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      How should we measure medication adherence in clinical trials and practice?

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          To determine if simple adherence measures, such as twenty-four hour recall and refill history, are accurate for routine use, compared to more time-consuming measures such as pill counts.


          Randomized, double-blind, placebo-controlled trial.


          Walter Reed Army Medical Center, a tertiary medical center in Washington.


          Men and women >30 years old with known coronary heart disease and taking a statin medication.


          Clinical pharmacists met with patients for adherence assessments.

          Main outcome measures

          Adherence was measured by pill counts, twenty-four hour recall by patient, and refill history per computer record. Temporal changes in these adherence measures were assessed using general linear models for repeated measures.


          Adherence was consistently greater for the experimental agent than for the statin therapy (n = 148). Mean pill count adherence for statin drug was 78.7 ± 25.2% compared to 93.5 ± 11.6% (P < 0.001) for the study agent. Refill history and twenty-four hour recall inaccurately measured adherence when compared to pill counts. Adherence, as determined by pill count, for both experimental (P = 0.029) and statin therapy (P = 0.015) showed significant variability across time in general linear models. Neither refill history nor twenty-four hour recall was sensitive to temporal changes.


          Twenty-four hour recall and refill history inaccurately measure medication adherence for both clinical trial and clinical practice pharmacotherapies. Further, these measures are insensitive to changes in adherence. For a single or multiple assessments across time, pill count more accurately measures medication adherence. Pill count should be the standard for monitoring medication adherence for both clinical trials and clinical practice.

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          Most cited references 29

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          Methods for measuring and monitoring medication regimen adherence in clinical trials and clinical practice.

           K C Farmer (1999)
          Researchers and clinicians have used numerous methods in their attempts to adequately assess patient compliance (adherence) with medication regimens and to identify noncompliant patients. Large variations have been reported in the extent of noncompliance in individual patients and large populations. In addition, nonadherence has often been poorly defined. Direct measures of adherence include drug assays of blood or urine, use of drug markers with the target medication, and direct observation of the patient receiving the medication. Indirect measures of adherence imply that the medication has been used by the patient; these measures include various forms of self-reporting by the patient, medication measurement (pill count), use of electronic monitoring devices, and review of prescription records and claims. Compliance measures should be assessed on the basis of their validity (sensitivity and specificity or statistical correlation) and the reference standard used. Many early studies used pill counts as a reference standard, but electronic monitoring devices such as the Medication Event Monitoring System have replaced pill counts as the reference standard. The choice of a method for measuring adherence to a medication regimen should be based on the usefulness and reliability of the method in light of the researcher's or clinician's goals. Specific methods may be more applicable to certain situations, depending on the type of adherence being assessed, the precision required, and the intended application of the results.
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            Patient adherence and medical treatment outcomes: a meta-analysis.

            Adherence is a factor in the outcome of medical treatment, but the strength and moderators of the adherence-outcome association have not been systematically assessed. A quantitative review using meta-analysis of three decades of empirical research correlating adherence with objective measures of treatment outcomes. Sixty-three studies assessing patient adherence and outcomes of medical treatment were found involving medical regimens recommended by a nonpsychiatrist physician, and measuring patient adherence and health outcomes. Studies were analyzed according to disease (acute/chronic, severity), population (adult/child), type of regimen (preventive/treatment, use of medication), and type and sensitivity of adherence and outcomes measurements. Overall, the outcome difference between high and low adherence is 26%. According to a stringent random effects model, adherence is most strongly related to outcomes in studies of nonmedication regimens, where measures of adherence are continuous, and where the disease is chronic (particularly hypertension, hypercholesterolemia, intestinal disease, and sleep apnea). A less stringent fixed effects model shows a trend for higher adherence-outcome correlations in studies of less serious conditions, of pediatric patients, and in those studies using self-reports of adherence, multiple measures of adherence, and less specific measures of outcomes. Intercorrelations among moderator variables in multiple regression show that the best predictor of the adherence-outcome relationship is methodological-the sensitivity/quality of the adherence assessment.
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              A comparison study of multiple measures of adherence to HIV protease inhibitors.

              Poor adherence to HIV protease inhibitors may compromise the effectiveness of treatment. Few studies have compared methods for measuring adherence or have related adherence measures to a clinical outcome. To examine the relationship among a composite score of adherence, the three primary measures of adherence, and HIV virologic response. Longitudinal cohort study. Public HIV clinic. 108 HIV-infected adults receiving protease inhibitors or non-nucleoside reverse transcriptase inhibitors who were monitored for 666 monthly intervals. Medication Event Monitoring System (MEMS), pill count, and interview combined into a composite adherence score (CAS), and HIV viral load. Mean antiretroviral adherence differed by adherence measure (MEMS, 0.63; pill count, 0.83; interview, 0.93; and CAS, 0.76). Composite adherence score decreased significantly over time. Composite adherence score, MEMS values, pill values, and interview values were statistically significantly associated with achievement of an undetectable viral load within 6 months of initiating therapy. Composite adherence score showed the strongest predictive relationship (odds ratios for a 10% increase in adherence for CAS, MEMS, pill count, and interview, respectively, were 1.26 [95% CI, 1.16 to 1.37], 1.13 [CI, 1.06 to 1.21], 1.10 [CI, 1.02 to 1.19], and 1.35 [CI, 0.94 to 1.94]). Different measures applied to the same patient suggest different levels of adherence. Adherence may be underestimated by MEMS and overestimated by pill count and interview. A summary measure combining several measures is more strongly related to a clinical response, but more practical measurement methods are needed for clinical use.

                Author and article information

                Ther Clin Risk Manag
                Therapeutics and Clinical Risk Management
                Therapeutics and Clinical Risk Management
                Dove Medical Press
                August 2007
                August 2007
                : 3
                : 4
                : 685-690
                Pharmacy and Cardiology Services, Walter Reed Army Medical Center Washington, DC, USA
                Author notes
                Correspondence: Jeannie Kim Lee Clinical Pharmacist, Department of Pharmacy, Walter Reed Army Medical Center, 6900 Georgia Avenue, NW, Building 2, Room 2P02, Washington, DC 20307-5001, USA Tel +1 202 782 5774, Fax +1 202 782 8242, Email jeannie.lee@ 123456na.amedd.army.mil
                © 2007 Dove Medical Press Limited. All rights reserved
                Original Research


                adherence, pharmacist, niacin, pill count, simvastatin, hyperlipidemia


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