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

Abstract

Background mHealth 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. Objective To determine which factors influence the uptake and successful completion of an mHealth tablet questionnaire by analyzing its implementation in a primary care setting. Methods We 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. Results The 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. 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 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.

A systematic review on the effectiveness and impact of clinical decision support systems for breathlessness

“…1 ). Many studies were excluded as they report only retrospective validation 22 or was purely for patient use and did not inform clinicians 23 . Majority of the studies ( n = 30) included were RCTs.…”

Primary care asthma surveillance: a review of knowledge translation tools and strategies for quality improvement

“…A limitation of electronic questionnaires is the reliance on patients to accurately self-report symptoms and exacerbations, which introduces recall and other biases that could impact validity [ 21 , 22 ]. Another challenge of implementation is the limited uptake of questionnaires by clinicians and patients who are provided electronic questionnaires [ 23 , 24 ]. Overall, questionnaires have been shown to be effective for improving the diagnosis of asthma by gaining additional insight into patient symptoms and history, however difficulties related to accuracy and uptake of these electronic questionnaires remain.…”

Improving computerized decision support system interventions: a qualitative study combining the theoretical domains framework with the GUIDES Checklist

“…Finally, although the GUIDES calls for ensuring that the quality of patient data inputs is adequate, it does not address identified belief statements pertaining to patient-facing data collection interfaces as part of the CDSS, including: how patient questionnaires might enable time savings in clinical data collection, their effects on patient-provider relationships; how well they are tailored to patient needs; and how they might enable patient prompts for providers to use the CDSS. These factors are equally absent in other CDSS evaluation frameworks, despite the growing use of pre-visit electronic patient questionnaires, which have been shown to be a reliable, acceptable and usable in real-world settings [ 28 ], and present opportunities for patient-mediated knowledge translation [ 29 , 30 ]. As CDSSs continue to evolve to include more patient-reported data, this should be a consideration in CDSS intervention development [ 31 ].…”