1. Diagnostic Decision-Making: How do we do it and how can we (and our learners) improve? META Scholars September 5, 2013

2. Agenda Overview of diagnostic reasoning How good are we? How can we (and our learners) improve?

3. Objectives Be able to describe the basic process of making a diagnosis Acknowledge we struggle with making diagnoses List several ways we can improve our diagnostic skills

4. Overview of Clinical Reasoning Overview of making a diagnosis How our brains deal with it What it actually looks like in practice

5. How do Doctors Think?

6. Data CollectionProblem Representation (Framing) Access Illness Scripts Potential Match Diagnosis!

7. Data collection History Physical examination Laboratory studies Imaging studies

8. Data CollectionProblem Representation (Framing) Access Illness Scripts Potential Match Diagnosis!

9. Problem Representation Making sense of the data obtained Identification of the key elements Categorization Semantic qualifiers Frame things (context is everything)

11. Data CollectionProblem Representation (Framing) Access Illness Scripts Potential Match Diagnosis!

12. Illness Scripts Mental representations of the key elements of specific diagnoses –History –Physical –Labs –Imaging –Response to therapy

13. Acute Coronary Syndrome PericarditisPulmonary embolismAortic Dissection (AD) Epidemiology Older age, risk factors include diabetes, hypertension, dyslipidemia, family history, tobacco use Uremia, auto-immune disease, prior URI, recent MI or heart surgery, malignancy Risk factors of endothelial injury, hypercoaguability, and stasis: recent surgery, active cancer (e.g. adenocarcinoma), medications (e.g. OCP); immobility Older patient, HTN the primary risk. Younger patients also at risk (cocaine, collagen vascular, bicuspic aortic valve…) Time Course Acute onset, not necessarily preceded by exertional angina Acute, but may occur in setting of sub-acute or chronic disease Acute onset usually without progression, unless second PE Acute onset, usually constant Clinical Features (1) History (2) Exam (3) Labs (4)Imaging Advanced Studies 1) Chest pain, with crescendo to maximal pain; often dull and sub- sternal, radiating to arms/shoulders; diaphoresis; dyspnea; nausea/vomiting, diaphoresis. 2) Tachycardia 3) Elevated cardiac biomarkers (troponin/CK), abnormal ECG (ST elevation/ depression, T wave changes) 4) Regional wall motion abnormality on echocardiogram 1) Sharp, stabbing chest pain radiating to back and trapezius ridge; improved with sitting forward 2) Pericardial friction rub (may be ephemeral, more pronounced with sitting forward) 3) Abnormal ECG (diffuse ST elevation, PR depression); elevated inflammatory markers (ESR, CRP) 4) Common: Pericardial effusion on echo or CT 1) Shortness of breath, pleuritic chest pain 2) Tachycardia; tachypnea; normal lung exam, 3. Common: positive D- dimer 4. Xray with minimal abnormalities; CT chest with pulmonary angiogram demonstrates a clot; V/Q scan with unmatched perfusion defect 1) Common: Sudden onset, severe ripping and tearing CP radiating to back

14. Data CollectionProblem Representation (Framing) Access Illness Scripts Potential Match Diagnosis!

15. Illness Script Selection Match the problem formulation to the illness script

16. Data CollectionProblem Representation (Framing) Access Illness Scripts Potential Match Diagnosis!

17. Overview of Clinical Reasoning Overview of making a diagnosis How our brains deal with it What it actually looks like in practice

18. How do doctors think? We’re not really sure, but we do have a general idea A couple of key points: –Experience really matters –Lots of complexity

19. Question 1: Image from Wikimedia Commons

21. Data CollectionProblem Representation (Framing) Access Illness Scripts Potential Match Diagnosis!

22. Question 2:

24. Data CollectionProblem Representation (Framing) Access Illness Scripts Potential Match Diagnosis!

25. Overview of Clinical Reasoning Overview of making a diagnosis How our brains deal with it What it actually looks like in practice

26. How it plays out…. Bedside Clinical Reasoning –Hypothesis generation –Hypotheses refinement –Diagnostic testing –Causal reasoning –Diagnostic verification

27. A Case 69 year-old man with a history of CAD presents with chest pain –Acute coronary syndrome! Unlike prior MI Pain is sharp and stabbing –Less likely ACS, maybe PE? –Pericarditis? No associated dyspnea Radiates through to the back –?Aortic Dissection Hypothesis Generation Hypothesis Refinement and Generation

28. Exam –Differential pulses in upper extremities –Aortic insufficiency murmur CXR –Widened mediastinum CT scan –Aortic dissection Causal Reasoning Diagnostic Testing and Verification Hypothesis Refinement

29. Bedside Clinical Reasoning –Hypothesis generation –Hypotheses refinement –Diagnostic testing –Causal reasoning –Diagnostic verification

