Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis
Background: Medication adherence measures are often dichotomized to classify patients into those with good or poor adherence using a cut-off value ⩾80%, but this cut-off may not be universal across diseases or medication classes. This study aimed to examine the cut-off value that optimally distingui...
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Series: | Therapeutic Advances in Chronic Disease |
Online Access: | https://doi.org/10.1177/2040622321990264 |
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doaj-f269e43caa0b4cc486dd601aecf71e6b2021-02-17T17:03:37ZengSAGE PublishingTherapeutic Advances in Chronic Disease2040-62312021-02-011210.1177/2040622321990264Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysisMing Tsuey LimNorazida Ab RahmanXin Rou TehChee Lee ChanShantini ThevendranNajwa Ahmad HamdiKa Keat LimSheamini SivasampuBackground: Medication adherence measures are often dichotomized to classify patients into those with good or poor adherence using a cut-off value ⩾80%, but this cut-off may not be universal across diseases or medication classes. This study aimed to examine the cut-off value that optimally distinguish good and poor adherence by using the medication possession ratio (MPR) and proportion of days covered (PDC) as adherence measures and glycated hemoglobin (HbA1c) as outcome measure among type 2 diabetes mellitus (T2DM) patients. Method: We used pharmacy dispensing data of 1461 eligible T2DM patients from public primary care clinics in Malaysia treated with oral antidiabetic drugs between January 2018 and May 2019. Adherence rates were calculated during the period preceding the HbA1c measurement. Adherence cut-off values for the following conditions were compared: adherence measure (MPR versus PDC), assessment period (90-day versus 180-day), and HbA1c target (⩽7.0% versus ⩽8.0%). Results: The optimal adherence cut-offs for MPR and PDC in predicting HbA1c ⩽7.0% ranged between 86.1% and 98.3% across the two assessment periods. In predicting HbA1c ⩽8.0%, the optimal adherence cut-offs ranged from 86.1% to 92.8%. The cut-off value was notably higher with PDC as the adherence measure, shorter assessment period, and a stricter HbA1c target (⩽7.0%) as outcome. Conclusion: We found that optimal adherence cut-off appeared to be slightly higher than the conventional value of 80%. The adherence thresholds may vary depending on the length of assessment period and outcome definition but a reasonably wise cut-off to distinguish good versus poor medication adherence to be clinically meaningful should be at 90%.https://doi.org/10.1177/2040622321990264 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ming Tsuey Lim Norazida Ab Rahman Xin Rou Teh Chee Lee Chan Shantini Thevendran Najwa Ahmad Hamdi Ka Keat Lim Sheamini Sivasampu |
spellingShingle |
Ming Tsuey Lim Norazida Ab Rahman Xin Rou Teh Chee Lee Chan Shantini Thevendran Najwa Ahmad Hamdi Ka Keat Lim Sheamini Sivasampu Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis Therapeutic Advances in Chronic Disease |
author_facet |
Ming Tsuey Lim Norazida Ab Rahman Xin Rou Teh Chee Lee Chan Shantini Thevendran Najwa Ahmad Hamdi Ka Keat Lim Sheamini Sivasampu |
author_sort |
Ming Tsuey Lim |
title |
Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis |
title_short |
Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis |
title_full |
Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis |
title_fullStr |
Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis |
title_full_unstemmed |
Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis |
title_sort |
optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis |
publisher |
SAGE Publishing |
series |
Therapeutic Advances in Chronic Disease |
issn |
2040-6231 |
publishDate |
2021-02-01 |
description |
Background: Medication adherence measures are often dichotomized to classify patients into those with good or poor adherence using a cut-off value ⩾80%, but this cut-off may not be universal across diseases or medication classes. This study aimed to examine the cut-off value that optimally distinguish good and poor adherence by using the medication possession ratio (MPR) and proportion of days covered (PDC) as adherence measures and glycated hemoglobin (HbA1c) as outcome measure among type 2 diabetes mellitus (T2DM) patients. Method: We used pharmacy dispensing data of 1461 eligible T2DM patients from public primary care clinics in Malaysia treated with oral antidiabetic drugs between January 2018 and May 2019. Adherence rates were calculated during the period preceding the HbA1c measurement. Adherence cut-off values for the following conditions were compared: adherence measure (MPR versus PDC), assessment period (90-day versus 180-day), and HbA1c target (⩽7.0% versus ⩽8.0%). Results: The optimal adherence cut-offs for MPR and PDC in predicting HbA1c ⩽7.0% ranged between 86.1% and 98.3% across the two assessment periods. In predicting HbA1c ⩽8.0%, the optimal adherence cut-offs ranged from 86.1% to 92.8%. The cut-off value was notably higher with PDC as the adherence measure, shorter assessment period, and a stricter HbA1c target (⩽7.0%) as outcome. Conclusion: We found that optimal adherence cut-off appeared to be slightly higher than the conventional value of 80%. The adherence thresholds may vary depending on the length of assessment period and outcome definition but a reasonably wise cut-off to distinguish good versus poor medication adherence to be clinically meaningful should be at 90%. |
url |
https://doi.org/10.1177/2040622321990264 |
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