Global Burden of Chronic Obstructive Pulmonary Disease Through 2050.

Importance: Chronic obstructive pulmonary disease (COPD) is a respiratory condition that is associated with significant health and economic burden worldwide. Previous studies assessed the global current-day prevalence of COPD, but to better facilitate resource planning and intervention development, long-term projections are needed. Objective: To assess the global burden of COPD through 2050, considering COPD risk factors. Design, Setting, and Participants: In this modeling study, historical data on COPD prevalence was extracted from a recent meta-analysis on 2019 global COPD prevalence, and 2010 to 2018 historical prevalence was estimated using random-effects meta-analytical models. COPD risk factor data were obtained from the Global Burden of Disease database. Main Outcomes and Measures: To project global COPD prevalence to 2050, generalized additive models were developed, including smoking prevalence, indoor and outdoor air pollution, and development indices as predictors, and stratified by age, sex, and World Bank region. Results: The models estimated that the number of COPD cases globally among those aged 25 years and older will increase by 23% from 2020 to 2050, approaching 600 million patients with COPD globally by 2050. Growth in the burden of COPD was projected to be the largest among women and in low- and middle-income regions. The number of female cases was projected to increase by 47.1% (vs a 9.4% increase for males), and the number of cases in low- and middle-income regions was expected to be more than double that of high-income regions by 2050. Conclusions and Relevance: In this modeling study of future COPD burden, projections indicated that COPD would continue to affect hundreds of millions of people globally, with disproportionate growth among females and in low-middle income regions through 2050. Further research, prevention, and advocacy are needed to address these issues so that adequate preparation and resource allocation can take place.

Prediction of short-acting beta-agonist usage in patients with asthma using temporal-convolutional neural networks.

Objective: Changes in short-acting beta-agonist (SABA) use are an important signal of asthma control and risk of asthma exacerbations. Inhaler sensors passively capture SABA use and may provide longitudinal data to identify at-riskpatients. We evaluate the performance of several ML models in predicting daily SABA use for participants with asthma and determine relevant features for predictive accuracy. Methods: Participants with self-reported asthma enrolled in a digital health platform (Propeller Health, WI), which included a smartphone application and inhaler sensors that collected the date and time of SABA use. Linear regression, random forests, and temporal convolutional networks (TCN) were applied to predict expected SABA puffs/person/day from SABA usage and environmental triggers. The models were compared with a simple baseline model using explained variance (R2), as well as using average precision (AP) and area under the receiving operator characteristic curve (ROC AUC) for predicting days with ≥1-10 puffs. Results: Data included 1.2 million days of data from 13 202 participants. A TCN outperformed other models in predicting puff count (R2 = 0.562) and day-over-day change in puff count (R2 = 0.344). The TCN predicted days with ≥10 puffs with an ROC AUC score of 0.952 and an AP of 0.762 for predicting a day with ≥1 puffs. SABA use over the preceding 7 days had the highest feature importance, with a smaller but meaningful contribution from air pollutant features. Conclusion: Predicted SABA use may serve as a valuable forward-looking signal to inform early clinical intervention and self-management. Further validation with known exacerbation events is needed.

