Cargando…

Group-Based Trajectory Modeling to Identify Patterns of Adherence and Its Predictors Among Older Adults on Angiotensin-Converting Enzyme Inhibitors (ACEIs)/Angiotensin Receptor Blockers (ARBs)

PURPOSE: Commonly prescribed medications among patients with comorbid diabetes mellitus and hypertension include ARBs and ACEIs. However, these medications are associated with suboptimal adherence leading to inadequately controlled blood pressure. Unlike traditional single estimates of proportion of...

Descripción completa

Detalles Bibliográficos
Autores principales: Paranjpe, Rutugandha, Johnson, Michael L, Essien, Ekere J, Barner, Jamie C, Serna, Omar, Gallardo, Esteban, Majd, Zahra, Fleming, Marc L, Ordonez, Nancy, Holstad, Marcia M, Abughosh, Susan M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7568634/
https://www.ncbi.nlm.nih.gov/pubmed/33116437
http://dx.doi.org/10.2147/PPA.S270809
_version_ 1783596563021430784
author Paranjpe, Rutugandha
Johnson, Michael L
Essien, Ekere J
Barner, Jamie C
Serna, Omar
Gallardo, Esteban
Majd, Zahra
Fleming, Marc L
Ordonez, Nancy
Holstad, Marcia M
Abughosh, Susan M
author_facet Paranjpe, Rutugandha
Johnson, Michael L
Essien, Ekere J
Barner, Jamie C
Serna, Omar
Gallardo, Esteban
Majd, Zahra
Fleming, Marc L
Ordonez, Nancy
Holstad, Marcia M
Abughosh, Susan M
author_sort Paranjpe, Rutugandha
collection PubMed
description PURPOSE: Commonly prescribed medications among patients with comorbid diabetes mellitus and hypertension include ARBs and ACEIs. However, these medications are associated with suboptimal adherence leading to inadequately controlled blood pressure. Unlike traditional single estimates of proportion of days covered (PDC), group-based trajectory modeling (GBTM) can graphically display the dynamic nature of adherence. The objective of this study was to evaluate adherence using GBTMs among patients prescribed ACEI/ARBs and identify predictors associated with each adherence trajectory. PATIENTS AND METHODS: Patients with an ACEI/ARBs prescription were identified between July 2017 and December 2017 using a Medicare Advantage dataset. PDC was used to measure monthly patient adherence during the one-year follow-up period. The monthly PDC was added to a logistic group-based trajectory model to provide distinct patterns of adherence. Further, a multinomial logistic regression was conducted to determine predictors of each identified adherence trajectory. Predictors included various socio-demographic and clinical patient characteristics. RESULTS: A total of 22,774 patients were included in the analysis and categorized into 4 distinct adherence trajectories: rapid decline (12.6%); adherent (58.5%); gaps in adherence (12.2%), and gradual decline (16.6%). Significant predictors associated with all lower adherence trajectories included 90 days refill, >2 number of other medications, ≥1 hospitalizations, and prevalent users. Significant predictors associated with the rapid decline trajectory included male sex, comorbidities, and increased CMS risk score. Further, significant predictors associated with the gaps in adherence trajectory included increasing age, and comorbidities. Lastly, significant predictors associated with the gradual decline trajectory included increasing age, no health plan subsidy, comorbidities, and increasing CMS risk score. CONCLUSION: Identifying various patient characteristics associated with non-adherent trajectories can guide the development of tailored interventions to enhance adherence to ACEI/ARBs.
format Online
Article
Text
id pubmed-7568634
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-75686342020-10-27 Group-Based Trajectory Modeling to Identify Patterns of Adherence and Its Predictors Among Older Adults on Angiotensin-Converting Enzyme Inhibitors (ACEIs)/Angiotensin Receptor Blockers (ARBs) Paranjpe, Rutugandha Johnson, Michael L Essien, Ekere J Barner, Jamie C Serna, Omar Gallardo, Esteban Majd, Zahra Fleming, Marc L Ordonez, Nancy Holstad, Marcia M Abughosh, Susan M Patient Prefer Adherence Original Research PURPOSE: Commonly prescribed medications among patients with comorbid diabetes mellitus and hypertension include ARBs and ACEIs. However, these medications are associated with suboptimal adherence leading to inadequately controlled blood pressure. Unlike traditional single estimates of proportion of days covered (PDC), group-based trajectory modeling (GBTM) can graphically display the dynamic nature of adherence. The objective of this study was to evaluate