Andrew Kouri

Background: Computerized clinical decision support systems (CDSSs) can improve care by bridging knowledge to practice gaps. However, the real-world uptake of such systems in health care settings has been suboptimal. We sought to: (1) use the Theoretical Domains Framework (TDF) to identify determinants (barriers/enablers) of uptake of the Electronic Asthma Management System (eAMS) CDSS; (2) match identified TDF belief statements to elements in the Guideline Implementation with Decision Support (GUIDES) Checklist; and (3) explore the relationship between the TDF and GUIDES frameworks and the usefulness of this sequential approach for identifying opportunities to improve CDSS uptake. Methods: In Phase 1, we conducted semistructured interviews with primary care physicians in Toronto, Canada regarding the uptake of the eAMS CDSS. Using content analysis, two coders independently analyzed interview transcripts guided by the TDF to generate themes representing barriers and enablers to CDSS uptake. In Phase 2, the same reviewers independently mapped each belief statement to a GUIDES domain and factor. We calculated the proportion of TDF belief statements that linked to each GUIDES domain and the proportion of TDF domains that linked to GUIDES factors (and vice-versa) and domains. Results: We interviewed 10 participants before data saturation. In Phase 1, we identified 53 belief statements covering 12 TDF domains; 18 (34.0%) were barriers, and 35 (66.0%) were enablers. In Phase 2, 41 statements (77.4%) linked to at least one GUIDES factor, while 12 (22.6%) did not link to any specific factor. The GUIDES Context Domain was linked to the largest number of belief statements (19/53; 35.8%). Each TDF domain linked to one or more GUIDES factor, with 6 TDF domains linking to more than 1 factor and 8 TDF domains linking to more than 1 GUIDES domain. Conclusions: The TDF provides unique insights into barriers and enablers to CDSS uptake, which can then be mapped to GUIDES domains and factors to identify required changes to CDSS context, content, and system. This can be followed by conventional mapping of TDF domains to behaviour change techniques to optimize CDSS implementation. This novel step-wise approach combines two established frameworks to optimize CDSS interventions, and requires prospective validation.

Background: The use of mobile health (mHealth) in asthma and chronic obstructive pulmonary disease (COPD) is growing, and as the population ages, a greater number of older adults stand to benefit from mHealth-enhanced airway disease care. Though older adults are a heterogeneous population of health technology users, older age represents a potential barrier to health technology adoption, and there is currently a lack of knowledge on how older age influences mHealth use in asthma and COPD. Objective: In this qualitative study, we sought to explore the experiences and perspectives of adults who were aged 65 years and older with asthma and COPD toward mHealth use. Methods: Semistructured individual interviews were conducted with adults who were aged 65 years and older with asthma or COPD and owned a smartphone. Applying phenomenological methodology, we analyzed interview transcripts in order to develop themes and propose an essential experience of mHealth use among older adults with airway disease. We then summarized our qualitative findings and proposed strategies to leverage our results in order to guide future research and implementation efforts targeting older adults’ use of airway mHealth. Results: Twenty participants (mean age 79.8, SD 4.4 years) were interviewed. Participants described a central tension between (1) the perception that mHealth could help maintain independence throughout aging and (2) an apprehension toward the ways in which mHealth could negatively affect established health care experiences. Several elements of these 2 themes are absent from previous research focusing on younger adults with asthma and COPD. The individual elements of these 2 themes informed potential strategies to optimize future older adults’ use of asthma and COPD mHealth tools. Conclusions: Focusing on the perspectives and experiences of older adults with asthma and COPD in their use of mHealth identified novel understandings of health technology use in this important demographic in need of greater care. These lessons were translated into potential strategies that will need to be objectively evaluated in future airway mHealth research, development, and implementation efforts.

BACKGROUND The use of mobile health (mHealth) in asthma and chronic obstructive pulmonary disease (COPD) is growing, and as the population ages, a greater number of older adults stand to benefit from mHealth-enhanced airway disease care. Though older adults are a heterogeneous population of health technology users, older age represents a potential barrier to health technology adoption, and there is currently a lack of knowledge on how older age influences mHealth use in asthma and COPD. OBJECTIVE In this qualitative study, we sought to explore the experiences and perspectives of adults who were aged 65 years and older with asthma and COPD toward mHealth use. METHODS Semistructured individual interviews were conducted with adults who were aged 65 years and older with asthma or COPD and owned a smartphone. Applying phenomenological methodology, we analyzed interview transcripts in order to develop themes and propose an essential experience of mHealth use among older adults with airway disease. We then summarized our qualitative findings and proposed strategies to leverage our results in order to guide future research and implementation efforts targeting older adults’ use of airway mHealth. RESULTS Twenty participants (mean age 79.8, SD 4.4 years) were interviewed. Participants described a central tension between (1) the perception that mHealth could help maintain independence throughout aging and (2) an apprehension toward the ways in which mHealth could negatively affect established health care experiences. Several elements of these 2 themes are absent from previous research focusing on younger adults with asthma and COPD. The individual elements of these 2 themes informed potential strategies to optimize future older adults’ use of asthma and COPD mHealth tools. CONCLUSIONS Focusing on the perspectives and experiences of older adults with asthma and COPD in their use of mHealth identified novel understandings of health technology use in this important demographic in need of greater care. These lessons were translated into potential strategies that will need to be objectively evaluated in future airway mHealth research, development, and implementation efforts.