Budget impact analysis of a digital monitoring platform for COPD.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a progressive debilitating condition with frequent exacerbations that have a high burden for patients and society. Digital tools may help to reduce the economic burden for patients and payers by improving outcomes. The Propeller platform is a digital self-management tool that facilitates passive monitoring of inhaler medication utilization, potentially assisting the healthcare team to identify patients at risk of a COPD exacerbation who may require further intervention. This study estimated the budget impact of Propeller from commercial payer and Medicare fee-for-service payer perspectives. METHODS: An Excel-based model was used to estimate the budget impact of Propeller for COPD patients in commercial and Medicare population sizes of 5 million members. Data on prevalence, baseline healthcare resource utilization (HCRU), and baseline use of rescue and controller inhaler medications with unit costs (adjusted to 2020 US dollars) were obtained from peer-reviewed literature. Data on reductions in HCRU during Propeller usage were based on direct evidence. Estimates for costs of remote monitoring were obtained from publicly available information. All patients were assumed to have insurance claims related to ongoing remote monitoring. RESULTS: The estimated number of annual eligible COPD patients for commercial and Medicare was 212,200 and 606,600, respectively. Propeller decreased costs by an estimated $2,475 (commercial) and $915 (Medicare) per enrolled patient. The greatest increase in expenditure was for remote monitoring related expenses. After accounting for estimated reductions in hospitalizations, emergency department visits and short-acting beta-agonist use, total net savings were approximately $1.60 and $1.70 per-member per-month for commercial and Medicare payers, respectively. CONCLUSION: Propeller is projected to be cost saving from both the commercial and Medicare payer perspectives.

Retrospective assessment of a collaborative digital asthma program for Medicaid-enrolled children in southwest Detroit: reductions in short-acting beta-agonist (SABA) medication use.

BACKGROUND: Real-world evidence for digitally-supported asthma programs among Medicaid-enrolled children remains limited. Using data from a collaborative quality improvement program, we evaluated the impact of a digital intervention on asthma inhaler use among children in southwest Detroit. METHODS: Children (6-13 years) enrolled with Kids Health Connection (KHC), a program involving home visits with an asthma educator, were invited to participate in a digital self-management asthma program (Propeller Health). Patients were provided with a sensor to capture short-acting beta-agonist (SABA) medication use, and given access to a paired mobile app to track usage. Patients' healthcare providers and caregivers ("followers") were invited to view data as well. Retrospective paired t-tests assessed change in mean SABA use and SABA-free days (SFD) over time, and regressions explored the relationship between followers and medication use. RESULTS: Fifty-one patients were assessed. Mean program participation was nine months, and patients had on average 3 followers. From the first to last participation month, mean SABA use decreased from 0.68 to 0.25 puffs/day (p < 0.001), and mean SFD increased from 25.2 to 28.1 days/month (p < 0.001). 76% of patients had an increase in the number of SFD. There was a positive, but non-significant, relationship between the number of followers and reductions in SABA inhaler use. CONCLUSIONS: We observed a significant reduction in SABA inhaler use and an increase in the number of SABA-free days among Medicaid-enrolled children enrolled in a multi-modal digital asthma program.

Is Once Versus Twice Daily Dosing Better for Adherence in Asthma and Chronic Obstructive Pulmonary Disease?

BACKGROUND: Patients with asthma and chronic obstructive pulmonary disease (COPD) may be prescribed once- or twice-daily dosing of controller inhalers. OBJECTIVE: To assess differences in controller adherence by dosing schedule and age. METHODS: Electronic medication monitors (EMMs) captured the date and time of inhaler actuations over 90 days in patients using the Propeller Health platform. Prescribed inhaler schedule was self-reported. Once- versus twice-daily schedule comparisons were assessed retrospectively using regressions adjusting for age. RESULTS: A total of 6294 patients with asthma and 1791 patients with COPD were included. On average, once-daily users had significantly higher median (interquartile range [IQR]) daily adherence than twice-daily users (asthma: 63.3 [IQR: 31.1, 86.7]% vs 50.3 [IQR: 21.1, 78.3]%, P < .001; COPD: 83.3 [IQR: 57.2, 95.6]% vs 64.7 [IQR: 32.8, 88.9]%, P < .001). This pattern persisted in all age groups, with the exception of 4- to 17-year-olds in asthma. The lowest adherence was in the young adult population (18- to 29-year-olds). The percentage of patients who achieved ≥80% adherence was significantly higher among once- versus twice-daily users in asthma (34.3% vs 23.6%, P < .001) and COPD (54.8% vs 38.6%, P < .001). The adjusted odds of once- versus twice-daily users achieving ≥80% adherence was 1.36 (95% confidence interval: 1.19-1.56, P < .001) in asthma and 1.73 (95% confidence interval: 1.38-2.17, P < .001) in COPD. Most once-daily patients with COPD took their medication in the morning versus at night; there was no difference in morning versus afternoon/evening administration in all other asthma and COPD groups. CONCLUSION: Patients with asthma and COPD who were prescribed once-daily versus twice-daily medications were more likely to adhere to their inhalers. Patients with COPD had higher adherence than those with asthma, possibly reflecting, in part, the older cohort age. The effect of greater adherence on exacerbations is a topic for future analysis.