30. Agenda Overview of diagnostic reasoning How good are we? How can we (and our learners) improve?

31. Definition of a Diagnostic Error: A diagnosis that, on the basis of the eventual appreciation of more definitive information, was –Unintentionally delayed, or –Wrong, or –Missed altogether

32. Question 3 What is your personal rate of diagnostic error? A)<1% B)2-3% C)5% D)10-15% E)>20%

33. Question 4 What is the overall rate of diagnostic error in medicine? A)<1% B)2-3% C)5% D)10-15% E)>20%

34. Rate of Diagnostic Error Overall, likely rate of diagnostic error is about 10% Error rate varies by specialty and study –Anatomic pathology 2-5% –ED up to 12% –Medical inpatient diagnosis ~6-8%

35. Do these errors matter? Account for up to 17% of adverse events 40,000-80,000 US hospital deaths per year attributable to diagnostic error 5% of all autopsies show a lethal diagnosis that could have been treated ante-mortem Tort claims data (really expensive) JAMA 2002; 288:2405

36. What do these errors look like? DiagnosisMissed on initial evaluation Stroke9% Sub-arachnoid hemorrhage 5% Pulmonary Tb45% Acute Coronary Syndrome 2-3% Appendicitis19%

37. What causes these errors? Three general categories of diagnostic error –“No Fault” (7%) Very unusual presentations, patient-related error –Systems-related (19%) Technical failure, organizational issues –Cognitive errors (28%) Faults in knowledge, data gathering, information processing or metacognition 46%

38. Arch Intern Med 2005;165:1493-1499.

39. Basis of Cognitive Errors Cognitive Errors –Faulty knowledge –Faulty data gathering –Faulty synthesis –Affective error

40. Basis of Cognitive Errors Cognitive Errors –Faulty knowledge –Faulty data gathering Failure to ask or look EMRs –Faulty synthesis –Affective error

41. Red Flag Medicine We often embrace “Red Flag Medicine” –Overly trusting of technology –Doubt the utility of the clinical exam –Lack confidence in clinical skills !

42. Basis of Cognitive Errors Cognitive Errors –Faulty knowledge –Faulty data gathering Failure to ask or look EMRs –Faulty synthesis –Affective error

43. Basis of Cognitive Errors Cognitive Errors –Faulty knowledge –Faulty data gathering Failure to ask or look EMRs –Faulty synthesis/metacognition Premature closure Misjudging the importance of a finding Faulty context generation

44. Question 5: List two things that annoy you about people List three of your favorite people

45. Basis of Cognitive Errors Cognitive Errors –Faulty knowledge –Faulty data gathering –Faulty synthesis –Affective error

46. Agenda Overview of diagnostic reasoning How good are we? How can we (and our learners) improve?

47. Potential Solutions Monitoring and feedback systems Reframe root cause analysis Provide improved clinical decision support Mandate/encourage appropriate use of EMRs Data visualization tools Cognitive awareness and techniques

48. Time Performance Expert Experienced Non Expert Slide from Gurpreet Dhaliwal

49. Making Experts Progressive Problem Solving Feedback Simulation Deliberate Practice

50. Progressive Problem Solving Avoid the routinization of work –Go past where you have to Reformulate problems –Add challenging, nuance and difficulty

51. Diagnostic Feedback Diagnostic Closure Are we really as good as we think we are?

52. Croskerry P. The feedback sanction. Academic Emergency Med 2000.

54. Simulation Practice, practice, practice We can’t see as many patients as we need to We don’t see all the presentations and diseases we need to

55. High-Fidelity Sim

57. Fox MC et al. N Engl J Med 2013;369:966-972

58. Deliberate Practice What do I stink at? Focus on it Work on it repeatedly Assess performance

59. Fox MC et al. N Engl J Med 2013;369:966-972

60. Habits for Good to Great ExperiencedExpert On The Job LearningAs needed Progressive Problem Solving Feedback on my patient outcomesRandomSought out Case ReadingSpectatorSimulator Skill DevelopmentAs it happensDeliberate Practice Dhaliwal G. Clinical Excellence: Make It A Habit. Academic Medicine 2012

61. Action Steps 1.Mindset  Continuous learning/pushing ourselves 2.Feedback  Set up a system 3.Simulation  One case per week 4.What is lacking?  Get deliberate Slide from Gurpreet Dhaliwal

62. Question 6: List the two most important things you learned in the past hour List the two things you wish we had covered but didn’t

63. Agenda Overview of diagnostic reasoning How good are we? How can we (and our learners) improve?

64. Objectives Be able to describe the basic process of making a diagnosis Acknowledge we struggle with making diagnoses List several ways we can improve our diagnostic skills

65. More Information http://www.improvediagnosis.org/?Clinical Reasoning

66. Diagnostic Decision-Making: How do we do it and how can we (and our learners) improve? META Scholars September 5, 2013