Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling

BackgroundmHealth tablet-based interventions are increasingly being studied and deployed in various health care settings, yet little knowledge exists regarding patient uptake and acceptance or how patient demographics influence these important implementation metrics....

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Main Authors: Kouri, Andrew, Yamada, Janet, Sale, Joanna E M, Straus, Sharon E, Gupta, Samir
Format: Article
Language:English
Published: JMIR Publications 2020-09-01
Series:Journal of Medical Internet Research
Online Access:http://www.jmir.org/2020/9/e19358/
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spelling doaj-68b26e0e864c4e9c8ec89aac317266da2021-04-02T18:56:47ZengJMIR PublicationsJournal of Medical Internet Research1438-88712020-09-01229e1935810.2196/19358Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor ModelingKouri, AndrewYamada, JanetSale, Joanna E MStraus, Sharon EGupta, Samir BackgroundmHealth tablet-based interventions are increasingly being studied and deployed in various health care settings, yet little knowledge exists regarding patient uptake and acceptance or how patient demographics influence these important implementation metrics. ObjectiveTo determine which factors influence the uptake and successful completion of an mHealth tablet questionnaire by analyzing its implementation in a primary care setting. MethodsWe prospectively studied a patient-facing electronic touch-tablet asthma questionnaire deployed as part of the Electronic Asthma Management System. We describe tablet uptake and completion rates and corresponding predictor models for these behaviors. ResultsThe tablet was offered to and accepted by patients in 891/1715 (52.0%) visits. Patients refused the tablet in 33.0% (439/1330) visits in which it was successfully offered. Patients aged older than 65 years of age (odds ratio [OR] 2.30, 95% CI 1.33-3.95) and with concurrent chronic obstructive pulmonary disease (OR 2.22, 95% CI 1.05-4.67) were more likely to refuse the tablet, and those on an asthma medication (OR 0.55, 95% CI 0.30-0.99) were less likely to refuse it. Once accepted, the questionnaire was completed in 784/891 (88.0%) instances, with those on an asthma medication (OR 0.53, 95% CI 0.32-0.88) being less likely to leave it incomplete. ConclusionsOlder age predicted initial tablet refusal but not tablet questionnaire completion, suggesting that perceptions of mHealth among older adults may negatively impact uptake, independent of usability. The influence of being on an asthma medication suggests that disease severity may also mediate mHealth acceptance. Although use of mHealth questionnaires is growing rapidly across health care settings and diseases, few studies describe their real-world acceptance and its predictors. Our results should be complemented by qualitative methods to identify barriers and enablers to uptake and may inform technological and implementation strategies to drive successful usage.http://www.jmir.org/2020/9/e19358/
collection DOAJ
language English
format Article
sources DOAJ
author Kouri, Andrew
Yamada, Janet
Sale, Joanna E M
Straus, Sharon E
Gupta, Samir
spellingShingle Kouri, Andrew
Yamada, Janet
Sale, Joanna E M
Straus, Sharon E
Gupta, Samir
Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling
Journal of Medical Internet Research
author_facet Kouri, Andrew
Yamada, Janet
Sale, Joanna E M
Straus, Sharon E
Gupta, Samir
author_sort Kouri, Andrew
title Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling
title_short Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling
title_full Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling
title_fullStr Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling
title_full_unstemmed Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling
title_sort primary care pre-visit electronic patient questionnaire for asthma: uptake analysis and predictor modeling
publisher JMIR Publications
series Journal of Medical Internet Research
issn 1438-8871
publishDate 2020-09-01
description BackgroundmHealth tablet-based interventions are increasingly being studied and deployed in various health care settings, yet little knowledge exists regarding patient uptake and acceptance or how patient demographics influence these important implementation metrics. ObjectiveTo determine which factors influence the uptake and successful completion of an mHealth tablet questionnaire by analyzing its implementation in a primary care setting. MethodsWe prospectively studied a patient-facing electronic touch-tablet asthma questionnaire deployed as part of the Electronic Asthma Management System. We describe tablet uptake and completion rates and corresponding predictor models for these behaviors. ResultsThe tablet was offered to and accepted by patients in 891/1715 (52.0%) visits. Patients refused the tablet in 33.0% (439/1330) visits in which it was successfully offered. Patients aged older than 65 years of age (odds ratio [OR] 2.30, 95% CI 1.33-3.95) and with concurrent chronic obstructive pulmonary disease (OR 2.22, 95% CI 1.05-4.67) were more likely to refuse the tablet, and those on an asthma medication (OR 0.55, 95% CI 0.30-0.99) were less likely to refuse it. Once accepted, the questionnaire was completed in 784/891 (88.0%) instances, with those on an asthma medication (OR 0.53, 95% CI 0.32-0.88) being less likely to leave it incomplete. ConclusionsOlder age predicted initial tablet refusal but not tablet questionnaire completion, suggesting that perceptions of mHealth among older adults may negatively impact uptake, independent of usability. The influence of being on an asthma medication suggests that disease severity may also mediate mHealth acceptance. Although use of mHealth questionnaires is growing rapidly across health care settings and diseases, few studies describe their real-world acceptance and its predictors. Our results should be complemented by qualitative methods to identify barriers and enablers to uptake and may inform technological and implementation strategies to drive successful usage.
url http://www.jmir.org/2020/9/e19358/
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