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Medication Adherence Trajectories: A Systematic Literature Review

BACKGROUND: Traditional adherence measures such as proportion of days covered (PDC) and medication possession ratio (MPR) are limited in their ability to explain patient medication adherence over time. Group-based trajectory modeling (GBTM) is a new methodological approach that visually describes th...

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Autores principales: Alhazami, Mai, Pontinha, Vasco M., Patterson, Julie A., Holdford, David A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academy of Managed Care Pharmacy 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391275/
https://www.ncbi.nlm.nih.gov/pubmed/32857646
http://dx.doi.org/10.18553/jmcp.2020.26.9.1138
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author Alhazami, Mai
Pontinha, Vasco M.
Patterson, Julie A.
Holdford, David A.
author_facet Alhazami, Mai
Pontinha, Vasco M.
Patterson, Julie A.
Holdford, David A.
author_sort Alhazami, Mai
collection PubMed
description BACKGROUND: Traditional adherence measures such as proportion of days covered (PDC) and medication possession ratio (MPR) are limited in their ability to explain patient medication adherence over time. Group-based trajectory modeling (GBTM) is a new methodological approach that visually describes the dynamics of long-term medication adherence and classifies adherence behavior into groups. OBJECTIVES: To describe and compare trajectories of medication nonadherence reported in the medical literature, including identifying consistent trends in adherence trajectories and disease and patient characteristics that predict trajectory group membership. METHODS: A systematic literature review was conducted in April 2020 in PubMed and CINAHL using MeSH terms and key words in appropriate combinations. Citations were screened for relevance using predefined inclusion and exclusion criteria and evaluated according to variables associated with group-based trajectory models. RESULTS: 21 articles met the study criteria and were reviewed. Generally, studies identified 4 to 6 trajectory groups that described longitudinal medication adherence behavior. Most commonly identified trajectories were labeled as (a) consistent, high adherence, (b) declining adherence, (c) early and consistent nonadherence, and (d) initial nonadherence followed by an increase. Several predictors, including socioeconomic status, disease characteristics, and therapy initiation were routinely associated with group membership. CONCLUSIONS: This review suggests that adherence trajectories and predictors of specific group membership may be similar across diverse disease states. GBTM describes longitudinal, dynamic patterns of medication adherence that may facilitate the development of targeted interventions to promote adherence. Implications for value-based payment systems are discussed in this review.
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spelling pubmed-103912752023-08-02 Medication Adherence Trajectories: A Systematic Literature Review Alhazami, Mai Pontinha, Vasco M. Patterson, Julie A. Holdford, David A. J Manag Care Spec Pharm Systematic Review BACKGROUND: Traditional adherence measures such as proportion of days covered (PDC) and medication possession ratio (MPR) are limited in their ability to explain patient medication adherence over time. Group-based trajectory modeling (GBTM) is a new methodological approach that visually describes the dynamics of long-term medication adherence and classifies adherence behavior into groups. OBJECTIVES: To describe and compare trajectories of medication nonadherence reported in the medical literature, including identifying consistent trends in adherence trajectories and disease and patient characteristics that predict trajectory group membership. METHODS: A systematic literature review was conducted in April 2020 in PubMed and CINAHL using MeSH terms and key words in appropriate combinations. Citations were screened for relevance using predefined inclusion and exclusion criteria and evaluated according to variables associated with group-based trajectory models. RESULTS: 21 articles met the study criteria and were reviewed. Generally, studies identified 4 to 6 trajectory groups that described longitudinal medication adherence behavior. Most commonly identified trajectories were labeled as (a) consistent, high adherence, (b) declining adherence, (c) early and consistent nonadherence, and (d) initial nonadherence followed by an increase. Several predictors, including socioeconomic status, disease characteristics, and therapy initiation were routinely associated with group membership. CONCLUSIONS: This review suggests that adherence trajectories and predictors of specific group membership may be similar across diverse disease states. GBTM describes longitudinal, dynamic patterns of medication adherence that may facilitate the development of targeted interventions to promote adherence. Implications for value-based payment systems are discussed in this review. Academy of Managed Care Pharmacy 2020-09 /pmc/articles/PMC10391275/ /pubmed/32857646 http://dx.doi.org/10.18553/jmcp.2020.26.9.1138 Text en Copyright © 2020, Academy of Managed Care Pharmacy. All rights reserved. https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Systematic Review
Alhazami, Mai
Pontinha, Vasco M.
Patterson, Julie A.
Holdford, David A.
Medication Adherence Trajectories: A Systematic Literature Review
title Medication Adherence Trajectories: A Systematic Literature Review
title_full Medication Adherence Trajectories: A Systematic Literature Review
title_fullStr Medication Adherence Trajectories: A Systematic Literature Review
title_full_unstemmed Medication Adherence Trajectories: A Systematic Literature Review
title_short Medication Adherence Trajectories: A Systematic Literature Review
title_sort medication adherence trajectories: a systematic literature review
topic Systematic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391275/
https://www.ncbi.nlm.nih.gov/pubmed/32857646
http://dx.doi.org/10.18553/jmcp.2020.26.9.1138
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