Outcome measures for adherence data from a medication event monitoring system: A literature review

Linda Hartman, Willem F Lems, Maarten Boers, Linda Hartman, Willem F Lems, Maarten Boers

Abstract

What is known: Currently, medication bottles with an electronic cap are frequently used to measure medication adherence. This system is termed medication event monitoring system (MEMS). To our knowledge, the optimal method to summarize data from MEMS has not yet been determined.

Objective: Look for best practices on how to quantify adherence data from MEMS.

Methods: Review of PubMed, Embase and Cochrane databases for the articles on medication adherence with MEMS.

Results: Of 1493 identified articles, 207 were included in this review. The MEMS cap was used for a median of 3 months (IQR: 4; range: 1 week to 24 months) in various health conditions. Many different outcome measures were used. Most studies computed an adherence score, expressed as the percentage of days on which the correct dose of medication was taken. The threshold to mark people as adherent was most frequently, arbitrarily, set at 80% (range: 67%-95%). We found no data to support a specific threshold.

Discussion: Although the commonly used definition of adherence has face validity, we found no validation studies, and not all studies used the same cut-off for adherence. Ideally, a cut-off should be defined and validated in the context of the specific drug and its pharmacokinetic and dynamic characteristics, and perhaps other contextual factors, rather than generically. In addition, there was large heterogeneity in the definition of what "correct intake" of medication is.

What is new and conclusion: Outcome measures for MEMS data lacked standardization, and no demonstrable effort to validate any definition against a relevant clinical outcome is available. Consensus on the definition of adherence is urgently needed.

Keywords: adherence; literature review; outcome measures.

© 2018 The Authors. Journal of Clinical Pharmacy and Therapeutics Published by John Wiley & Sons Ltd.

Figures

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Figure 1
PRISMA flow diagram of article selection

References

    1. El Alili M, Vrijens B, Demonceau J, Evers SM, Hiligsmann M. A scoping review of studies comparing the medication event monitoring system (MEMS) with alternative methods for measuring medication adherence. Br J Clin Pharmacol. 2016;82(1):268‐279.
    1. . The Glucocorticoid Low‐dose Outcome in RheumatoId Arthritis Study (Gloria) 2018. . Accessed March 14, 2018.
    1. Bachmann LH, Stephens J, Richey CM, Hook EW 3rd. Measured versus self‐reported compliance with doxycycline therapy for chlamydia‐associated syndromes: high therapeutic success rates despite poor compliance. Sex Transm Dis. 1999;26(5):272‐278.
    1. Eby J, Chapman J, Marukutira T, et al. The adherence‐outcome relationship is not altered by diary‐driven adjustments of microelectronic monitor data. Pharmacoepidemiol Drug Saf. 2015;24(12):1313‐1320.
    1. Barker GT, Cook PF, Schmiege SJ, Kahook MY, Kammer JA, Mansberger SL. Psychometric properties of the Glaucoma Treatment Compliance Assessment Tool in a multicenter trial. Am J Ophthalmol. 2015;159(6): 1092–1099 e2.
    1. Cook PF, Schmiege SJ, Mansberger SL, et al. Motivational interviewing or reminders for glaucoma medication adherence? Results of a multi‐site randomized controlled trial. Psychol Health. 2017;32(2):145–165.
    1. Cook PF, Schmiege SJ, Mansberger SL, Kammer J, Fitzgerald T, Kahook MY. Predictors of adherence to glaucoma treatment in a multisite study. Ann Behav Med. 2015;49(1):29–39.
    1. Boland MV, Chang DS, Frazier T, Plyler R, Friedman DS. Electronic monitoring to assess adherence with once‐daily glaucoma medications and risk factors for nonadherence: the automated dosing reminder study. JAMA Ophthalmol. 2014;132(7):838–844.
    1. Rosen MI, Rigsby MO, Salahi JT, Ryan CE, Cramer JA. Electronic monitoring and counseling to improve medication adherence. Behav Res Ther. 2004;42(4):409–422.
    1. Magidson JF. Depressive symptoms, lifestyle structure, and art adherence among hiv‐infected individuals: a longitudinal mediation analysis. AIDS Behav. 2015;19(1):34–40.
    1. Yang J, Ko YH, Paik JW, et al. Symptom severity and attitudes toward medication: impacts on adherence in outpatients with schizophrenia. Schizophr Res. 2012;134(2–3):226–231.
    1. Santschi V, Wuerzner G, Schneider MP, Bugnon O, Burnier M. Clinical evaluation of IDAS II, a new electronic device enabling drug adherence monitoring. Eur J Clin Pharmacol. 2007;63(12):1179–1184.
    1. Deschamps AE, Graeve VD, van Wijngaerden E, et al. Prevalence and correlates of nonadherence to antiretroviral therapy in a population of HIV patients using Medication Event Monitoring System. AIDS Patient Care STDS. 2004;18(11):644–657.
    1. Israni AK, Weng FL, Cen YY, Joffe M, Kamoun M, Feldman HI. Electronically measured adherence to immunosuppressive medications and kidney function after deceased donor kidney transplantation. Clin Transplant. 2011;25(2):E124–E131.
    1. Olds PK, Kiwanuka JP, Nansera D, et al. Assessment of HIV antiretroviral therapy adherence by measuring drug concentrations in hair among children in rural Uganda. AIDS Care. 2015;27(3):327–332.
    1. Winkler A, Teuscher AU, Mueller B, Diem P. Monitoring adherence to prescribed medication in type 2 diabetic patients treated with sulfonylureas. Swiss Med Wkly. 2002;132(27–28):379–385.
    1. Lee JY, Kusek JW, Greene PG, et al. Assessing medication adherence by pill count and electronic monitoring in the African American Study of Kidney Disease and Hypertension (AASK) Pilot Study. Am J Hypertens. 1996;9(8):719–725.
    1. Alinia H, Moradi Tuchayi S, Smith JA, et al. Long‐term adherence to topical psoriasis treatment can be abysmal: a one‐year randomized intervention study using objective electronic adherence monitoring. Br J Dermatol. 2016;176(3):759–764.
    1. Tugwell P, Boers M, Brooks P, Simon L, Strand V, Idzerda L. OMERACT: an international initiative to improve outcome measurement in rheumatology. Trials. 2007;8:38.
    1. Gargon E, Williamson PR, Altman DG, Blazeby JM, Clarke M. The COMET Initiative database: progress and activities from 2011 to 2013. Trials. 2014;15:279.
    1. Chai PR, Carreiro S, Innes BJ, et al. Oxycodone ingestion patterns in acute fracture pain with digital pills. Anesth Analg. 2017;125(6):2105–2112.
    1. Browne SH, Peloquin C, Santillo F, et al. Digitizing medicines for remote capture of oral medication adherence using co‐encapsulation. Clin Pharmacol Ther. 2018;103(3):502–510.

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