title: Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.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.
  
  
  RESULTS
  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.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%).
  
  
  CONCLUSIONS
  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.
authors.affiliation: Division of Pharmacoepidemiology & Pharmacotherapy, Utrecht Institute for Pharmaceutical Sciences, Utrecht, The Netherlands. t.t.menckeberg@uu.nl <t.t.menckeberg@uu.nl>
authors.forename: Tanja T
authors.initials: TT
authors.lastname: Menckeberg
authors.forename: Svetlana V
authors.initials: SV
authors.lastname: Belitser
authors.forename: Marcel L
authors.initials: ML
authors.lastname: Bouvy
authors.forename: Madelon
authors.initials: M
authors.lastname: Bracke
authors.forename: Jan-Willem J
authors.initials: JW
authors.lastname: Lammers
authors.forename: Jan A M
authors.initials: JA
authors.lastname: Raaijmakers
authors.forename: Hubert G M
authors.initials: HG
authors.lastname: Leufkens
mesh_terms: D002908:Chronic Disease / Q000188:drug therapy*; D003266:Continuity of Patient Care / Q000706:statistics & numerical data*; D006801:Humans; D008390:Markov Chains; D009426:Netherlands; D010349:Patient Compliance / Q000706:statistics & numerical data*; D011336:Probability; D012646:Self Administration / Q000706:statistics & numerical data*