Investigating the Potential for Bias When Using a Widely Accepted Medication Adherence Measure to Predict Mortality

2018 ◽  
Vol 38 (11) ◽  
pp. 1086-1094 ◽  
Author(s):  
Ralph C. Ward ◽  
David J. Taber ◽  
Robert Neal Axon ◽  
Mulugeta Gebregziabher
Keyword(s):  
Medication Adherence ◽  
Adherence Measure

scholarly journals Optimal cut-off points for adherence measure among patients with type 2 diabetes in primary care clinics: a retrospective analysis

2021 ◽  
Vol 12 ◽  
pp. 204062232199026
Author(s):  
Ming Tsuey Lim ◽  
Norazida Ab Rahman ◽  
Xin Rou Teh ◽  
Chee Lee Chan ◽  
Shantini Thevendran ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Medication Adherence ◽  
Poor Adherence ◽  
Adherence Measure ◽  
Primary Care Clinics ◽  
Assessment Period ◽  
Hba1c Target ◽  
Optimal Adherence

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%.

HIV Medication Adherence Measure

2012 ◽  
Author(s):  
Eva N. Woodward ◽  
David W. Pantalone
Keyword(s):  
Medication Adherence ◽  
Adherence Measure ◽  
Hiv Medication

Abstract 015: Importance of Balanced Follow-up Time and Other Study Design Considerations When Evaluating Adherence Using Two Novel Oral Anticoagulants

2017 ◽  
Vol 10 (suppl_3) ◽  
Author(s):  
Craig Coleman ◽  
Zhong Yuan ◽  
Jeffrey Schein ◽  
Concetta Crivera ◽  
Veronica Ashton ◽  
...  
Keyword(s):  
Medication Adherence ◽  
Real World ◽  
Oral Anticoagulant Therapy ◽  
Oral Anticoagulants ◽  
Real World Data ◽  
Adherence Measure ◽  
Adherence Measurement ◽  
Minimum Number ◽  
The Impact

Background: Medication adherence rates decline over time, especially after the first dispensing. Comparing adherence rates for medications that have been on the market for differing period of time may distort real differences in medication adherence. Other analysis factors such as minimum number of dispensing criteria and Pharmacy Quality Alliance (PQA) adherence measures can also affect adherence measurement. Objectives: To use one real world example (rivaroxaban vs apixaban) in non-valvular atrial fibrillation (NVAF) patients to quantify the impact of adjusting for imbalances in follow-up periods, minimum number of dispensing, and use of the PQA adherence measure. Methods: Using IMS Health Real-World Data Adjudicated Claims and Truven MarketScan claims databases, we included adult patients with ≥1 rivaroxaban or apixaban dispensing (index date), ≥1 year of pre-index eligibility, ≥1 AF diagnosis pre-index, newly initiated on oral anticoagulant therapy, and no valvular involvement. Adherence was evaluated using proportion of days covered (PDC) ≥0.8 for cohorts with (1) unbalanced follow-up (2) balanced follow-up (by matching on month and year of follow-up since fill-date) (3) ≥2 rivaroxaban or apixaban dispensings and a balanced follow-up, and using (4) the PQA adherence measure. Results: Rivaroxaban users had significantly longer mean (SD) follow-up than apixaban (408 [300] versus 254 [196] days, respectively). While apixaban users appeared to be more adherent in unadjusted analyses, this finding was reversed after 1) adjusting for unbalanced follow-up 2) excluding single-time users; and 3) applying the PQA-endorsed adherence measure (Figure). Similar results were found using the Truven databases. Conclusion: Comparisons of the adherence rates among medications need to account for the period of time each have been on the market, number of dispensing and PQA measures. Retrospective analyses of adherence that do not adjust for such differences could produce spurious findings.

Reliability of a Medication Adherence Measure in an Outpatient Setting

2005 ◽  
Vol 330 (3) ◽  
pp. 128-133 ◽  
Author(s):  
Marie Krousel-Wood ◽  
Ann Jannu ◽  
Richard N. Re ◽  
Paul Muntner ◽  
Karen Desalvo
Keyword(s):  
Medication Adherence ◽  
Outpatient Setting ◽  
Adherence Measure

scholarly journals Predictive Validity of a Medication Adherence Measure in an Outpatient Setting

2008 ◽  
Vol 10 (5) ◽  
pp. 348-354 ◽  
Author(s):  
Donald E. Morisky ◽  
Alfonso Ang ◽  
Marie Krousel-Wood ◽  
Harry J. Ward
Keyword(s):  
Medication Adherence ◽  
Predictive Validity ◽  
Outpatient Setting ◽  
Adherence Measure

scholarly journals Reach and Validity of an Objective Medication Adherence Measure Among Safety Net Health Plan Members with Diabetes: A Cross-Sectional Study

2015 ◽  
Vol 21 (8) ◽  
pp. 688-698 ◽  
Author(s):  
Neda Ratanawongsa ◽  
Andrew J. Karter ◽  
Judy Quan ◽  
Melissa M. Parker ◽  
Margaret Handley ◽  
...  
Keyword(s):  
Medication Adherence ◽  
Health Plan ◽  
Safety Net ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Adherence Measure

scholarly journals Assessing Analgesic Regimen Adherence with the Morisky Medication Adherence Measure for Taiwanese Patients with Cancer Pain

2008 ◽  
Vol 36 (2) ◽  
pp. 157-166 ◽  
Author(s):  
Jann Inn Tzeng ◽  
Chia-Chi Chang ◽  
Hsiu-Ju Chang ◽  
Chia-Chin Lin
Keyword(s):  
Medication Adherence ◽  
Cancer Pain ◽  
Adherence Measure ◽  
Regimen Adherence ◽  
Patients With Cancer ◽  
Analgesic Regimen

Improving medication adherence in patients with severe mental illness

2013 ◽  
Vol 19 (6) ◽  
pp. 69-80 ◽  
Author(s):  
Kelly C. Lee
Keyword(s):  
Mental Illness ◽  
Medication Adherence ◽  
Severe Mental Illness
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