Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence

<p>Abstract</p> <p>Background</p> <p>In order to accurately distinguish gaps of varying length in drug treatment for chronic conditions from discontinuation without resuming therapy, short-term observation does not suffice. Thus, the use of inhalation corticosteroids (ICS) in the long-term, during a ten-year period is investigated. To describe medication use as a continuum, taking into account the timeliness and consistency of refilling, a Markov model is proposed.</p> <p>Methods</p> <p>Patients, that filled at least one prescription in 1993, were selected from the PHARMO medical record linkage system (RLS) containing >95% prescription dispensings per patient originating from community pharmacy records of 6 medium-sized cities in the Netherlands.</p> <p>The probabilities of continuous use, the refilling of at least one ICS prescription in each year of follow-up, and medication free periods were assessed by Markov analysis. Stratified analysis according to new use was performed.</p> <p>Results</p> <p>The transition probabilities of the refilling of at least one ICS prescription in the subsequent year of follow-up, were assessed for each year of follow-up and for the total study period.</p> <p>The change of transition probabilities in time was evaluated, e.g. the probability of continuing ICS use of starters in the first two years (51%) of follow-up increased to more than 70% in the following years. The probabilities of different patterns of medication use were assessed: continuous use (7.7%), cumulative medication gaps (1–8 years 69.1%) and discontinuing (23.2%) during ten-year follow-up for new users. New users had lower probability of continuous use (7.7%) and more variability in ICS refill patterns than previous users (56%).</p> <p>Conclusion</p> <p>In addition to well-established methods in epidemiology to ascertain compliance and persistence, a Markov model could be useful to further specify the variety of possible patterns of medication use within the continuum of adherence. This Markov model describes variation in behaviour and patterns of ICS use and could also be useful to investigate continuous use of other drugs applied in chronic diseases.</p

The probability of gaps, medication free periods of several lengths, in the total population and stratified for new and previous use

<p><b>Copyright information:</b></p><p>Taken from "Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence"</p><p>http://www.biomedcentral.com/1472-6963/7/106</p><p>BMC Health Services Research 2007;7():106-106.</p><p>Published online 10 Jul 2007</p><p>PMCID:PMC1959200.</p><p></p

3a For new users, the probabilities of continuous use, gaps and discontinuation in the period that has elapsed until a particular year of follow-up

<p><b>Copyright information:</b></p><p>Taken from "Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence"</p><p>http://www.biomedcentral.com/1472-6963/7/106</p><p>BMC Health Services Research 2007;7():106-106.</p><p>Published online 10 Jul 2007</p><p>PMCID:PMC1959200.</p><p></p> 3b For new users, for each year of follow-up the proportion of patients with irregular ICS use (medication free periods) and continued ICS use in the period of follow-up that has elapsed until then are shown

Transition probabilities from one particular state, 1993, to all other possible states for new users are shown

<p><b>Copyright information:</b></p><p>Taken from "Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence"</p><p>http://www.biomedcentral.com/1472-6963/7/106</p><p>BMC Health Services Research 2007;7():106-106.</p><p>Published online 10 Jul 2007</p><p>PMCID:PMC1959200.</p><p></p> The transition probability of filling at least one ICS prescription in 1994, given filling at least one prescription in 1993, P, is 51%. One of the possible transitions is