Medication Adherence and Asthma Control with Once-Daily Indacaterol/Glycopyrronium/Mometasone Furoate Breezhaler Digital Companion: 90-Day Analysis from Germany.

INTRODUCTION: Suboptimal adherence to inhaled asthma therapy is associated with poor clinical outcomes. Digital companion paired inhaler devices record medication use and provide reminders, thereby improving treatment adherence and asthma outcomes. This analysis assessed the impact of indacaterol/glycopyrronium/mometasone furoate (IND/GLY/MF) Breezhaler® digital companion on medication adherence and symptom control in adults with asthma from Germany. METHODS: This retrospective analysis included adults (≥ 18 years) with asthma and prescribed Breezhaler digital companion. Assessments included: mean medication adherence (number of puffs taken/prescribed × 100) and change in Asthma Control Test (ACT) scores [well controlled (≥ 20), not well controlled (15-20) and poorly controlled (≤ 15)] at 1 month after the first ACT (second ACT). The percent of patients with ≥ 80% medication adherence (days 16-30 and 76-90) and the change in ACT (baseline and ≥ 30 days) were analysed. RESULTS: Of the 163 patients with 90 days data, ≥ 80% medication adherence was achieved in 82.8% and 72.4% of patients at months 1 and 3, respectively. Change in asthma control was examined in ~ 60% (n = 97) of patients who completed ≥ 2 ACTs through the application. At baseline, 33.0% of patients were well controlled and 53.6% were well controlled at second ACT. Furthermore, 43.3% patients reported very poor control at baseline which decreased to 22.7% at second ACT. CONCLUSION: The use of IND/GLY/MF (Breezhaler) with a digital companion (sensor + application) may be associated with improved symptom control and high level of controller medication adherence in patients with asthma.

Improvement in symptom-related disruptions is associated with fewer days of short-acting beta-agonist use in asthma.

Significant indirect healthcare costs are related to uncontrolled asthma, including productivity loss. Days with short-acting beta-agonist (SABA) use is associated with symptom-related disruptions at work, home, and school. Digital self-management platforms may support fewer days with SABA medication use and may reduce symptom-related disruptions.

Training the next generation of behavioral medicine scientists to accelerate digital health.

We trace the evolution of digital health industry careers for behavioral medicine specialists. We discuss the current misalignment of career opportunities in the private sector with the predominant graduate education training model that emphasizes the pursuit of academic positions. We describe the potential risks to the profession and public health if the field does not adapt professional training models to be inclusive of private sector industry roles. Finally, we offer a series of recommendations aimed at trainees, faculty advisors, and training programs to better prepare trainees for meaningful careers in industry.

This commentary focuses on the career paths available for behavioral medicine scientists in the private sector digital health industry. Although this field has exciting and impactful career options, graduate training models have been slow to adapt to prepare graduates for these opportunities. We describe many actionable steps that trainees, advisors, and graduate programs can take to help training programs to evolve to prepare graduate for more diverse career paths.

Perceptions of Environmental Influence and Environmental Information-Seeking Behavior Among People With Asthma and COPD.

