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

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 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%.

scholarly journals Determination of Factors Effecting Medication Adherence in Depressed Patients Receiving Antidepressants in Pakistan

2020 ◽  
Vol 8 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Muhammad Amir ◽  
Nathanial Rickles ◽  
Zeeshan Feroz ◽  
Anwer Ejaz Beg
Keyword(s):  
Medication Adherence ◽  
Significant Influence ◽  
Assessment Tool ◽  
Outpatient Setting ◽  
Vital Role ◽  
Limited Information ◽  
Self Assessment ◽  
Duration Of Therapy ◽  
Depressed Patients ◽  
Relationship Of

Background: The prevalence of depression in Pakistan is considered to be higher than other developing countries. Medication adherence is a major factor in the success and cost effectiveness of the treatment of depression. Limited information relating medication adherence and its factor are available for patients in Pakistan. Objective: The study aim to determine the factors associated with adherence of antidepressants in depressed patients. Methods: The study was conducted in outpatient setting of hospital. 200 participants were enrolled in the study. Self-assessment tool was used to determine the medication adherence. Results: The results showed that factors such as gender, education, employment and total number of medications have significant influence on adherence of antidepressants. The study also shows that the relationship of factors and adherence changes with the duration of therapy. Conclusion: Factors play a vital role in understanding the barriers in medication non-adherence. Factors effecting medication adherence change with respect to the duration of therapy. Gender, employment, morbidity and number of medications taken earlier have significant influence on medication adherence of antidepressants in depressed patients.

HIV Medication Adherence Measure

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

scholarly journals HBA1C Control Predictive Validity of Four Self-Reported Measures of Antidiabetes Medication Adherence

2014 ◽  
Vol 17 (7) ◽  
pp. A730
Author(s):  
A. Zongo ◽  
L. Guenette ◽  
J. Moisan ◽  
J.P. Gregoire
Keyword(s):  
Medication Adherence ◽  
Predictive Validity ◽  
Hba1c Control

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.

Effect of Electronic Prescribing Compared to Paper-Based (Handwritten) Prescribing on Primary Medication Adherence in an Outpatient Setting: A Systematic Review

2021 ◽  
Vol 12 (04) ◽  
pp. 845-855
Author(s):  
David Aluga ◽  
Lawrence A. Nnyanzi ◽  
Nicola King ◽  
Elvis A. Okolie ◽  
Peter Raby
Keyword(s):  
Medication Adherence ◽  
Randomized Study ◽  
The United States ◽  
Outpatient Setting ◽  
Electronic Prescribing ◽  
Future Research ◽  
Medical Subject Headings ◽  
Keywords And Phrases ◽  
Significant Difference ◽  
The Impact

Abstract Background Electronic prescriptions are often created and delivered electronically to the pharmacy while paper-based/handwritten prescriptions may be delivered to the pharmacy by the patients. These differences in the mode of creation and transmission of the two types of prescription could influence the rate at which outpatients fill new prescriptions of previously untried medications. Objectives This study aimed to evaluate literatures to determine the impact of electronic prescribing compared with paper-based/handwritten prescribing on primary medication adherence in an outpatient setting. Methods The keywords and phrases “outpatients,” “e-prescriptions,” “paper-based prescriptions,” and “primary medication adherence” were combined with their relevant synonyms and medical subject headings. A comprehensive literature search was conducted on EMBASE, CINAHL, and MEDLINE databases, and Google Scholar. The results of the search were screened and selected using predefined inclusion and exclusion criteria. The Critical Appraisal Skills Program (CASP) was used for quality appraisal of included studies. Data relevant to the objective of the review were extracted and analyzed through narrative synthesis. Results A total of 10 original studies were included in the final review, including 1 prospective randomized study and 9 observational studies. Nine of the 10 studies were performed in the United States. Four of the studies indicated that electronic prescribing significantly increases initial medication adherence, while four of the studies suggested the opposite. The remaining two studies found no significant difference in primary medication adherence between the two methods of prescribing. The variations in the studies did not allow the homogeneity required for meta-analysis to be achieved. Conclusion The conflicting findings relating to the efficacy of primary medication adherence across both systems demonstrate the need for a standardized measure of medication adherence. This would help further determine the respective benefits of both approaches. Future research should also be conducted in different countries to give a more accurate representation of adherence.

Concurrent and Predictive Validity of a Self-reported Measure of Medication Adherence

Medical Care ◽  
1986 ◽  
Vol 24 (1) ◽  
pp. 67-74 ◽  
Author(s):  
Donald E. Morisky ◽  
Lawrence W. Green ◽  
David M. Levine
Keyword(s):  
Medication Adherence ◽  
Predictive Validity
Sign in / Sign up

Export Citation Format

Share Document