These authors tackle in depth the question "how do we evaluate the effectiveness of treatment"?
Their bullet points are below:
➤ Clinically important outcome values allow physicians to provide patients with more realistic expectations regarding their treatment that are based on their specific demographics.
➤ Clinically important outcome values can vary for the same procedure or population depending on the method of calculation used, which raises the need for uniform ways to calculate and compare these values across populations and procedures.
➤ A shift in approach from focusing solely on significant outcomes, or p values, to considering both clinically important and significant outcomes will allow clinicians to provide more efficient care, in line with recent trends toward a value-based health-care system.
➤ Clinically important outcome values allow physicians to provide patients with more realistic expectations regarding their treatment that are based on their specific demographics.
➤ Clinically important outcome values can vary for the same procedure or population depending on the method of calculation used, which raises the need for uniform ways to calculate and compare these values across populations and procedures.
➤ A shift in approach from focusing solely on significant outcomes, or p values, to considering both clinically important and significant outcomes will allow clinicians to provide more efficient care, in line with recent trends toward a value-based health-care system.
Comment: It is important to recognize that a study can show that one treatment is statistically significantly better than another without it being clinically significantly better. Consider a hypothetical study of a traditional treatment (A) and a novel treatment (B) with 25 patients each evaluated by the Simple Shoulder Test (SST). The increased benefit (difference between the pre and the post op SST) for the new treatment B is significantly better than the traditional treatment (p=0.003).
This article points out that there are many different ways for measuring the clinical benefit and, furthermore, that the value of a measure such as the MCID may be different for different treatments or different populations of patients.
Another issue relates to studies showing significant "geometric" improvement with respect to the positioning of arthroplasty components, without evidence that there is associated clinical improvement.
Another issue relates to studies showing significant "geometric" improvement with respect to the positioning of arthroplasty components, without evidence that there is associated clinical improvement.
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