Clinical Reasoning Framework

Clinical Reasoning Framework

Introduction

Clinical reasoning is the cognitive process by which a clinician gathers information, integrates it with prior knowledge, and arrives at a diagnosis and management plan. It is the intellectual core of medical practice, yet it is often taught implicitly rather than explicitly. Understanding the cognitive science of diagnostic reasoning — including its strengths, vulnerabilities, and systematic approaches — is essential for becoming a safe, effective clinician and for lifelong professional growth.

---

Illness Script Theory

An illness script is a cognitive knowledge structure that summarises the essential features of a clinical entity in a way that facilitates rapid recognition and comparison. First described by Feltovich and Barrows (1984) and later developed by Schmidt, Norman, and Boshuizen.

Three-component structure of an illness script:

1. Enabling conditions (predisposing factors / epidemiology):

Who gets this condition? Risk factors, demographics, precipitants.

Example for STEMI: older age, male sex, smoking, hypertension, diabetes, hyperlipidaemia, family history, prior atherosclerosis, cocaine use (vasospasm in young patients)

1. Pathophysiological fault:

The core mechanism — what has gone wrong at the biological level.

Example for STEMI: atherosclerotic plaque rupture → platelet aggregation and thrombus formation → complete occlusion of epicardial coronary artery → cessation of myocardial blood flow → transmural ischaemia and necrosis (time-dependent)

1. Signs and symptoms / consequences:

What the patient experiences and what the clinician finds.

Example for STEMI: central crushing chest pain ± radiation to jaw/arm, diaphoresis, nausea, dyspnoea, pallor; signs: ECG (ST elevation), raised troponin, haemodynamic compromise; complications: VF, LV dysfunction, cardiogenic shock, papillary muscle rupture

Why illness scripts matter:

• Experts activate illness scripts automatically and rapidly (pattern recognition)
• Novices use analytical reasoning (slower, more effortful, explicit)
• The illness script framework helps learners organise new clinical knowledge, build richer semantic networks, and make faster and more accurate diagnoses
• When presenting/discussing a case, using the illness script structure communicates diagnostic thinking clearly

Illness scripts vs disease concepts:

Disease concepts are abstract (e.g., "STEMI = complete coronary occlusion"). Illness scripts are patient-oriented (enabling conditions → fault → consequences) and include the clinical context. Scripts are refined and updated each time a patient is seen — hence the importance of clinical experience.

---

Diagnostic Reasoning Approaches

Hypothetico-deductive reasoning (System 2 / analytical):

• The clinician generates hypotheses early in the encounter (from the first few cues — chief complaint, demographics, referral letter) and then seeks evidence to confirm or refute them
• Bayesian in nature: prior probability (prevalence) × likelihood ratio of finding = posterior probability (revised probability of diagnosis)
• Systematic, effortful, slower
• Important when presentation is atypical, multiple competing diagnoses, or high stakes
• Errors: confirmation bias (seeking confirming evidence while ignoring disconfirming evidence); testing inefficiency (ordering every test rather than selective high-yield tests)

Pattern recognition (System 1 / intuitive):

• Rapid, non-analytic; the clinician immediately recognises the diagnosis from a gestalt pattern (the overall clinical picture instantly matches a stored illness script)
• Experienced clinicians use pattern recognition most of the time
• Fast and usually accurate for typical presentations
• Errors: pattern recognition applied when the situation is actually atypical → misdiagnosis; the clinician "sees what they expect to see"

Dual-process theory (Kahneman — System 1 and System 2):

• System 1: fast, automatic, unconscious, effortless; uses heuristics and pattern matching; frugal with cognitive resources; prone to predictable biases
• System 2: slow, deliberate, conscious, effortful; logical and analytical; can override System 1; but is lazy (takes effort) — tends to be invoked only when System 1 fails or when the problem is recognised as difficult
• Safe clinical reasoning requires: appropriate use of System 1 for typical presentations + deliberate engagement of System 2 for atypical presentations, diagnostic uncertainty, or high-risk scenarios
• Metacognition: Thinking about one's own thinking; the ability to slow down, recognise when System 1 may be leading astray, and engage System 2. A critical safety skill.

---

Cognitive Biases in Clinical Reasoning

Cognitive biases are systematic errors in thinking that deviate from rationality. In medicine, they contribute to diagnostic error (second most common cause of adverse events after medication error).

