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Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors

BACKGROUND: Group-based trajectory modelling (GBTM) has recently been explored internationally as an improved approach to measuring medication adherence (MA) by differentiating between alternative temporal patterns of nonadherence. To build on this international research, we use the method to identi...

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Autores principales: Park, Kyu Hyung, Tickle, Leonie, Cutler, Henry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8784627/
https://www.ncbi.nlm.nih.gov/pubmed/35106359
http://dx.doi.org/10.1016/j.ssmph.2021.100973
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author Park, Kyu Hyung
Tickle, Leonie
Cutler, Henry
author_facet Park, Kyu Hyung
Tickle, Leonie
Cutler, Henry
author_sort Park, Kyu Hyung
collection PubMed
description BACKGROUND: Group-based trajectory modelling (GBTM) has recently been explored internationally as an improved approach to measuring medication adherence (MA) by differentiating between alternative temporal patterns of nonadherence. To build on this international research, we use the method to identify temporal patterns of medication adherence to antidepressants, bisphosphonates or statins, and their associations with patient characteristics. OBJECTIVES: The objectives include identification of MA types using GBTM, exploration of features and associated patient characteristics of each MA type, and identification of the advantages of GBTM compared to the traditional proportion of days covered (PDC) measure. DATA AND METHODS: We used 45 and Up Study survey data which contains information about demographics, family, health, diet, work and lifestyle of 267,153 participants aged at least 45 years across New South Wales, Australia. This data was linked to participant records of medication use, outpatient and inpatient care, and death. Our study participants initiated use of antidepressants (9287 participants), bisphosphonates (1660 participants) or statins (10,242 participants) during 2012–2016. MA types were identified from 180-day patterns of medication use for antidepressants and 360-day patterns for bisphosphonates and statins. Multinomial and binomial logistic regressions were performed to estimate participant characteristics associated with GBTM MA and PDC MA, respectively. RESULTS: Three GBTM MA types were identified for antidepressants and six for bisphosphonates and statins. For all three medications, MA types included: almost fully adherent; decreasing adherence and early discontinuation. The additional nonadherent types for bisphosphonates and statins were improved adherence, low adherence and later discontinuation. Participant characteristics impacting GBTM MA and PDC MA were consistent. However, several associations were uniquely found for GBTM MA as compared to PDC MA. CONCLUSION: GBTM permits clinicians, policy-makers and researchers to differentiate between alternative nonadherence patterns, allowing them to better identify patients at risk of poor adherence and tailor interventions accordingly.
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spelling pubmed-87846272022-01-31 Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors Park, Kyu Hyung Tickle, Leonie Cutler, Henry SSM Popul Health Article BACKGROUND: Group-based trajectory modelling (GBTM) has recently been explored internationally as an improved approach to measuring medication adherence (MA) by differentiating between alternative temporal patterns of nonadherence. To build on this international research, we use the method to identify temporal patterns of medication adherence to antidepressants, bisphosphonates or statins, and their associations with patient characteristics. OBJECTIVES: The objectives include identification of MA types using GBTM, exploration of features and associated patient characteristics of each MA type, and identification of the advantages of GBTM compared to the traditional proportion of days covered (PDC) measure. DATA AND METHODS: We used 45 and Up Study survey data which contains information about demographics, family, health, diet, work and lifestyle of 267,153 participants aged at least 45 years across New South Wales, Australia. This data was linked to participant records of medication use, outpatient and inpatient care, and death. Our study participants initiated use of antidepressants (9287 participants), bisphosphonates (1660 participants) or statins (10,242 participants) during 2012–2016. MA types were identified from 180-day patterns of medication use for antidepressants and 360-day patterns for bisphosphonates and statins. Multinomial and binomial logistic regressions were performed to estimate participant characteristics associated with GBTM MA and PDC MA, respectively. RESULTS: Three GBTM MA types were identified for antidepressants and six for bisphosphonates and statins. For all three medications, MA types included: almost fully adherent; decreasing adherence and early discontinuation. The additional nonadherent types for bisphosphonates and statins were improved adherence, low adherence and later discontinuation. Participant characteristics impacting GBTM MA and PDC MA were consistent. However, several associations were uniquely found for GBTM MA as compared to PDC MA. CONCLUSION: GBTM permits clinicians, policy-makers and researchers to differentiate between alternative nonadherence patterns, allowing them to better identify patients at risk of poor adherence and tailor interventions accordingly. Elsevier 2021-11-19 /pmc/articles/PMC8784627/ /pubmed/35106359 http://dx.doi.org/10.1016/j.ssmph.2021.100973 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Park, Kyu Hyung
Tickle, Leonie
Cutler, Henry
Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors
title Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors
title_full Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors
title_fullStr Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors
title_full_unstemmed Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors
title_short Identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors
title_sort identifying temporal patterns of adherence to antidepressants, bisphosphonates and statins, and associated patient factors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8784627/
https://www.ncbi.nlm.nih.gov/pubmed/35106359
http://dx.doi.org/10.1016/j.ssmph.2021.100973
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