Posts Tagged Persistency

Persistency Is The Best Measure of Medication Adherence

In an earlier post, I discussed that while medication possession ratios (MPRs) tend to dominate the marketplace reporting tools for medication adherence programs, MPR is not, in fact, the best measure of medication adherence.  Reason being, the results of an MPR analysis depend heavily upon the methodological choices made in defining MPR and the quality of the days supply figured provided by the pharmacist.  Mostly importantly, MPRs allow for little to no clinical interpretation. 

Of all the measurement options that exist, I find persistency to be the most useful.  Persistency, which is a dichotomous yes/no measure that is based on the length of therapy, tells whether a patient’s length of therapy meets or exceeds a certain threshold.  For example, it is common for published studies to report the percent of newly treated patients who were persistent with their medication one year after starting therapy.  There are two key reasons why I prefer persistency over other adherence measures:

1.  It measures the most significant medication adherence problem, i.e., whether patients stop taking their medication altogether.  While small gaps in therapy are not desirable, they are far less prevalent or clinically impactful than discontinuing treatment altogether.  Studies have shown that between 40 and 60% of newly treated patients stop taking their chronic medications after one year.  The figure below, from a BMJ study of antihypertensive users, reports both persistency over time and non-adherence due to poor execution of the dosing regimen.  As the authors state, “non-execution of the dosing regimen created a shortfall in drug intake that is an order of magnitude smaller than the shortfall created by early discontinuation/short persistence.”  Discontinuation has to be the top priority, and organizations will manage what they measure–so measure persistency.

 

 2. The clinical interpretation is unequivocal.  As I discussed in the previous post, improvements in MPR are very difficult to interpret in terms of their clinical impact due to the lack of data on the relationship between differences in MPR or gaps and clinical outcomes.  However, when a patient discontinues their chronic medication altogether, the clinical impact is far clearer (as long as the patient was an appropriate candidate for the medication to begin with—a topic for another day).  The negative clinical and economic impact of discontinuation can be forecasted for a population based on published randomized trials.

Another advantage of a persistency measure is that it is less susceptible to errors in days supply figures provided by the pharmacist because the analysis typically provides a 30 or more day gap in therapy before labeling someone as non-persistent.  That said, persistency is still vulnerable, albeit less than MPR, to differences in methodological approaches.  The two key decisions in a persistency analysis are 1) how long to follow patients;  and 2) what gap in therapy will be considered non-persistence (e.g., 30-day, 60-day, or 90-day gap).  Obviously, the longer you follow patients, the lower the persistency rate will be and the larger the gap in therapy required to be labeled non-persistent, the higher the persistency rate will be.  Accordingly, if comparing vendors, make sure you have the same follow-up length and gap criteria.  In addition, persistency rates for new versus ongoing users look dramatically different so you should always ask that the two groups be reported separately to prevent changes in the mix of members from artificially influencing your results.

Perhaps the biggest reason persistency is not reported as frequently as MPR is because it requires member-level analysis over time, controlling for eligibility.  This involves more complex analytics and processing time for large groups of patients, but given the reasons I’ve outlined above, it is worth the effort.

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