CLINICAL REASONING FACULTY OF MEDICINE MALANG ISLAMIC UNIVERSITY

CLINICAL REASONING FACULTY OF MEDICINE MALANG ISLAMIC UNIVERSITY

Clinical Diagnostic Reasoning Knowledge Patient story Data Problem representation Context Hypothesis Illness script Diagnosis Experience

Promote diagnostic reasoning: 1. 2. 3. 4. Experience Articulate problem representation Prioritize and justify diagnostic possibilities Develop illness scripts/disease concepts

Key Elements Of Clinical Diagnostic Reasoning

Data Acquisition Based on knowledge, experience, and other important context Elements: � History, � Findings on physical examination, � Results of laboratory testing and imaging studies

Problem Representation The way to translate a presentation of symptoms and signs into a coherent clinical case Transformation of patient-specific details into abstract (medical) terms, using semantic qualifiers, in onesentence summary Clinicians may have no conscious awareness of this cognitive step The problem representation, unless elicited in the teaching setting, is rarely articulated

Semantic Qualifiers Paired opposing descriptors that can be used to compare and contrast diagnostic considerations Associated with strong clinical reasoning help the doctors sort through differential diagnoses Several implied pairs when considering hypotheses for a diagnosis of gout: � � � multiple (not single), discrete (not continuous) episodes, abrupt (not gradual) onset, severe (not mild) pain, single joint (not multiple joints) Problem representation: acute onset of a recurrent, painful, monoarticular process in an otherwise healthy middle-aged man

Illness Script The way the clinical experience and knowledge stored in memory Storage Strategy of Experts Problem representation trigger clinical memory, permitting the related knowledge (illness script) to become accessible for reasoning

Illness Script: Key To Pattern Recognition Generated by reading and by experience Has a predictable structure: � � � Another structure: � � � predisposing conditions, pathophysiological insult, clinical consequences epidemiology, temporal pattern, syndrome statement Content: those elements which distinguish among like diseases

Illness Script The defining and discriminating clinical features of a disease, condition, or syndrome become "anchor points" in memory Defining features: descriptors that are characteristic of the diagnoses Discriminating features: descriptors that are useful for distinguishing the diagnoses from one another

Illness Script: Gout

Illness Script Syndrome: Right Upper Quadrant Pain Disease Epidemiology Temporal Course Syndrome Description Ascending Cholangitis Cholecystitis Acute Hepatitis B

Illness Script Syndrome: Acute Chest Pain Disease Epidemiology Temporal Course Syndrome Description Angina Pulmonary Embolus Spontaneous Pneumothorax

Defining & Discriminating Features Of A Set Of Diagnostic Hypotheses: Acute Arthritis

Pattern & Probabilities: Hypothetico. Deductive Reasoning The strategy of generating a hypothesis early in the reasoning process, and then seeking out information to prove or disprove their theory before moving on to a different hypothesis if necessary The model of a combined non-analytical strategy (pattern recognition) with a more analytical phase (checking key features of the proposed diagnosis) are effective and used simultaneously, in interactive fashion

Pattern & Probabilities: Hypothetico. Deductive Reasoning Pattern recognition: � essential to diagnostic expertise � this skill is developed through clinical experience Deliberative analytic reasoning is the primary strategy when: a case is complex or ill defined, � the clinical findings are unusual, � the physician has had little clinical experience with the particular disease entity �

Pattern & Probabilities: Hypothetico. Deductive Reasoning The difference between novices and experts: � the speed & accuracy of the hypotheses made, � the method and efficiency of weighing up evidence for and against the hypothesis Some of this speed lies in the ability to recognise patterns Some areas of medicine rely heavily on pattern recognition