Continuing medical education professionals assigned the task of working with outcomes data seek ways to describe significant patterns in informative and narrative formats. Numbers and units combine to yield accurate measurements. But what is the difference between accuracy and precision?
How many participants answered this question? How many answered the question correctly pre- and post-activity? These are all examples of accuracy. Basically, are my results aligned with the truth? It becomes problematic when we make leaps of faith. If we claim, accuracy is precision necessarily implied? Did participants clearly learn something they didn't know before participating in your learning intervention?
Sounds pretty straightforward but what if we aren't using the right tool or aren't using the tool properly?
When you measure, you must interpret the measurement against the standard established by the tool. In the process, you put a little bit of yourself into the measurement and, for this reason, the tool you use to measure has a big impact on the result you get. The existence of a measurement, not surprisingly, means that someone actually measured it. There is a natural limit to how well I can measure objects depending on how well I can ‘see’ it as well as how good of a tool I am using to see it.—Matt Anticole
I don't work in CME often--just for a few clients. But as I navigate different stakeholder journeys in medical affairs, e-learning, health economics, medical journalism, and health policy I continue to share insights.
It is up to you to figure out what it means for your business model but the healthcare ecosytem is evolving and will include patients, treatment algortihms meant for the macropopulations--but what will that mean for the n of 1 patient? Its worth making a plan.
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