Measurement Issues in Using Pharmacy Records to Calculate Adherence to Antiretroviral Drugs

Grimes, Deanna E.; Andrade, Roberto; Niemeyer, Chad R.; Grimes, Richard M.

doi:10.1310/hct1402-68

Cited by 6 publications

(13 citation statements)

References 24 publications

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“…Pharmacy data may serve as a source for the calculation of pick-up rates and refill rates. Pick-up rates describe the number of picked-up prescriptions as a percent of the total prescribed doses 49. Refill rates are defined as the division of the amount of days the drugs have been prescribed by the total calendar days of that period 50.…”

Section: Resultsmentioning

confidence: 99%

<p>Assessing methods of measuring medication adherence in chronically ill children–a narrative review</p>

Al-Hassany¹,

Kloosterboer²,

Dierckx³

et al. 2019

PPA

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Nonadherence in children who use long-term medication is a serious problem and assessing adherence is an important step to provide solutions to this problem. Medication adherence can be measured by several methods, including (a) self-report questionnaires or structured interviews, (b) therapeutic drug monitoring (TDM), (c) electronic devices, and (d) pick-up/refill rates. The objective of this narrative review is to provide an overview of the literature about methods for the measurement of medication adherence in chronically ill children and adolescents. Therefore, we conducted a literature search by using multiple databases. Four methods of monitoring medication adherence are presented for the most described chronic diseases: asthma, HIV/AIDS, epilepsy, diabetes mellitus and ADHD. First, 10 commonly used self-report questionnaires and structured interviews are described, including the main characteristics, (dis)advantages and their validation studies. Second, the use of TDM in pediatric trials for medication adherence measurement is discussed. New sampling methods (e.g. dried blood spot) and sampling matrices (e.g. hair, saliva and urine) have shown their benefits for TDM in children. Third, electronic devices to measure medication adherence in children are presented, being developed for several drug administration routes. Fourth, the analyses, advantages and disadvantages of pharmacy data are discussed. The usage of this data requires specific calculations and interpretations to assess adherence. As presented in this review, every adherence method has specific (dis)advantages. When deciding which adherence method is applicable, validity and generalizability should be taken into account. Combining multiple methods seems to offer the best solution in the daily clinical practice.

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Section: Resultsmentioning

confidence: 99%

<p>Assessing methods of measuring medication adherence in chronically ill children–a narrative review</p>

Al-Hassany¹,

Kloosterboer²,

Dierckx³

et al. 2019

PPA

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“…Therefore, in order to reveal cases of non-adherence, validated tools (e.g., Morisky, or MARS questionnaires), and objective assessment methods (electronic monitoring widely accepted as a gold standard) are strongly advisable (Osterberg and Blaschke, 2005). In daily practice, relevant databases, such as electronic health records, and pharmacy fill records, may be effectively used for screening for non-adherence (Carroll et al, 2011; Grimes et al, 2013). On the other hand, adherence-enhancing interventions are worth considering to implement in daily clinical practice, to be used on a regular basis for every individual patients.…”

Section: Discussionmentioning

confidence: 99%

Determinants of patient adherence: a review of systematic reviews

Kardas¹,

Lewek²,

2013

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Purpose: A number of potential determinants of medication non-adherence have been described so far. However, the heterogenic quality of existing publications poses the need for the use of a rigorous methodology in building a list of such determinants. The purpose of this study was a systematic review of current research on determinants of patient adherence on the basis of a recently agreed European consensus taxonomy and terminology.Methods: MEDLINE, EMBASE, CINAHL, Cochrane Library, IPA, and PsycINFO were systematically searched for systematic reviews published between 2000/01/01 and 2009/12/31 that provided determinants on non-adherence to medication. The searches were limited to reviews having adherence to medication prescribed by health professionals for outpatient as a major topic.Results: Fifty-one reviews were included in this review, covering 19 different disease categories. In these reviews, exclusively assessing non-adherence to chronic therapies, 771 individual factor items were identified, of which most were determinants of implementation, and only 47—determinants of persistence with medication. Factors with an unambiguous effect on adherence were further grouped into 8 clusters of socio-economic-related factors, 6 of healthcare team- and system-related factors, 6 of condition-related factors, 6 of therapy-related factors, and 14 of patient-related factors. The lack of standardized definitions and use of poor measurement methods resulted in many inconsistencies.Conclusions: This study provides clear evidence that medication non-adherence is affected by multiple determinants. Therefore, the prediction of non-adherence of individual patients is difficult, and suitable measurement and multifaceted interventions may be the most effective answer toward unsatisfactory adherence. The limited number of publications assessing determinants of persistence with medication, and lack of those providing determinants of adherence to short-term treatment identify areas for future research.

