Evidence based diagnosis: does the language reflect the theory?
BMJ 2006; 333 doi: https://doi.org/10.1136/bmj.38915.558738.55 (Published 24 August 2006) Cite this as: BMJ 2006;333:442- Matt T Bianchi (mtbianchi@partners.org), resident1,
- Brian M Alexander, resident2
- 1 Partners Neurology, Massachusetts General Hospital and Brigham and Women's Hospital, Boston, MA 02114,
- 2 Partners Radiation-Oncology, Massachusetts General Hospital and Brigham and Women's Hospital
- Correspondence to: M Bianchi
- Accepted 17 June 2006
Although interest in evidence based medicine has increased in recent years, and it is taught in most medical schools, evidence based strategies have been adopted inconsistently into routine care.1 2 One aspect of evidence based medicine involves understanding the limitations of inherently imperfect diagnostic tests. Many trainees appreciate the concepts of sensitivity and specificity and learn how to combine the “art” of the history and physical exam (pre-test probability of disease) with the “science” of diagnostic testing (post-test probability of disease) without explicit use of quantitative probability theory. Nevertheless, it seems that quantitative reasoning is neither intuitive nor well understood. As diagnostic testing is a common and critical component of evaluating patients, it is worth considering whether the manner in which we verbally communicate these ideas may represent a fundamental (yet reparable) hindrance to diagnostic reasoning. We discuss common examples of diagnostic language that do not accurately reflect the underlying theory, and review the evidence for inadequate clinical application of bayesian strategies.
Innocent generalisations?
As trainees, we can all recall hearing pearls of wisdom conveyed in the form of: “Any patient presenting with this sign/symptom is assumed to have disease X until proved otherwise.” The common mnemonic “SPin/SNout” is used to indicate that positive results from specific tests rule in disease, while negative results from sensitive tests rule out disease. One may hear sensitivity or specificity discussed in isolation (“that test is so sensitive that a negative result rules out disease”) or, more commonly, of a test having good positive or negative predictive value. Certain findings are called “non-specific” because they manifest in multiple diseases. Although this language seems to …
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