Guyatt and Djulbegovic provide an important conclusion of guidelines and individual clinical practice.
The recognition that values and preferences vary widely among individuals has an important implication: the standardisation of care, which was one of the original reasons for the introduction of guidelines, and is still considered a key rationale for assessing the quality of care initiatives, is neither possible nor desirable for the many value and preference-sensitive decisions that clinicians and patients face.
Tonelli in a 2012 article says the following about guidelines and clinical practice:
Guideline development versus clinical practice
Prior to a more thorough elucidation of the factors beyond study design that make clinical research results more or less compelling, it is crucial to be clear about the task at hand. As noted above, clinical practice guideline developers have acknowledged that they ought to consider factors beyond study design in their deliberations, meaning the strength of a guideline recommendation will not necessarily follow from the strength of the study design alone[4]. The development of clinical practice guidelines, however, is a fundamentally different task than making a clinical decision regarding a particular patient. For the former, one must continue to focus on groups and subgroups that can be distinguished by reference to a few specific characteristics. Hence, features that are patient specific and variable, such as the personal value attached to a specific outcome, cannot be easily incorporated into guidelines. Similarly, features that rest with individual clinicians, such as the sense of prior probability regarding a study outcome, cannot be fully accounted for by guideline committees, many of whom will be methodologists rather than clinicians[6]. Finally, some features, such as ease of implementation, will vary between locations and systems in which care is delivered, again limiting the ability of clinical practice guidelines to incorporate such factors. The practice of clinical medicine, delivering care to individual patients, will remain more complex and challenging than the development of clinical practice guidelines. Clinicians must deal with more features relevant to the compellingness of clinical research and, to make matters even more complicated, may find specific clinical research compelling in the care of a particular patient, but much less compelling in a similar patient who differs in some meaningful way from the first. The value of knowledge gained from a particular example of clinical research is not fixed for the clinician, but rather must be considered and carefully weighed when serving as a warrant for a particular clinical decision[7].
Weisberg in his book Willful ignorance: the mismeasure of uncertainty talks about how clinicians and researchers inhabit different worlds.
Research focuses on what is likely to happen “on the average” in certain specified circumstances. What, for example, is the effect on the mortality rate for middle-aged men who adopt a low-dose aspirin regimen? However, the clinician's concern is her particular patient. What will happen to Sam Smith if he starts on an aspirin regimen tomorrow? So, she may balk at mechanically following some general guidelines that are alleged to be statistically optimal...
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In a real sense, clinicians and researchers tend to inhabit different conceptual worlds. The clinician is sensitive to the ambiguities of the “gray zone” in which difficult decisions must be made. She is in a land where the uncertainty is mainly of the “what is really going on here?” kind. For the researcher, on the other hand, the world must look black and white, so that the rules of probability math can be applied. This ambiguity blindness has become absolutely necessary. Without it, as we will see, the elaborate machinery of statistical methodology would come to a grinding halt. Consequently, there is no middle road between the clinical and statistical perspectives.
Clinicians and researchers face different kinds of uncertainties, probabilities, and decision making processes, but learning both is essential in understanding how science works.
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1. You should attempt to re-express your target’s position so clearly, vividly, and fairly that your target says, “Thanks, I wish I’d thought of putting it that way.
2. You should list any points of agreement (especially if they are not matters of general or widespread agreement).
3. You should mention anything you have learned from your target.
4. Only then are you permitted to say so much as a word of rebuttal or criticism.
Daniel Dennett, Intuition pumps and other tools for thinking.
Valid criticism is doing you a favor. - Carl Sagan