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“…Advantages of pharmacy refill data include being inexpensive and immune to social desirability/recall bias or tampering [ 8 , 11 ]. Such data usually [ 8 , 21 ], although not always [ 22 ], have at least moderate correlations with virologic outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…Further, pharmacy refill records will not reflect patients obtaining medications through alternative sources, such as free samples, family or friends, or other pharmacies, which may occur in the most vulnerable patients [ 8 ]. These concerns are highlighted by studies that have described groups of patients who were highly adherent as measured by pharmacy refill data, but did not achieve or maintain viral suppression, and poorly adherent patients who maintained undetectable viral load [ 11 , 23 ]. Such problems are unlikely to have occurred in our study, because other sources of obtaining treatment are limited.…”

Section: Discussionmentioning

confidence: 99%

“…Adherence estimated from pharmacy-refill data is likely to be more objective and accurate than self-report, but requires protocols for data collection and management [ 10 ]. Different measurement and calculation methods used on pharmacy data can lead to inconsistencies [ 11 , 12 ] when data are compared across cohorts or used in pooled analyses.…”

Section: Introductionmentioning

confidence: 99%

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Identifying Risk of Viral Failure in Treated HIV-Infected Patients Using Different Measures of Adherence: The Antiretroviral Therapy Cohort Collaboration

Ingle

Crane

Glass

et al. 2018

JCM

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Adherence to antiretroviral therapy (ART) is critical for successful treatment of Human Immunodeficiency Virus (HIV), but comparisons across settings are difficult because adherence is measured in different ways. We examined utility of different adherence measures for identification of patients at risk of viral failure (VF). Eight cohorts in the ART Cohort Collaboration contributed data from pharmacy refills or self-report questionnaires collected between 1996 and 2013 (N = 11689). For pharmacy data (N = 7156), we examined associations of percentage adherence during the 1st year of ART with VF (>500 copies/mL) at 1 year. For self-report data (N = 4533), we examined 28-day adherence with VF based on closest viral load measure within 6 months after questionnaire date. Since adherence differed markedly by measurement type, we defined different cut-off points for pharmacy (lower <45%, medium 45–99%, higher 100%) and self-report (lower ≤95%, medium 96–99%, higher 100%) data. Adjusted odds ratios (ORs) for VF in lower and medium, compared to higher adherence groups, were 23.04 (95% CI: 18.44–28.78) and 3.84 (3.36–4.39) for pharmacy data. For self-report data, they were 3.19 (2.31–4.40) and 1.08 (0.80–1.46). Both types of measure were strongly associated with VF. Although adherence measurements over longer time-frames are preferable for prediction, they are less useful for intervention.

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Measurement Issues in Using Pharmacy Records to Calculate Adherence to Antiretroviral Drugs

Abstract: This study demonstrated that 6 different methods of calculating adherence from pharmacy records yielded adherence rates of 28.1% to 56.2%. Studies using pharmacy records should specify how adherence is calculated.

Cited by 6 publications

References 24 publications

<p>Assessing methods of measuring medication adherence in chronically ill children–a narrative review</p>

<p>Assessing methods of measuring medication adherence in chronically ill children–a narrative review</p>

Determinants of patient adherence: a review of systematic reviews

Identifying Risk of Viral Failure in Treated HIV-Infected Patients Using Different Measures of Adherence: The Antiretroviral Therapy Cohort Collaboration

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