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Development of an algorithm for analysing the electronic measurement of medication adherence in routine HIV care.

Development of an algorithm for analysing the electronic measurement of medication adherence in routine HIV care.
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Rotzinger A, Cavassini M, Bugnon O, Schneider MP,


Rotzinger A, Cavassini M, Bugnon O, Schneider MP, (click to view)

Rotzinger A, Cavassini M, Bugnon O, Schneider MP,

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International journal of clinical pharmacy 2016 7 29()

Abstract

Background Medication adherence is crucial for successful treatment. Various methods exist for measuring adherence, including electronic drug monitoring, pharmacy refills, pill count, and interviews. These methods are not equivalent, and no method can be considered as the gold standard. A combination of methods is therefore recommended. Objective To develop an algorithm for the management of routinely collected adherence data and to compare persistence and implementation curves using post-algorithm data (reconciled data) versus raw electronic drug monitoring data. Setting A community pharmacy located within a university medical outpatient clinic in Lausanne, Switzerland. Methods The algorithm was developed to take advantage of the strengths of each available adherence measurement method, with electronic drug monitoring as a cornerstone to capture the dynamics of patient behaviour, pill count as a complementary objective method to detect any discrepancy between the number of openings measured by electronic monitoring and the number of pills ingested per opening, and annotated interviews to interpret the discrepancy. The algorithm was tested using data from patients taking lopinavir/r and having participated in an adherence-enhancing programme for more than 3 months. Main outcome measure Adherence was calculated as the percentage of persistent patients (persistence) and the proportion of days with correct dosing over time (implementation) from inclusion to the end of the median follow-up period. Results A 10-step algorithm was established. Among 2041 analysed inter-visit periods, 496 (24 %) were classified as inaccurate, among which 372 (75 %) could be reconciled. The average implementation values were 85 % (raw data) and 91 % (reconciled data) (p < 0.0001). At day 544, persistence values were 68 % (raw) and 82 % (reconciled) (p = 0.11), and adherence values were 74 % (raw) and 82 % (reconciled) (p < 0.0001). Conclusion Combining electronic drug monitoring, pill count and patient interviews is possible within the setting of a medication adherence clinic. Electronic drug monitoring underestimates medication adherence, affecting subsequent analysis of routinely collected adherence data. To ensure a set of reliable electronic drug monitoring data, structured and timely electronic drug monitoring management should be reinforced.

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