First-Fill Medication Discontinuations and Nonadherence to Antihypertensive Therapy: An Observational Study

Evans, Charity; Eurich, Dean T.; Rémillard, Alfred J.; Shevchuk, Yvonne; Blackburn, David

doi:10.1038/ajh.2011.198

Cited by 41 publications

(37 citation statements)

References 28 publications

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“…First, studies restricted to individuals starting new medications will almost always find lower adherence rates compared to studies where “experienced” users are included. This observation results from a consistently high rate of attrition observed in the first few months after starting any new medication 20,21. Second, adherence rates expressed as percentages can vary substantially depending on whether they are categorical percentages (ie, percent of a population achieving ≥ 80% adherence) or are mean percentages (mean percent adherence achieved in a population).…”

Section: Non-adherence Rates Require Careful Interpretationmentioning

confidence: 99%

“…Non-adherence in the first year appears to be consistently driven by three unique patterns of medication use: (a) primary non-adherence, (b) non-persistence, and (c) noncompliance or poor execution 21,29. Primary non-adherence refers to patients who receive a prescription but never actually obtain the medication.…”

Section: Patterns Of Non-adherencementioning

confidence: 99%

“…Those exhibiting non-persistence stop taking their medication altogether, whereas poor executers continue taking prescribed medications but fail to consume the recommended quantity on a regular basis 31. Recent studies suggest that “early non-persistence,” where individuals discontinue a medication soon after obtaining the first prescription, contributes disproportionately to overall non-adherence in the first year of therapy 5,21,32. For example, individuals who discontinue antihypertensive or statin medications within the first 3 months of therapy make up between 30% and 50% of all cases of non-adherence in the first year 21,32.…”

Section: Patterns Of Non-adherencementioning

confidence: 99%

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Nonadherence in type 2 diabetes: practical considerations for interpreting the literature

Blackburn

Swidrovich²,

Lemstra³

2013

PPA

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The rising prevalence of type 2 diabetes poses a serious threat to human health and the viability of many health care systems around the world. Although several prescription medications can play a vital role in controlling symptoms and preventing complications, non-adherence to these therapies is highly prevalent and has been linked to increases in morbidity, mortality, and health care costs. Although a vast array of significant adherence predictors has been identified, the ability to explain or predict non-adherence with known risk-factors remains poor. Further, the definitions, outcomes, and various measures used in the non-adherence literature can be misleading for the unfamiliar reviewer. In this narrative review, a practical overview of important considerations for interpreting adherence endpoints and measures is discussed. Also, an organizational framework is proposed to consider published adherence interventions. This framework may allow for a unique appreciation into areas of limited knowledge and thus highlights targets for future research.

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Section: Non-adherence Rates Require Careful Interpretationmentioning

confidence: 99%

Section: Patterns Of Non-adherencementioning

confidence: 99%

Section: Patterns Of Non-adherencementioning

confidence: 99%

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Nonadherence in type 2 diabetes: practical considerations for interpreting the literature

Blackburn

Swidrovich²,

Lemstra³

2013

PPA

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“…[4][5][6][7][8][51][52][53][54][55][56][57][58] Medication non-adherence can lead to adverse health outcomes, increased hospitalisations and health care costs. 3,12,18,55,59 The adverse impact of medication non-adherence grows as the burden of chronic diseases increases.…”

Section: Epidemiology Of Medication Non-adherencementioning

confidence: 99%

“…5,53 There is a tendency for medication adherence in chronic illnesses to decline over time. 7,8,56 Non-adherence to recently initiated statins increased between one-month and twelve months in: hypertension (18% versus 47.9%), heart failure (16.3% versus 50%) and coronary heart disease (28.2% versus 38.3%) populations. 7 Alendronate non-adherence in patients with osteoporosis increased, particularly during the first six to twelve months after the initial prescription.…”

Section: Prevalencementioning

confidence: 99%

Improving medication adherence in patients with chronic disease using a targeted and tailored approach

