Decision tree logic |
Classic decision analysis combines "probability" and "utility" to mathematically compare multiple care options that lead to hard outcomes such as death, disability or cure (an example is here). Unfortunately, say the authors, this imposes numbers on a narrow set of possibilities that fail to account for the full range of outcomes. For example, the recent controversial and arguably nihilistic breast and prostate cancer screening recommendations were informed by decision analysis. While that methodology may have its place, "More to Life" argues that this sterile approach fails to account for the full range of physical and psychological burdens that can result from delayed diagnosis and inappropriate treatment.
While decision analysis attempts to make up for its shortcomings with additional analytics, Drs. Hartzband and Groopman argue that much of the underlying premise is fundamentally flawed by its failure to capture highly individual interpretations of what it means to be sick and how that can vary over time. Distilling this down to a limited set of uni-dimensional outcomes centered on death, disability or cure ignores the "vital dimensions of life that are not easily quantified."
Yikes.
It's it own defence, the DMCB's fondness for decision analysis has been based on its insights, not on its answers. In other words, it's a tool can open one window on the truth. What Drs Hartzband and Groopman charge, however, is that the science of clinical guidelines is being hijacked by an over reliance on decision analysis by out-of-touch experts. That's a serious charge that will complicate the national effort to disseminate scientific guidelines into every nook and cranny of medical practice.
Which leads the DMCB back to another fond topic that ultimately trumps all others: the need for an informed and engaged patient to process clinical guideline recommendations, the advice of a physician, the opinions of friends and family and their own personal values to ultimately make the decision for themselves about testing and treatment.
Decision analysis alone is not up to the task.
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