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

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 inves...

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Autores principales: Menckeberg, Tanja T, Belitser, Svetlana V, Bouvy, Marcel L, Bracke, Madelon, Lammers, Jan-Willem J, Raaijmakers, Jan AM, Leufkens, Hubert GM
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1959200/
https://www.ncbi.nlm.nih.gov/pubmed/17620145
http://dx.doi.org/10.1186/1472-6963-7-106
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author Menckeberg, Tanja T
Belitser, Svetlana V
Bouvy, Marcel L
Bracke, Madelon
Lammers, Jan-Willem J
Raaijmakers, Jan AM
Leufkens, Hubert GM
author_facet Menckeberg, Tanja T
Belitser, Svetlana V
Bouvy, Marcel L
Bracke, Madelon
Lammers, Jan-Willem J
Raaijmakers, Jan AM
Leufkens, Hubert GM
author_sort Menckeberg, Tanja T
collection PubMed
description 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%). CONCLUSION: 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.
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spelling pubmed-19592002007-08-30 Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence Menckeberg, Tanja T Belitser, Svetlana V Bouvy, Marcel L Bracke, Madelon Lammers, Jan-Willem J Raaijmakers, Jan AM Leufkens, Hubert GM BMC Health Serv Res Research Article 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%). CONCLUSION: 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. BioMed Central 2007-07-10 /pmc/articles/PMC1959200/ /pubmed/17620145 http://dx.doi.org/10.1186/1472-6963-7-106 Text en Copyright © 2007 Menckeberg et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Menckeberg, Tanja T
Belitser, Svetlana V
Bouvy, Marcel L
Bracke, Madelon
Lammers, Jan-Willem J
Raaijmakers, Jan AM
Leufkens, Hubert GM
Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence
title Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence
title_full Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence
title_fullStr Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence
title_full_unstemmed Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence
title_short Distinguishing patterns in the dynamics of long-term medication use by Markov analysis: beyond persistence
title_sort distinguishing patterns in the dynamics of long-term medication use by markov analysis: beyond persistence
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1959200/
https://www.ncbi.nlm.nih.gov/pubmed/17620145
http://dx.doi.org/10.1186/1472-6963-7-106
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