BMJ: "Evidence based medicine on trial"

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Carl Heneghan: 

Evidence based medicine on trial

4 Dec, 14 | by BMJ Evidence based medicine (EBM) should form the foundation of effective clinical decision making; however, growing unrest—and an awful lot of criticism—suggests the evidence bit of EBM is increasingly part of the problem, and not the solution.

“Carl Heneghan jointly runs the Evidence Live conference with The BMJ and is a founder of the AllTrials campaign.” 

I am linking to this article because of the Twitter discussion on #understandingpsychosis – and other situations where the word “evidence” sometimes seems to trigger System 1 reactions that block off relevant information. 


Quote: 

Distortion of the research agenda, mainly by commercial decisions, is leading to an ever increasing evidence base that doesn’t meet the needs of patients. With too much focus on the well, and not enough on the sick, the paradoxical situation has arisen whereby medicine is potentially harming the healthy through earlier detection and increasingly looser definitions of disease.

As an example, if you find yourself constantly late, disorganised, forgetful, and overwhelmed by your responsibilities—which could refer to all of us—you might have adult attention-deficit disorder. You will be pleased to know that there are at least four different medications currently available for this condition. You could argue that the pharmaceutical industry is becoming equally good, if not better, at manufacturing diseases as opposed to drugs.

While research publications continue to increase—to the point where the notion of keeping up to date is nigh on impossible—the quality is often very poor, if not sometimes outright pitiful. Although there has been a growth in research to promote implementation, my observations—note the low level of my evidence —have been that while clinicians are extremely good at responding to robust evidence, all too often the quality of the evidence is weak and unworthy of implementation.

Poor quality evidence arises when observational data are used to establish treatment effects; when outcome measures are unimportant to patients or, even worse, are meaningless for patient care; and also when simple factors to account for bias are not incorporated into the research design.

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