Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Apr 21, 2020
Date Accepted: Jul 26, 2020
A Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modelling
ABSTRACT
Background:
mHealth tablet-based interventions are increasingly being studied and deployed in various healthcare settings, yet little knowledge exists regarding patient uptake and acceptance, and how patient demographics influence these important implementation metrics.
Objective:
To analyze implementation of an mHealth tablet questionnaire in primary care, including uptake and successful completion, and factors influencing these metrics.
Methods:
We prospectively studied a patient-facing, waiting room, electronic touch-tablet asthma questionnaire deployed as part of the Electronic Asthma Management System (eAMS). We describe tablet uptake and completion rates and corresponding predictor models for these behaviors.
Results:
The tablet was offered to and accepted by patients (“uptake”) in 891/1715 (52.0%) visits. Patients refused the tablet in 439/1330 (33.0%) visits in which it was successfully offered. Patients aged ≥ 65 years (OR 2.30, 1.33-3.95) and with concurrent chronic obstructive pulmonary disease (COPD) (OR 2.22, 1.05-4.67) were more likely to refuse the tablet, and those on an asthma medication (OR 0.55, 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, 0.32-0.88) being less likely to leave it incomplete.
Conclusions:
Older 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 healthcare settings and diseases, few studies describe their real-world acceptance and its predictors. Our results should be complimented by qualitative methods to identify barriers and enablers to uptake, and may inform technological and implementation strategies to drive successful usage. Clinical Trial: n/a
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