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Uncontrolled asthma poses substantial negative personal and health system impacts. Web-based technologies, including smartphones, are novel means to enable evidence-based care and improve patient outcomes.
The aim of this study was to design, develop, and assess the utilization of an asthma collaborative self-management (CSM) platform (
We designed and developed
We enrolled 138 patients with a mean age of 45.3 years to receive the
Individuals with asthma reported good usability and high satisfaction levels, reacted to
ClinicalTrials.gov NCT01964469; https://clinicaltrials.gov/ct2/show/NCT01964469
Asthma is a common chronic disease that poses a serious global health problem. In Canada alone, asthma affects 10.8% of Canadians [
Collaborative self-management (CSM) is defined as “a system of coordinated healthcare interventions and communications for populations with conditions in which self-care efforts are significant” [
Smartphones have become ubiquitous, and mHealth apps have the potential to transform elements of chronic disease management [
We sought to design and develop a multifunctional, CSM mHealth platform for patients with Asthma, based on clinical content from international evidence-based guidelines, following a UCD process and then evaluate its utilization to inform iterative product improvement.
The
Specifications were developed collaboratively with Canada Health Infoway and included (1) a user-centered Web-based asthma self-management platform available on any Web-enabled device including mobile phone browsers and standard Web browsers on laptop, desktop, and tablet to ensure equitable access of the app; (2) patient access to their personal health information and electronic health (eHealth) records through connectivity with TELUS health space, which was a localized version of Microsoft HealthVault (Web-based personal health record developed by Microsoft); (3) alignment with national and provincial clinical and eHealth priorities, as per the Canadian Thoracic Society (CTS), Ontario Lung Association (OLA), eHealth Ontario (a provincial agency tasked with the implementation of Ontario’s public Electronic Health Record System), and the Ontario Ministry of Health and Long-Term Care; and (4) scalability to the provincial level and ability to be leveraged by other jurisdictions within Canada. Evidence-based best practices from the CTS Asthma guidelines [
The utilization data reported in this manuscript are derived from the intervention (
Overall, 2 customized consumer satisfaction questionnaires and the standardized System Usability Scale (SUS) [
The statistics reported in this manuscript are primarily descriptive. We reported counts and percentages for categorical variables as well as means and SDs for continuous variables or pseudocontinuous variables derived as means of multiple ordinal questionnaire items. We used the Wilcoxon rank-sum Test to compare the number of weeks with at least one login during the 52 weeks between groups defined by age, college education, smartphone use, and baseline Asthma Control Test (ACT) score. Age groups were defined as less than 50 years versus aged 50 years and above because it approximately divided the population in half.
Examples of the various features designed for breathe. The first row provides examples of the main home screen, the current zone of control that the patient is in, and environment information. The second row provides examples of the journaling feature where users can report symptoms, medication intake, and review entries. The last row has examples of the desktop version of breathe, where the zone of control review and action plans are displayed. These are not actual plans, medications, or patient data but instead, prototypes of the breathe interface.
The health care provider developed an
The Journal feature allows patients to track daily symptoms, record reliever and controller medication usage, and log peak flow measurements. The historical review feature allows users to look back at previous journal entries and peak flow values entered.
The journal entries feed an integrated asthma control algorithm at the
Data visualization and analysis of several trends, including identified triggers, control zone, and peak flow values, were available to users. An example of the usefulness of this feature is that trigger frequency reported back to patients may enable patient insights into which triggers to avoid in the future.
This feature provides real-time current and forecast of location-specific (based on users’ input about their location) environmental conditions including temperature, humidity index, weather forecast, and the AQHI with specific poor air quality risk-reduction health messaging.
