Differential diagnosis

6,752 views
6,434 views

Published on

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.

Published in: Health & Medicine
0 Comments
4 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
6,752
On SlideShare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
0
Comments
0
Likes
4
Embeds 0
No embeds

No notes for slide
  • Preps:[ ] http://www.youtube.com/watch?v=PIsNt_7sah4&context=C424eec3ADvjVQa1PpcFNro-9j28igPaz8S5f7gha2qiN_6PrMWIc7:00, 8:45/9:30[ ] http://en.wikipedia.org/wiki/List_of_cognitive_biases[ ] http://www.medlit.info/member/medical_error_news/menv12i3/dispositions.htm[ ] http://www.youtube.com/watch?v=PIsNt_7sah4&context=C424eec3ADvjVQa1PpcFNro-9j28igPaz8S5f7gha2qiN_6PrMWIc 19:00[ ] http://www.harding-center.com/fact-boxes/mammographyhttp://www.harding-center.com/fact-boxes/psa-screening[ ]
  • Your challenge: this is the MOST important topic of your life when making decisions of any type. Requires constant vigilance!  My challenge: I’ll be teaching this topic to learners of all stages, including experts in diagnosis far beyond my own acumen, so don’t expect ME to be a master diagnostician because I’ve done research in this! Also, this topic can be extremely self-referential and at times dull so I’ll do my best to make it spicy and provocative. We’ll start off talking about diagnosis.
  • I’ll discuss the vocabulary words and then provide some visual examples and movies so the words actually make sense.
  • Heuristic: mental short cuts to ease the cognitive load of making a decision. Examples of this method include using a rule of thumb, an educated guess, an intuitive judgment, or common sense.
  • GerdGigerenzer, German professor of adaptive behavior and cognition is a prolific writer on Heuristics. Here he is talking about the “Angle of Gaze Heuristic” in sports.And speaking of patient safety, Here’s an example of a Sully Sullenberger applying this heuristic in a life or death situation.
  • ‘Prescribe macrolides only if the child is older than3 years and has had fever formore than 2 days. Otherwise, do not prescribe macrolides.75% sensitivity with other tools, 72% sensitivity with this heuristic.
  • I’ll be talking about Cognitive dispositions to respond, cognitive biases and cognitive errors a little bit later in a broad context.
  • Instead of playing a “Match-up” game, I’ve organized the new unfamiliar words with their simpler intuitive partners.I want you to reflect on a recent M&M, misdiagnosis or patient error that you’ve experienced recently.Take a few minutes in a group of two or three looking at the Heuristics and Biases list and share an example.SatisficePortmanteau of “Satisfy and Suffice”
  • Here’s an example of representative restraint – trying to hammer a square peg into a round hole. Nice pattern, wrong fit.
  • Here are some examples of some Dual Process Models
  • Type I process: the hard-wired, specialized parts of the brain that deal with specific needs of our existence e.g. parenting, face recognition, cooperative behaviors, language acquisition, foraging, anticipation of emotional states of othersType 2 processes: are deliberately used to solve reasoning and decision problems in a systematic, analytical way. They follow rules of logic and science and generally deliver error-free solutions providing that everything works appropriately, but this isn’t always the case. Consider, for example, a laboratory diagnostic test that depends upon a technologically complex analyzer. All of the decisions made in selecting the appropriate test, procuring the sample, preparing it for the analyzer, and providing appropriate training for the technician who operates it, might prove futile if an incorrect calibration procedure was followed. Such Type 2 process errors may prove more consequential because a greater level of confidence is usually placed in the data they provide
  • Now that we got the analytical, Type II explanations out of the way, here are some faster approaches to the same topic:House/Sherlock Holmes vs Watson/computerGladwell's Blink, Groopman's How Doctors ThinkOccam's razorHickam's dictum (search satisficers; portmanteau of satisfy/suffice)Dysrationalia override (hard vs soft stops in EPIC, someone exclaiming "oh, you KNOW better than to xxx!")Fuzzy trace theory (reciting my talk verbatim vs saying "oh heuristics are like shortcuts?  They're great when you have checks and balances.")
  • House:His Medical Team:
  • Sherlock HolmesHis quote: “deduction” actually is Abductive reasoning aka “educated guess or hand-waving” of following a hypothesis to its logical conclusion“Deduction” moving from the general to the specific in derivation“Induction” moving from thespecific to the general in assuming patterns exist
  • IBM QA computer uses an algorithm approach and is able to calculate the likelihood of a particular answer and its confidence when answering. I don’t know the details, but I’m assuming its similar to Bayesian reasoning which we’ll delve into after a few more examples.
  • Thin-slicingFirst Impressions. There are flaws of the anchoring heuristic though...
  • Eg. Polyuria/polydipsia/polyphagiaThe simplest solution is usually the correct oneOccam’s razor is inherently heuristic (rule of thumb) and not considered an irrefutable principle of logic.It is attributed to William of Occam (a 14th century English logician and Franciscan friar)Alternate descriptors include:Plurality should not be posited without necessity (pluralitas non estponenda sine necessitate)Entities must not be multiplied beyond necessity (ntia non suntmultiplicandapraeternecessitatem)Law of Parsimony and ‘Diagnostic parsimony‘In medical terms it is often translated into the law of diagnostic parsimony – to try to come up with a ‘unifying’ diagnosis that can explain all the patient’s problems (i.e. to invokeOccam’s Razor)Diagnostic parsimony advocates that when diagnosing a given injury, ailment, illness, or disease a doctor should strive to look for the fewest possible causes that will account for all the symptoms.http://lifeinthefastlane.com/2010/06/funtabulously-frivolous-friday-five-016/