Anchoring bias:

• Definition: over-reliance on the first piece of information encountered (the "anchor"); subsequent information is interpreted relative to this anchor rather than objectively
• Example: a patient presenting with chest pain is diagnosed with "musculoskeletal pain" based on initial history of recent gym activity. Subsequent troponin results are explained away as "probably a false positive" even when clearly elevated. The initial anchor (MSK pain) distorts interpretation of all subsequent information.
• Mitigation: deliberately generate differential diagnoses at the outset; be willing to revise when new information contradicts the anchor

Premature closure:

• Definition: accepting the first satisfactory explanation and stopping diagnostic workup before adequate data has been gathered; "if you think you have the answer, you stop looking"
• Example: a patient with chest pain and an ECG showing RBBB is diagnosed with "known RBBB" and discharged. The new RBBB (Sgarbossa criteria) was not recognised as a potential STEMI equivalent.
• The most common cognitive error in emergency medicine
• Mitigation: deliberately ask "what else could this be?"; always explain ALL of the patient's findings; ensure each abnormal finding is accounted for

Availability bias:

• Definition: overestimating the probability of conditions that are more easily brought to mind (e.g., because they are vivid, recent, or emotionally salient)
• Example: after a case conference presentation about bilateral pulmonary emboli, a clinician over-diagnoses PE in subsequent patients with dyspnoea. Alternatively, after not seeing a case of aortic dissection for years, a clinician rarely considers it.
• Mitigation: use prevalence (prior probability) and formal probabilistic reasoning; use clinical decision rules (Wells score for DVT/PE, HEART score for ACS)

Framing effect:

• Definition: the way information is presented influences the diagnostic process; a framing that emphasises one diagnosis makes it harder to consider alternatives
• Example: a referral letter saying "65-year-old anxious woman with palpitations — likely panic disorder" biases the receiving clinician against considering AF or SVT even when clinically present
• Mitigation: generate your own history from the patient before reading referrals; identify and consciously counteract the framing; use structured assessment tools

---

Presenting a Case: SBAR Framework

Effective clinical communication is a patient safety issue. The SBAR (Situation-Background-Assessment-Recommendation) framework was adapted from military/aviation use into healthcare to provide a structured, predictable format for clinical handover and escalation.

S — Situation:

• Who is the patient? What is happening right now?
• "I am calling about Mr. John Smith, 62M in bed 4, who has developed acute onset central chest pain over the last 30 minutes, with associated diaphoresis."

B — Background:

• Relevant medical history, medications, allergies, context
• "He has a background of hypertension and type 2 diabetes. He is allergic to penicillin. He was admitted yesterday for cellulitis and is currently on IV flucloxacillin."

A — Assessment:

• Your clinical assessment — what do you think is happening?
• "His ECG shows 2 mm ST elevation in V2-V4. I am concerned this is an anterior STEMI."

R — Recommendation:

• What do you need / what should happen?
• "I would like you to review him urgently and I recommend we activate the cath lab and start the STEMI protocol."

---

Problem Representation and the One-Liner

Problem representation is a concise summary of the key features of a case that encapsulates the diagnostic problem at a given moment. It serves as a pivot statement that focuses the diagnostic workup.

Structure: [Age] [sex] [relevant predisposing conditions] with [key symptoms and signs] in the context of [temporal/situational modifiers].

Example: "A 68-year-old woman with hypertension, diabetes, and hyperlipidaemia presenting with 90 minutes of central chest pain radiating to the jaw and diaphoresis, with inferiorly-distributed ST elevation on ECG."

This one-liner efficiently communicates: the patient's risk profile (enabling conditions), the time course, the key clinical features, and the critical ECG finding — everything needed to activate an appropriate response.

Evolution of problem representation during the encounter:

• At initial presentation: based on chief complaint + demographics
• After history: enriched with temporal features, risk factors, associated symptoms
• After examination: integrates physical signs
• After investigations: becomes increasingly diagnostic-specific

Semantic qualifiers: Words that enrich the problem representation by characterising the features precisely — "sudden onset" vs "gradual"; "pleuritic" vs "pressing"; "exertional" vs "rest"; "central" vs "pleuritic/positional" chest pain. These qualifiers activate different illness scripts and guide the differential diagnosis.