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Michigan State University Clinical and Translational Sciences Institute

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eCAP Data Integration

Jul 28, 2023

 

By: Jonathan Babbage

Medication adherence can be a difficult variable to reliably determine.   "Self-report medication adherence measures vary substantially in their question phrasing, recall periods, and response items. Self-reports tend to overestimate adherence behavior compared with other assessment methods and generally have high specificity but low sensitivity."[1]  Electronic medication caps allow investigators to track the exact date and times that a medication was opened.

 

CTSI has collaborated with investigators that are studying diabetes management including a subject's medication adherence.  In order to do this, at enrollment, each subject is given an eCAPTM medication container manufactured by Information Mediary.  The cap will track each opening while the subject is part of the study.  The cap is scanned by a research assistant (RA) at each study event and the data are loaded into the manufacturers servers.  

 

We built an integration that will pull all of the adherence data from Information Mediary's servers through an authenticated API, and load the data directly into the study's REDCap project.  This load includes the raw timestamp data for each opening of the subject's medication.  For each interval between clinic visits, the system also calculates a number of days on medication, days adherent, and an adherence rate.  This can be done in real time, so the RA receives feedback about adherence during the visit and can respond according to the study protocol.  Other REDCap features such as alerts, dashboards, and reports can be configured to inform investigators, study staff, or subjects with details about adherence.  

 

This integration is an example of the customizations that CTSI provides investigators on campus.  If you have a study that would benefit from a data integration with a third party service, please contact us.

 

 

References

1. Stirratt MJ, Dunbar-Jacob J, Crane HM, et al. Self-report measures of medication adherence behavior: recommendations on optimal use. Transl Behav Med. 2015;5(4):470-482. doi:10.1007/s13142-015-0315-2

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