Literature DB >> 19780692

A study of medication-taking and unobtrusive, intelligent reminding.

Tamara L Hayes1, Kofi Cobbinah, Terry Dishongh, Jeffrey A Kaye, Janna Kimel, Michael Labhard, Todd Leen, Jay Lundell, Umut Ozertem, Misha Pavel, Matthai Philipose, Kevin Rhodes, Sengul Vurgun.   

Abstract

Poor medication adherence is one of the major causes of illness and of treatment failure in the United States. The objective of this study was to conduct an initial evaluation of a context-aware reminder system, which generated reminders at an opportune time to take the medication. Ten participants aged 65 or older, living alone and managing their own medications, participated in the study. Participants took a low-dose vitamin C tablet twice daily at times that they specified. Participants were considered adherent if they took the vitamin within 90 minutes (before or after) of the prescribed time. Adherence and activity in the home was measured using a system of sensors, including an instrumented pillbox. There were three phases of the study: baseline, in which there was no prompting; time-based, in which there was prompting at the prescribed times for pill-taking; and context-aware, in which participants were only prompted if they forgot to take their pills and were likely able to take their pills. The context-based prompting resulted in significantly better adherence (92.3%) as compared to time-based (73.5%) or no prompting (68.1%) conditions (p < 0.0002, chi(2) = 17.0). In addition, subjects had better adherence in the morning than in the evening. We have shown in this study that a system that generates reminders at an opportune time to take the medication significantly improves adherence. This study indicates that context-aware prompting may provide improved adherence over standard time-based reminders.

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Year:  2009        PMID: 19780692      PMCID: PMC2998278          DOI: 10.1089/tmj.2009.0033

Source DB:  PubMed          Journal:  Telemed J E Health        ISSN: 1530-5627            Impact factor:   3.536


  35 in total

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  19 in total

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8.  Prompting Technology and Persons With Dementia: The Significance of Context and Communication.

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9.  Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications.

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10.  Automated Detection of Activity Transitions for Prompting.

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