Measuring adherence with medications: time is of the essence

Steiner, John F.

doi:10.1002/pds.3932

Cited by 13 publications

(12 citation statements)

References 15 publications

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“…Clinicians and researchers recognize that adherence changes over time. 27 Yet, this reality is often ignored in studies that measure adherence only once, or over a short interval. Even when measured longitudinally, data are often averaged over time.…”

Section: Myth 3: Adherence Is Staticmentioning

confidence: 99%

The myths of medication adherence

Gellad

Thorpe

Steiner

et al. 2017

Pharmacoepidemiology and Drug

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Section: Myth 3: Adherence Is Staticmentioning

confidence: 99%

The myths of medication adherence

Gellad

Thorpe

Steiner

et al. 2017

Pharmacoepidemiology and Drug

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“…Adherence refers to the extent to which a patient takes medication as prescribed by a physician. Persistence is determined from continued prescription of a drug by the physician . A number of studies have indicated non‐adherence and non‐persistence with statin therapy .…”

Section: Introductionmentioning

confidence: 99%

Patient-related characteristics associated with non-persistence with statin therapy in elderly patients following an ischemic stroke

Wawruch

Zatko²,

Wimmer

et al. 2016

Pharmacoepidemiol Drug Saf

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“…However, through their method, time‐varying adherence to medication has been computed over a time period defined by three successive fills, time‐lapse different from the global time scale of the most studied clinical outcomes (e.g., time‐to‐event in survival analysis). Therefore, as Steiner (2016) highlighted, to establish a relationship between time‐varying adherence and clinical outcomes, it is fundamental that these two components are measured on the same time scale. In this way, it could be possible to investigate the effect of the longitudinal adherence on the clinical outcome.…”

Section: Introductionmentioning

confidence: 99%

Dynamic monitoring of the effects of adherence to medication on survival in heart failure patients: A joint modeling approach exploiting time‐varying covariates

Spreafico

Ieva

2020

Biometrical J

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Adherence to medication is the process by which patients take their drugs as prescribed, and represents an issue in pharmacoepidemiological studies. Poor adherence is often associated with adverse health conditions and outcomes, especially in case of chronic diseases such as heart failure (HF). This turns out in an increased request for health care services, and in a greater burden for the health care system. In recent years, there has been a substantial growth in pharmacotherapy research, aimed at studying effects and consequences of proper/improper adherence to medication both for the increasing awareness of the problem and for the pervasiveness of poor adherence among patients. However, the way adherence is computed and accounted for into predictive models is far from being informative as it may be. In fact, it is usually analyzed as a fixed baseline covariate, without considering its time‐varying behavior. The purpose and novelty of this study is to define a new personalized monitoring tool exploiting time‐varying definition of adherence to medication, within a joint modeling approach. In doing so, we are able to capture and quantify the association between the longitudinal process of dynamic adherence to medication with the long‐term survival outcome. Another novelty of this approach consists of exploiting the potential of health care administrative databases in order to reconstruct the dynamics of drugs consumption through pharmaceutical administrative registries. In particular, we analyzed administrative data provided by Regione Lombardia ‐ Healthcare Division related to patients hospitalized for HF between 2000 and 2012.

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Measuring adherence with medications: time is of the essence

Cited by 13 publications

References 15 publications

The myths of medication adherence

The myths of medication adherence

Patient-related characteristics associated with non-persistence with statin therapy in elderly patients following an ischemic stroke

Dynamic monitoring of the effects of adherence to medication on survival in heart failure patients: A joint modeling approach exploiting time‐varying covariates

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