 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. 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. 27. Cognitive Balanced Modeland “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. 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. 29. Clustering of approaches on an intuitive-analytical continuumType I Type II
  30. 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. 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 normalAn 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. 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. 33. DISCOVERING THE REASONING OF INTUITIONHow do we know what we know?
  34. 34. NDM method vs Heuristics and biasesNaturalistic 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. 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. 36. BALANCING SNAP JUDGMENTS AND DELIBERATIVE RUMINATIONBecause something’s gotta give.
  37. 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. 38. Croskerrys 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. 39. • http://links.lww.com/ACADMED/A38
  40. 40. Heuristics and Biases1. Anchoring/adjustment A. First Impressions2. Availability B. Previous experience3. Base-rate neglect C. “Mountains out of Molehills” or vice versa4. Premature closure D. Lock-it in. Prejudice5. Representativeness & E. Typical vs atypical Representativeness restraint6. Search satisficing F. Call off the search7. Unpacking principle G. Call off the dogs8. Context errors H. Red herring
  41. 41. Organizational Communication of Intuitive DecisionsKarl Weick’s Steps (My Medical Version)1. Heres what we face 1. Here’s what we face 1. What do you think we face?2. Heres what I think we 2. What should we do? should do 3. What’s the evidence?3. Heres why 4. Let’s pause now. 1. What if we’re wrong?4. Heres what we should 2. Have we made any cognitive keep our eye on errors? 3. Let’s look at our diagnostic5. Now, talk to me checklist 5. Now, let’s talk about our action plan and to-do list
  42. 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. 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 • DeGowins 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: whats 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

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