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Data for Adherence Decision Support
Simon Diemert, Jens Weber, Morgan Price, Jordan Bannman
75 - 79
10.3233/978-1-61499-951-5-75
Studies in Health Technology and Informatics
Volume 257: Improving Usability, Safety and Patient Outcomes with Health Information Technology
Abstract

Technological interventions aimed at addressing medication non-adherence have shown some promise but do not deliver the full potential of an Internet of Things based Adherence Decision Support (ADS) system due, in part, to a lack high-resolution definition and measure of adherence. This paper presents a novel methodology and pilot study aimed at collecting data to support an AI-based measure of adherence. The pilot study results demonstrate the viability of the methodology and that a full-scale study could provide meaningful data to support to an AI-based ADS system.

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