Nguyen¹

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Improving adherence to medications is an opportunity that can yield great improvements in health outcomes and reducing health costs. Supporting adherence to medicines requires insight into a patient's medication-taking behaviour and their reasons for non-adherence.Adherence interventions that show most promise include multifaceted interventions, and those targeted to non-adherent patients and/or tailored to patient-specific reasons for nonadherence. To identify non-adherent patients and their reasons for non-adherence in the practice setting, I argue that we require inexpensive measures that are easy to use and can inform the discussion with patients about their adherence. Adherence scales are inexpensive, easy-to-administer and have the potential to explore both medication-taking behaviour and reasons for behaviour.The overall aim of the thesis is to determine if a targeted and tailored intervention based on a discussion informed by validated adherence scales, will improve adherence to a recently initiated cardiovascular medication. I hypothesise that targeting and tailoring an intervention to non-adherent participants based on a discussion informed by adherence scales, will improve adherence at three months as measured by the four-item Medication Adherence Questionnaire (MAQ). I will also test whether improvements in adherence at three months are sustained at six months and explore the changes in adherence and reasons for nonadherence over time.The first part of the thesis involved identifying validated adherence scales suitable for use in the intervention. A systematic review was conducted on adherence scales to explore their use and validation. We found that adherence scales measured different aspects of adherence: medication-taking behaviour, barriers to adherence and beliefs associated with adherence. Adherence scales have been validated in different disease populations and against different measures of adherence. We selected two adherence scales for our study: the MAQ and Beliefs about Medicines Questionnaire-Specific (BMQ-S). The MAQ is one of the most commonly used adherence scales that has been validated in many disease populations and against different measures of adherence including electronic monitoring.The BMQ-S has been extensively used to elicit medication beliefs associated with medication adherence and validated in a number of diseases including cardiovascular disease, asthma and depression.A randomised controlled trial was conducted to determine if a targeted and tailored intervention would improve medication adherence. Four hundred and eight patients were iii assessed for eligibility from two community pharmacies, from which 152 patients were enrolled into the study. All enrolled participants completed the MAQ, BMQ-S and Brief Illness Perceptions Questionnaire (BIPQ). There were 120 participants identified as non-adherent using the MAQ, who were randomised into an intervention or control group. The remaining 32 participants were identified as adherent. In the intervention group, the r...

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Treatment interruption in hypertensive patients during the COVID‐19 pandemic: An interrupted time series analysis using prescription data in Okayama, Japan

Nakamura,

Mitsuhashi,

Matsumoto

et al. 2024

J of Gen and Family Med

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BackgroundThe COVID‐19 pandemic has impacted healthcare behaviors, leading to fewer pediatric visits in Japan and potentially fewer visits by adult patients. However, existing Japanese studies on treatment interruptions have generally relied on questionnaire‐based methods. In this study, we assessed the impact of the pandemic on antihypertensive treatment interruption using real‐world prescription data.MethodsWe conducted an interrupted time series analysis using the National Health Insurance Database in Okayama Prefecture, Japan. Participants included individuals aged 40–69 years with at least one antihypertensive prescription between 2018 and 2020. Treatment interruption was defined as a 3‐month or longer gap in prescriptions after medication depletion. We used segmented Poisson regression with models unadjusted and adjusted for seasonality and over‐dispersion to assess monthly treatment interruptions before and after Japan's April 2020 emergency.ResultsDuring the study period, 23.0% of 55,431 participants experienced treatment interruptions. Cyclical fluctuations in interruptions were observed. The crude analysis indicated a 1.2‐fold increase in treatment interruptions following the pandemic; however, the adjusted models showed no significant changes. Even among higher‐risk groups, such as women, younger adults, and those with shorter prescriptions, no significant alterations were observed.ConclusionWe found no significant impact of the COVID‐19 pandemic on antihypertensive treatment interruption in Okayama Prefecture. The less severe outbreak in the area or increased use of telemedicine and extended prescriptions may have contributed to treatment continuity. Further research is needed using a more stable and comprehensive database, broader regional data, and detailed prescription records to validate and extend our findings.

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First-Fill Medication Discontinuations and Nonadherence to Antihypertensive Therapy: An Observational Study

Abstract: A substantial proportion of nonadherence to AHT medications is due to discontinuations after only a single dispensation.

Cited by 41 publications

References 28 publications

Nonadherence in type 2 diabetes: practical considerations for interpreting the literature

Nonadherence in type 2 diabetes: practical considerations for interpreting the literature

Improving medication adherence in patients with chronic disease using a targeted and tailored approach

Treatment interruption in hypertensive patients during the COVID‐19 pandemic: An interrupted time series analysis using prescription data in Okayama, Japan

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