Architecture of the
This feature includes a variety of options including changing default (7:00 pm EST) time and email address to receive emailed medication adherence reminders and setting a location for location-specific environmental information. Email adherence reminders were automatically generated based on predefined rule-based logic including a welcome email,
A total of 344 patients were recruited into the RCT between October 31, 2012, and March 31, 2014, of whom 171 were allocated to the
Usability was evaluated by the SUS, a validated composite measure, which is scored from 0 to 100, with higher scores representing greater usability (
Satisfaction was evaluated using 5-point Likert scale responses, 1-strongly disagree, 3-do not know or neutral, 5-strongly agree. A total of 63.8% (74/116) of patients agreed or strongly agreed that the
The 123 patients in the intervention arm with utilization data accessed
Usability questionnaire.
Usability and user satisfaction of |
Statistics at 12 months | ||
Disagree or strongly disagree | 21 (18.1) | ||
Agree or strongly agree | 74 (63.8) | ||
Disagree or strongly disagree | 30 (25.6) | ||
Agree or strongly agree | 58 (49.6) | ||
Disagree or strongly disagree | 16 (13.9) | ||
Agree or strongly agree | 75 (65.2) | ||
71.1 (19.9) | |||
Ease of use: mean of 7 questions (n=119) | 4.1 (0.9) | ||
Usefulness: mean of 12 questions (n=118) | 3.6 (0.9) | ||
Design of components: mean of 12 questions reported (n=119) | 4.2 (0.7) |
Panel A: Total calculations of zone of control calculations per month of the intervention calculated from enrollment Panel B: Percentage of zone of control calculations per month of the intervention.
Tracking patient log-ins to the platform demonstrated a fall in use within the first 4 weeks of initiation and thereafter a standard decay in usage (
Further utilization analysis demonstrated patterns of use that related to patient behavior,
The post hoc analysis of patient factors that may have influenced utilization including age, education level, smartphone use, and asthma control is presented in
Attrition in breathe use throughout the 12-months of the study, with Eysenbach attrition curve plotted as a reference.
App use tracked by number of logins by time of day exploring the effectiveness of reminders. Note that automatic app reminders are default to send around 7:00 pm.
Sustained effect of email reminders on app use over the 12 months of intervention.
Panel A: Number of reported “good days” (no symptoms) and symptom episodes since enrollment. Panel B: Percentage of reported “good days” (no symptoms) and symptom episodes since enrollment.
Self-reported controller medication use showing the effect of clinic visits (surveillance effect) on self-reporting behavior (clinic visits were scheduled at 6 and 12 months from the beginning of the intervention).
Utilization by patient characteristics, indicating the number of weeks with at least one log-in during a 52-week period.
Group | Weeks (n) | Mean (SD) | |||||
<50 | 73 | 18.2 (17.9) | <.001 | ||||
≥50 | 49 | 30.1 (18.2) | —b | ||||
No | 34 | 21.6 (20.8) | .42 | ||||
Yes | 88 | 23.5 (18.2) | — | ||||
No | 40 | 23.8 (19.7) | .66 | ||||
Yes | 82 | 22.6 (18.6) | — | ||||
<20 | 65 | 22.7 (18.7) | .97 | ||||
≥20 | 57 | 23.2 (19.2) | — |
a
bNot applicable.
Despite a decade of mHealth app development, there remains a limited body of evidence demonstrating improved health outcomes with apps [
Patients had a high level of satisfaction with the individual design components of
The
The goal of UCD is to create and sustain a certain level of adherence to the platform, as adherence is a prerequisite to positive behavioral change and improved health outcomes. Despite good ratings for ease of use and a high degree of satisfaction with the
We considered that decreased utilization (attrition) in this study might have been related to population and design characteristics, including technology savviness, patients with relatively good disease control, infrequent physician monitoring, or because patients achieved their expected outcomes (or the correct
All participants had access to either a smartphone or a computer. Although, 55.2% (76/138) of our population had a smartphone and reported being comfortable or very comfortable with its use, one-third did not have a smartphone and therefore accessed the platform by laptop, desktop, or tablet. We considered that the nonsmartphone subset may have been less technology savvy, contributing to the decline in utilization and particularly may have contributed to the sharp decline in the first 4 weeks. However, our post hoc analysis did not find an association between utilization and having a smartphone.
