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Shi L, Liu J, Fonseca V, et al. Correlation between adherence rates measured by MEMS and self-reported questionnaires: a meta-analysis. Health Qual Life Outcomes. 2010;8:99doi: 10.1186/1477-7525-8-99.
Shi, L., Liu, J., Fonseca, V., Walker, P., Kalsekar, A., & Pawaskar, M. (2010). Correlation between adherence rates measured by MEMS and self-reported questionnaires: a meta-analysis. Health and quality of life outcomes, 899. https://doi.org/10.1186/1477-7525-8-99
Shi, Lizheng, et al. "Correlation between adherence rates measured by MEMS and self-reported questionnaires: a meta-analysis." Health and quality of life outcomes vol. 8 (2010): 99. doi: https://doi.org/10.1186/1477-7525-8-99
Shi L, Liu J, Fonseca V, Walker P, Kalsekar A, Pawaskar M. Correlation between adherence rates measured by MEMS and self-reported questionnaires: a meta-analysis. Health Qual Life Outcomes. 2010 Sep 13;8:99. doi: 10.1186/1477-7525-8-99. PMID: 20836888; PMCID: PMC2944346.
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Health Qual Life Outcomes. 2010 Sep 13;8:99. doi: 10.1186/1477-7525-8-99.

Correlation between adherence rates measured by MEMS and self-reported questionnaires: a meta-analysis.

Health and quality of life outcomes

Lizheng Shi, Jinan Liu, Vivian Fonseca, Philip Walker, Anupama Kalsekar, Manjiri Pawaskar

Affiliations

  1. Department of Health Systems Management, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, USA. [email protected]

PMID: 20836888 PMCID: PMC2944346 DOI: 10.1186/1477-7525-8-99

Abstract

PURPOSE: It is vital to understand the associations between the medication event monitoring systems (MEMS) and self-reported questionnaires (SRQs) because both are often used to measure medication adherence and can produce different results. In addition, the economic implication of using alternative measures is important as the cost of electronic monitoring devices is not covered by insurance, while self-reports are the most practical and cost-effective method in the clinical settings. This meta-analysis examined the correlations of two measurements of medication adherence: MEMS and SRQs.

METHODS: The literature search (1980-2009) used PubMed, OVID MEDLINE, PsycINFO (EBSCO), CINAHL (EBSCO), OVID HealthStar, EMBASE (Elsevier), and Cochrane Databases. Studies were included if the correlation coefficients [Pearson (rp) or Spearman (rs)] between adherences measured by both MEMS and SRQs were available or could be calculated from other statistics in the articles. Data were independently abstracted in duplicate with standardized protocol and abstraction form including 1) first author's name; 2) year of publication; 3) disease status of participants; 4) sample size; 5) mean age (year); 6) duration of trials (month); 7) SRQ names if available; 8) adherence (%) measured by MEMS; 9) adherence (%) measured by SRQ; 10) correlation coefficient and relative information, including p-value, 95% confidence interval (CI). A meta-analysis was conducted to pool the correlation coefficients using random-effect model.

RESULTS: Eleven studies (N = 1,684 patients) met the inclusion criteria. The mean of adherence measured by MEMS was 74.9% (range 53.4%-92.9%), versus 84.0% by SRQ (range 68.35%-95%). The correlation between adherence measured by MEMS and SRQs ranged from 0.24 to 0.87. The pooled correlation coefficient for 11 studies was 0.45 (p = 0.001, 95% confidence interval [95% CI]: 0.34-0.56). The subgroup meta-analysis on the seven studies reporting rp and four studies reporting rs reported the pooled correlation coefficient: 0.46 (p = 0.011, 95% CI: 0.33-0.59) and 0.43 (p = 0.0038, 95% CI: 0.23-0.64), respectively. No differences were found for other subgroup analyses.

CONCLUSION: Medication adherence measured by MEMS and SRQs tends to be at least moderately correlated, suggesting that SRQs give a good estimate of medication adherence.

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