  • The medical counterargument to Occam’s razorSaint’s Triad = Epigastric pain with eating, RUQ after eating, LLQ pain randomlyPatients can have as many diseases as they damn well pleaseAttributed to Dr John B Hickam (Duke University and Chairman of medicine at Indiana University)The actual process that occurs when diagnosing a patient is a continuous flow of hypothesis and testing of that hypothesis, then modifying the hypothesis, and so on…In the context of this method, the principle of Hickam’s dictum asserts that at no stage should a particular diagnosis be excluded solely because it doesn’t appear to fit the principle of Occam’s razor.The principle of Occam’s razor, or parsimony, does not demand that the diagnostician necessarily opt for the simplest explanation, but instead guides the medical practitioner to seek explanations, without unnecessary additional assumptions, which are capable of accounting for all relevant evidence.It is often statistically more likely that a patient has several common diseases, rather than having a single rarer disease which explains their myriad symptomsIt holds similar principles of Walter Chatton’s ‘anti-razor hypothesis’Whenever an affirmative proposition is apt to be verified for actually existing things, if two things, howsoever they are present according to arrangement and duration, cannot suffice for the verification of the proposition while another thing is lacking, then one must posit that other thing
  • Here are some examples of some Dual Process ModelsType I vs Type II predominates in the literature, but I don’t think it’s perfect. There’s some “abductive” hand waving that goes on.
  • Model for diagnostic reasoning based on pattern recognition and dual-process theory. The model is linear, running from left to right. The initial presentation of illness is either recognized or not by the observer. If it is recognized, the parallel fast, automatic processes of System 1 engage, whereas if it is not, the slower, analytical processes of System 2 engage instead. Determinants of System 1 and 2 processes are shown in dotted line boxes. Repetitive processing in System 2 leads to recognition and default to System 1 processing. Either system may override the other. 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.
  • Cognitive fuzzy maps (CFMs) are conceptual, graphic representations similar to a graph with nodes linked by branches. In contrast to a standard graph (such as a decision tree), a CFM represents a complex system without a given direction, as each node may have several univocal or reciprocal connections with other nodes. These connections may have a positive or a negative effect on other nodes, such as to activate or inactivate the linked node. Furthermore, each node does not represent an on/off switch, but, instead, each node may be partially active or inactive, varying between 0 and 1.It simulates the additive and subtractive tallying method that our brains use.Ex: Strep throat vs Viral Pharyngitisvsgonococcalpharyngitisvsdiptheriae, etc.
  • Blink = thin slicingInductive vs Deductive reasoningHRecognition primed
  • Pretest and post-test probabilities
  • Two ways of calculating the probability that a woman who tests positive in mammography screening actually has breast cancer (positive predictive value). The left side illustrates the calculation with conditional probabilities, and the right side with natural frequencies. The four probabilities at the bottom of the left tree are conditional probabilities, each normalized on base 100. The four frequencies at the bottom of the right tree are natural frequencies. The calculation using natural frequencies is simpler (smiling face) because natural frequencies are not normalized relative to base rates of breast cancer, whereas conditional probabilities (or relative frequencies) are, and need to be multiplied by the base rates. (The formula to calculate the positive predictive value is known as Bayes’s rule.)
  • Now that we’ve covered the vocabulary words, I’ll fill them in with a little more context to make some sentences.Naturalistic decision making method vs Heuristics and biases Expertise and decisional algorithmsField vs laboratory (JAMA Rational Clinical Examination)Definition of ExpertiseSources of Intuition  - Skilled Intuition as Recognition - Imperfect Intuition - Professional IntuitionAugmenting Professional Judgment - use of algorithms - Fast and Frugal tree vs HDPI vs ED RN triage Qs - Centor criteria
  • Chess players acquire a repertoire of 50K-100K immediately recognizable patterns, enabling them to identify a good move without having to calculate all possible continenciesFirefighters and Military commanders use a heuristic called “take-the-best” (progressive deepening)http://en.wikipedia.org/wiki/USS_Vincennes_(CG-49)In 1988 USS Vincennes shot down an Iranianairbus – US military did a root cause analysis and overhauled its decision making system"gotcha" words -- (if it ain't one, it's another!)Easy to see why the Medical community favors H&B over NDM!Ironically, we DON’T apply our own skepticism to the process of differential diagnosis.Cognitive Dispositions to Respond (CDR) – It’s not enough to say “gotcha!” we need to step back and say how and why did that happen?
  • Don’t fall prey to the unpacking principle and search satisficing bias!
  • Instead of playing a “Match-up” game, I’ve organized the new unfamiliar words with their simpler intuitive partners.I want you to reflect on a recent M&M, misdiagnosis or patient error that you’ve experienced recently.Take a few minutes in a group of two or three looking at the Heuristics and Biases list and share an example.SatisficePortmanteau of “Satisfy and Suffice”
  • Organizational scholar Karl Weick has proposed a simple 5-step process for communicating intuitive decisions and garnering feedback so as to ensure clear understanding on the part of a teamChest painYou think it is GERDPt experienced relief of sx with a trial of a GI cocktail containing lidocaine/maalox in the EDWhat if we’re wrong?Did we have engage in premature closure of diagnosis? Is diagnosis momentum coming into play because GERD is on their problem list and we’re taking that and running with it? (The answer may be Yes, and that’s fine as long as we’re aware and acknowledge it.)I don’t think it is a MI, but what if we’re wrong? (Let’s look at our diagnostic checklist.)
  • 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

    ×