Background: Computerized clinical decision support systems (CDSSs) are a promising knowledge translation tool, but often fail to meaningfully influence the outcomes they target. Low CDSS provider uptake is a potential contributor to this problem but has not been systematically studied. The objective of this systematic review and meta-regression was to determine reported CDSS uptake and identify which CDSS features may influence uptake. Methods: Medline, Embase, CINAHL, and the Cochrane Database of Controlled Trials were searched from January 2000 to August 2020. Randomized, non-randomized, and quasi-experimental trials reporting CDSS uptake in any patient population or setting were included. The main outcome extracted was CDSS uptake, reported as a raw proportion, and representing the number of times the CDSS was used or accessed over the total number of times it could have been interacted with. We also extracted context, content, system, and implementation features that might influence uptake, for each CDSS. Overall weighted uptake was calculated using random-effects meta-analysis and determinants of uptake were investigated using multivariable meta-regression. Results: Among 7995 citations screened, 55 studies involving 373,608 patients and 3607 providers met full inclusion criteria. Meta-analysis revealed that overall CDSS uptake was 34.2% (95% CI 23.2 to 47.1%). Uptake was only reported in 12.4% of studies that otherwise met inclusion criteria. Multivariable meta-regression revealed the following factors significantly associated with uptake: (1) formally evaluating the availability and quality of the patient data needed to inform CDSS advice; and (2) identifying and addressing other barriers to the behaviour change targeted by the CDSS. Conclusions and relevance: System uptake was seldom reported in CDSS trials. When reported, uptake was low. This represents a major and potentially modifiable barrier to overall CDSS effectiveness. We found that features relating to CDSS context and implementation strategy best predicted uptake. Future studies should measure the impact of addressing these features as part of the CDSS implementation strategy. Uptake reporting must also become standard in future studies reporting CDSS intervention effects. Registration: Pre-registered on PROSPERO, CRD42018092337

Background: Electronic patient questionnaires are becoming ubiquitous in health care. To address care gaps that contribute to poor asthma management, we developed the Electronic Asthma Management System, which includes a previsit electronic patient questionnaire linked to a computerized clinical decision support system. Objective: This study aims to identify the determinants (barriers and enablers) of patient uptake and completion of a previsit mobile health questionnaire. Methods: We conducted semistructured interviews with adult patients with asthma in Toronto, Canada. After demonstrating the questionnaire, participants completed the questionnaire using their smartphones and were then interviewed regarding perceived barriers and enablers to using and completing the questionnaire. Interview questions were based on the Theoretical Domains Framework to identify the determinants of health-related behavior. We generated themes that addressed the enablers and barriers to the uptake and completion of the questionnaire. Results: In total, 12 participants were interviewed for saturation. Key enablers were as follows: the questionnaire was easy to complete without additional knowledge or skills and was perceived as a priority and responsibility for patients, use could lead to more efficient and personalized care, completion on one’s own time would be convenient, and uptake and completion could be optimized through patient reminders. Concerns about data security, the usefulness of questionnaire data, the stress of completing it accurately and on time, competing priorities, and preferences to complete the questionnaire on other devices were the main barriers. Conclusions: The barriers and enablers identified by patients should be addressed by developing implementation strategies to enhance e-questionnaire use and completion by patients. As the use of e-questionnaires grows, our findings will contribute to implementation efforts across settings and diseases.

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.

BACKGROUND Electronic patient questionnaires are becoming ubiquitous in health care. To address care gaps that contribute to poor asthma management, we developed the Electronic Asthma Management System, which includes a previsit electronic patient questionnaire linked to a computerized clinical decision support system. OBJECTIVE This study aims to identify the determinants (barriers and enablers) of patient uptake and completion of a previsit mobile health questionnaire. METHODS We conducted semistructured interviews with adult patients with asthma in Toronto, Canada. After demonstrating the questionnaire, participants completed the questionnaire using their smartphones and were then interviewed regarding perceived barriers and enablers to using and completing the questionnaire. Interview questions were based on the Theoretical Domains Framework to identify the determinants of health-related behavior. We generated themes that addressed the enablers and barriers to the uptake and completion of the questionnaire. RESULTS In total, 12 participants were interviewed for saturation. Key enablers were as follows: the questionnaire was easy to complete without additional knowledge or skills and was perceived as a priority and responsibility for patients, use could lead to more efficient and personalized care, completion on one’s own time would be convenient, and uptake and completion could be optimized through patient reminders. Concerns about data security, the usefulness of questionnaire data, the stress of completing it accurately and on time, competing priorities, and preferences to complete the questionnaire on other devices were the main barriers. CONCLUSIONS The barriers and enablers identified by patients should be addressed by developing implementation strategies to enhance e-questionnaire use and completion by patients. As the use of e-questionnaires grows, our findings will contribute to implementation efforts across settings and diseases.

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.