Diagnosis is a process that involves collecting data about one’s illness (collate their symptoms) and determine their anatomic, physiologic and/or psychosocial derangement (usually called disease) in order to direct a clinician toward offering specific treatments.
There are four methods of diagnosis:
- Gestalt/Pattern recognition method: involves immediate recognition of a patient’s presentation based on a clinician’s past experience in identifying a similar pattern of disease.
- Exhaustive evaluation method: involves collecting all medical facts about a patient by completing a detailed subjective, physical and clinical examination to come to a final diagnosis.
- Algorithm method: involves asking a relevant but broad question and follow up the individual through pre-determined logical/evidence-based steps in order to reach a final diagnosis.
- Hypothetico-deductive method: involves formulating multiple hypotheses (a list of probable diagnoses), followed by performing relevant clinical tests to arrive at a final diagnosis.
There are multiple ways to apply the hypothetico-deductive method of diagnosis. Here, I have explained a ‘symptom guided – probability driven’ model to apply this diagnostic method.
Stage I: The symptoms reported by patients are collated to form a single hypothesis. Also, a single symptom can bring forth multiple hypotheses. Any relevant clinical data is utilised in this stage to support making a hypothesis.
Stage II: The list of hypotheses (potential diagnoses) are ranked based on success probability. A potential diagnosis that has the highest probability of becoming true/success is ranked as first. Such prioritisation is best done by considering the strength of association between the symptoms/relevant clinical data and the hypotheses.
Stage III: Conduct a focused subjective and objective examination to rule out the diagnoses that are less likely to be true. At this stage, you will arrive at a diagnosis by working your way up (by ruling out) the list of hypotheses generated.
Stage IV: Finally, perform a highly sensitive (most accurate) diagnostic test to confirm a diagnosis.
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