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This library has more use cases than just measuring adherence and visualizing prescribing records. Any data containing time-series could benefit from these types of analyses
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I agree that some types of timeseries can benefit from some of these plots and estimates, but (and this is a big but) these were designed with adherence in mind (in particular, what espisodes are and what the cmas are and how they're computed)
do you have something particular in mind?
and thanks a lot for the message :) it is not often that people using it also let know...
Don't have anything concrete yet. It's been several years since I used this library. Back then I used it in my thesis to try and discover adherence patterns from EHD prescribing and dispending records. I would like to use it now on something completely different, namely for time-series order picking dataset I have. The plots produced by adhereR are very suitable for this as they nicely show the lengths of each pick and in addition show gaps between picks. CMA and non-persistence could still be used as surrogate measures for the picker's performance.
Interesting, I never really considered such applications :) please let us know if it works or if you have idea/suggestions or if you find bugs...
best,
Dan
This library has more use cases than just measuring adherence and visualizing prescribing records. Any data containing time-series could benefit from these types of analyses
The text was updated successfully, but these errors were encountered: