Diagnostic Decision-Making: How do we do it and how can we

(and our learners) improve?

META Scholars

September 5, 2013

Agenda

• Overview of diagnostic reasoning

• How good are we?

• How can we (and our learners) improve?

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

Overview of Clinical Reasoning

• Overview of making a diagnosis

• How our brains deal with it

• What it actually looks like in practice

How do Doctors Think?

Data Collection Problem Representation

(Framing)

Access Illness Scripts

Potential Match

Diagnosis!

Data collection

• History

• Physical examination

• Laboratory studies

• Imaging studies

Data Collection Problem Representation

(Framing)

Access Illness Scripts

Potential Match

Diagnosis!

Problem Representation

• Making sense of the data obtained

• Identification of the key elements

• Categorization

• Semantic qualifiers

• Frame things (context is everything)

Data Collection Problem Representation

(Framing)

Access Illness Scripts

Potential Match

Diagnosis!

Illness Scripts

• Mental representations of the key elements of specific diagnoses– History– Physical– Labs– Imaging– Response to therapy

Acute Coronary Syndrome

Pericarditis Pulmonary embolism Aortic 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) Tachycardia3) 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 pain2) Tachycardia; tachypnea; normal lung exam, 3. Common: positive D-dimer4. 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

Data Collection Problem Representation

(Framing)

Access Illness Scripts

Potential Match

Diagnosis!

Illness Script Selection

• Match the problem formulation to the illness script

Data Collection Problem Representation

(Framing)

Access Illness Scripts

Potential Match

Diagnosis!

Overview of Clinical Reasoning

• Overview of making a diagnosis

• How our brains deal with it

• What it actually looks like in practice

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

Question 1:

Image from Wikimedia Commons

Data Collection Problem Representation

(Framing)

Access Illness Scripts

Potential Match

Diagnosis!

Question 2:

Data Collection Problem Representation

(Framing)

Access Illness Scripts

Potential Match

Diagnosis!

Overview of Clinical Reasoning

• Overview of making a diagnosis

• How our brains deal with it

• What it actually looks like in practice

How it plays out….

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

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

• Exam – Differential pulses in

upper extremities– Aortic insufficiency murmur

• CXR– Widened mediastinum

• CT scan– Aortic dissection

Causal Reasoning

Diagnostic Testing and Verification

Hypothesis Refinement

• Bedside Clinical Reasoning– Hypothesis generation– Hypotheses refinement

– Diagnostic testing– Causal reasoning

– Diagnostic verification

Agenda

• Overview of diagnostic reasoning

• How good are we?

• How can we (and our learners) improve?

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

Question 3

What is your personal rate of diagnostic error?

A) <1%

B) 2-3%

C) 5%

D) 10-15%

E) >20%

Question 4

What is the overall rate of diagnostic error in

medicine?

A) <1%

B) 2-3%

C) 5%

D) 10-15%

E) >20%

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%

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

What do these errors look like?

Diagnosis Missed on initial evaluation

Stroke 9%

Sub-arachnoid hemorrhage

5%

Pulmonary Tb 45%

Acute Coronary Syndrome

2-3%

Appendicitis 19%

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%

Arch Intern Med 2005;165:1493-1499.

Basis of Cognitive Errors

• Cognitive Errors– Faulty knowledge – Faulty data gathering – Faulty synthesis– Affective error

Basis of Cognitive Errors

• Cognitive Errors– Faulty knowledge – Faulty data gathering

• Failure to ask or look• EMRs

– Faulty synthesis– Affective error

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

!

Basis of Cognitive Errors

• Cognitive Errors– Faulty knowledge – Faulty data gathering

• Failure to ask or look• EMRs

– Faulty synthesis– Affective error

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

Question 5:

• List two things that annoy you about people

• List three of your favorite people

Basis of Cognitive Errors

• Cognitive Errors– Faulty knowledge – Faulty data gathering– Faulty synthesis– Affective error

Agenda

• Overview of diagnostic reasoning

• How good are we?

• How can we (and our learners) improve?

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

Time

Performance

Expert

Experienced Non Expert

Slide from Gurpreet Dhaliwal

Making Experts

• Progressive Problem Solving

• Feedback

• Simulation

• Deliberate Practice

Progressive Problem Solving

• Avoid the routinization of work– Go past where you have to

• Reformulate problems– Add challenging, nuance and difficulty

Diagnostic Feedback

• Diagnostic Closure

• Are we really as good as we think we are?

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

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

High-Fidelity Sim

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

Deliberate Practice

• What do I stink at?

• Focus on it

• Work on it repeatedly

• Assess performance

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

Habits for Good to Great

Experienced Expert

On The Job Learning As neededProgressive Problem

Solving

Feedback on my patient outcomes

Random Sought out

Case Reading Spectator Simulator

Skill Development As it happens Deliberate Practice

Dhaliwal G. Clinical Excellence: Make It A Habit. Academic Medicine 2012

Action Steps1. 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

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

Agenda

• Overview of diagnostic reasoning

• How good are we?

• How can we (and our learners) improve?

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

More Information

http://www.improvediagnosis.org/?ClinicalReasoning

Diagnostic Decision-Making: How do we do it and how can we

(and our learners) improve?

META Scholars

September 5, 2013