Before a diagnosis is accepted it should be tested to determine if it is valid. This can help prevent errors in diagnosis or inefficiency in resource utilization.
Tests for a diagnosis:
(1) adequacy
(2) coherence
(3) primacy
(4) parsimony
(5) robustness
(6) prediction
where:
• Parsimony ideally has 1 diagnosis explaining all of the patient's findings. This may fail in the older patient with multiple comorbid conditions or in a patient with a complex clinical course.
• Prediction can take the form of hypothesis matching (if this disease were present, then the patient would show these findings.)
Does the diagnosis?
Test
adequately explain all of the patient's clinical findings? If not, does it explain all of the patient's key findings?
adequacy
fit the patient's pathophysiologic state?
coherence
provide the best fit to explain the patient's illness?
primacy
provide the simplest explanation for the patient's findings?
parsimony
withstand attempts to disprove it? (devil's advocate)
robustness
best predict the clinical course of the patient's illness?
prediction
Is there another diagnosis that can?
Test
fit the patient's pathophysiologic state better?
coherence
explain the patient's illness better?
primacy
provide a simpler explanation?
parsimony
disprove or discount this diagnosis?
robustness
better predict the patient's clinical course?
prediction
To read more or access our algorithms and calculators, please log in or register.