We considered that younger age and higher education level might have an impact on utilization. We did not find an association between utilization and education level. In a post hoc analysis, we were able to demonstrate that being aged 50 years and above was significantly associated with higher utilization. Although general app use is normally greater in a younger population, we speculate that our participants over the age of 50 with a chronic disease may have had a higher level of concern about their chronic disease and potentially find more value in health-related apps than a younger population. We observed that increased utilization was associated with time of day, anticipated physician visits, and email reminders.
Patients in this study had relatively well controlled asthma as indicated by high baseline ACTs and a high percentage of good days when compared with episode days. We did not have a specific engagement strategy to motivate patients to return to the platform when they were feeling well. Failure to engage the users in moments of disease stability has been described by other authors as a critical factor affecting attrition across diseases [
In this study, patients were evaluated by a physician only twice after enrollment. Infrequent monitoring may have increased the attrition rate. Increased
Patients were satisfied with
Increased
Patterns of usage analysis identified physician visits and email reminders as strongly associated with utilization. A post hoc analysis identified being aged 50 years and above as significantly associated with higher utilization.
The population studied was a convenience sample from primary and specialty clinics with a dedicated asthma program, and at the time of enrollment, patients had relatively good asthma control. As such, patients’ evaluation of the app and their utilization patterns may not be representative of the general asthma population. Since this project was completed, native apps have largely supplanted Web browser–based apps such as
We followed UCD methods to develop
As we iterate development of the
Asthma Control Test
Air Quality Health Index
Canadian Institute for Health Research
collaborative self-management
Canadian Thoracic Society
electronic health
mobile health
Ontario Lung Association
per patient per week
randomized controlled trial
short-acting β-agonist
System Usability Scale
user-centered design
The OLA through investment from the Canada Health Infoway’s Consumer Health Solutions Program and the Ministry of Health and Long-Term Care (Asthma Program) supported the development of
PPM reports grants from the Natural Sciences and Engineering Research Council of Canada (NSERC), Canadian Institute for Health Research (CIHR), MITACS, and Ontario Centres of Excellence (OCE) during the conduct of this study. PPM is a member of advisory boards at Roche Canada. The work developed in this paper was not funded by any of these companies. MSY reports grants from Canada Health Infoway during the conduct of the study. MF, AKT, and CM have nothing to disclose. ASL reports grants from Canada Health Infoway, from Ontario Ministry of Health and Long-Term Care, during the conduct of the study. TT reports grants from Ontario Ministry of Health and Long-Term Care, grants from Ontario Ministry of the Environment and Climate Change, grants from CIHR, grants from Health Canada, grants from Canadian Respiratory Research Network, outside the submitted work. MDL received honoraria from the Astra Zeneca Severe Asthma PRECISION Program, and funds were paid directly to Queen's University for participation in multicenter clinical trials from Astra Zeneca, GlaxoSmithKline, Hoffman LaRoche Ltd, Janssen, and Novartis; grants were paid directly to Queen's University from the OLA, the Government of Ontario's Innovation Fund, Allergen NCE, Canadian Institutes of Health Research; and personal fees were paid by the Public Service Occupational Health Program Regions and Programs Bureau Health Canada or Government of Canada for preparation of a report on pollution exposure at post and the role of surveillance spirometry, outside the submitted work. SG has nothing to disclose. AGD reports that his employer was paid from grants from Canada Health Infoway and The Lung Association to cost recover his time spent on this project. JAC reports grants from Canada Health Infoway during the conduct of the study. CL declares that he is a member of advisory boards or equivalent in commercial organizations as AstraZeneca, Novartis, Boehringer Ingelheim, and GlaxoSmithKline as well as receiving funding from commercial organizations as AstraZeneca, Novartis, Boehringer Ingelheim, Pfizer, and Bayer. The work developed in this project was not funded by any of these companies.