adherence using GBTMs among patients prescribed ACEI/ARBs and identify predictors associated with each adherence trajectory. PATIENTS AND METHODS: Patients with an ACEI/ARBs prescription were identified between July 2017 and December 2017 using a Medicare Advantage dataset. PDC was used to measure monthly patient adherence during the one-year follow-up period. The monthly PDC was added to a logistic group-based trajectory model to provide distinct patterns of adherence. Further, a multinomial logistic regression was conducted to determine predictors of each identified adherence trajectory. Predictors included various socio-demographic and clinical patient characteristics. RESULTS: A total of 22,774 patients were included in the analysis and categorized into 4 distinct adherence trajectories: rapid decline (12.6%); adherent (58.5%); gaps in adherence (12.2%), and gradual decline (16.6%). Significant predictors associated with all lower adherence trajectories included 90 days refill, >2 number of other medications, ≥1 hospitalizations, and prevalent users. Significant predictors associated with the rapid decline trajectory included male sex, comorbidities, and increased CMS risk score. Further, significant predictors associated with the gaps in adherence trajectory included increasing age, and comorbidities. Lastly, significant predictors associated with the gradual decline trajectory included increasing age, no health plan subsidy, comorbidities, and increasing CMS risk score. CONCLUSION: Identifying various patient characteristics associated with non-adherent trajectories can guide the development of tailored interventions to enhance adherence to ACEI/ARBs. Dove 2020-10-13 /pmc/articles/PMC7568634/ /pubmed/33116437 http://dx.doi.org/10.2147/PPA.S270809 Text en © 2020 Paranjpe et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Paranjpe, Rutugandha
Johnson, Michael L
Essien, Ekere J
Barner, Jamie C
Serna, Omar
Gallardo, Esteban
Majd, Zahra
Fleming, Marc L
Ordonez, Nancy
Holstad, Marcia M
Abughosh, Susan M
Group-Based Trajectory Modeling to Identify Patterns of Adherence and Its Predictors Among Older Adults on Angiotensin-Converting Enzyme Inhibitors (ACEIs)/Angiotensin Receptor Blockers (ARBs)
title Group-Based Trajectory Modeling to Identify Patterns of Adherence and Its Predictors Among Older Adults on Angiotensin-Converting Enzyme Inhibitors (ACEIs)/Angiotensin Receptor Blockers (ARBs)
title_full Group-Based Trajectory Modeling to Identify Patterns of Adherence and Its Predictors Among Older Adults on Angiotensin-Converting Enzyme Inhibitors (ACEIs)/Angiotensin Receptor Blockers (ARBs)
title_fullStr Group-Based Trajectory Modeling to Identify Patterns of Adherence and Its Predictors Among Older Adults on Angiotensin-Converting Enzyme Inhibitors (ACEIs)/Angiotensin Receptor Blockers (ARBs)
title_full_unstemmed Group-Based Trajectory Modeling to Identify Patterns of Adherence and Its Predictors Among Older Adults on Angiotensin-Converting Enzyme Inhibitors (ACEIs)/Angiotensin Receptor Blockers (ARBs)
title_short Group-Based Trajectory Modeling to Identify Patterns of Adherence and Its Predictors Among Older Adults on Angiotensin-Converting Enzyme Inhibitors (ACEIs)/Angiotensin Receptor Blockers (ARBs)
title_sort group-based trajectory modeling to identify patterns of adherence and its predictors among older adults on angiotensin-converting enzyme inhibitors (aceis)/angiotensin receptor blockers (arbs)
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7568634/
https://www.ncbi.nlm.nih.gov/pubmed/33116437
http://dx.doi.org/10.2147/PPA.S270809
work_keys_str_mv AT paranjperutugandha groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT johnsonmichaell groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT essienekerej groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT barnerjamiec groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT sernaomar groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT gallardoesteban groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT majdzahra groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT flemingmarcl groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT ordoneznancy groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT holstadmarciam groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs
AT abughoshsusanm groupbasedtrajectorymodelingtoidentifypatternsofadherenceanditspredictorsamongolderadultsonangiotensinconvertingenzymeinhibitorsaceisangiotensinreceptorblockersarbs