Environmental exposures and socioeconomic status (SES) are associated with asthma and chronic obstructive pulmonary disease (COPD) morbidity and mortality. Despite efforts to reduce the impact of environmental exposures through regulation and education, knowledge gaps remain. We sought to understand how adults with asthma and COPD perceive and seek information about environmental factors, and how these responses varied by disease or socioeconomic characteristics. Participants with self-reported asthma or COPD enrolled in a digital platform for respiratory disease self-management, consisting of sensors to track medication use and a companion smartphone app, completed an electronic survey exploring perceptions of environmental factors. Using mixed-method analyses, we evaluated differences in responses by disease (asthma vs. COPD), education (≤ vs. > some college), annual household income (< vs. ≥ $50,000), and mean annual residential air pollutant exposure (> vs. ≤80th percentile). Survey responses from 698 participants [500 asthma (72%) and 198 COPD (28%)] were analyzed. A high percentage of participants perceived that environmental factors could influence their symptoms, including: pollen (93% for asthma vs. 86% for COPD), mold (89 vs. 85%), second-hand smoke (89 vs. 83%), and air pollution (84% for both). Participants reported seeking environmental information daily from an average of three sources, preferring mobile apps and television (TV) programs. Significant differences were identified by disease. Conclusion: Participants with asthma and COPD perceive a relationship between their respiratory symptoms and their environment and regularly seek out environmental information. This information can help inform digital health development for respiratory education and self-management.

Identifying impacts of air pollution on subacute asthma symptoms using digital medication sensors.

BACKGROUND: Objective tracking of asthma medication use and exposure in real-time and space has not been feasible previously. Exposure assessments have typically been tied to residential locations, which ignore exposure within patterns of daily activities. METHODS: We investigated the associations of exposure to multiple air pollutants, derived from nearest air quality monitors, with space-time asthma rescue inhaler use captured by digital sensors, in Jefferson County, Kentucky. A generalized linear mixed model, capable of accounting for repeated measures, over-dispersion and excessive zeros, was used in our analysis. A secondary analysis was done through the random forest machine learning technique. RESULTS: The 1039 participants enrolled were 63.4% female, 77.3% adult (>18) and 46.8% White. Digital sensors monitored the time and location of over 286 980 asthma rescue medication uses and associated air pollution exposures over 193 697 patient-days, creating a rich spatiotemporal dataset of over 10 905 240 data elements. In the generalized linear mixed model, an interquartile range (IQR) increase in pollutant exposure was associated with a mean rescue medication use increase per person per day of 0.201 [95% confidence interval (CI): 0.189-0.214], 0.153 (95% CI: 0.136-0.171), 0.131 (95% CI: 0.115-0.147) and 0.113 (95% CI: 0.097-0.129), for sulphur dioxide (SO2), nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3), respectively. Similar effect sizes were identified with the random forest model. Time-lagged exposure effects of 0-3 days were observed. CONCLUSIONS: Daily exposure to multiple pollutants was associated with increases in daily asthma rescue medication use for same day and lagged exposures up to 3 days. Associations were consistent when evaluated with the random forest modelling approach.

Electronic medication monitoring versus self-reported use of inhaled corticosteroids and short-acting beta2-agonists in uncontrolled asthma.

OBJECTIVE: Current standard of care, patient self-report and clinician estimation, overestimates true inhaled corticosteroids (ICS) adherence. We compare self-reported inhaled ICS and short-acting beta 2-agonists (SABA) use with objective data from electronic medication monitors (EMMs). METHODS: Adults with uncontrolled asthma and prescribed ICS and SABA were enrolled. At visit one, participants' ICS and SABA inhalers were fitted with EMMs to track real-time medication usage over 14 days. Participants were asked to complete paper diaries to self-report medication usage over the same period. Participant self-report of ICS adherence and SABA use versus objective ICS adherence and SABA use was compared using Wilcoxon signed-rank tests. RESULTS: One hundred participants (80% female, mean age 48.5 years, 60% completed college, 80% privately insured) had complete data. Participant self-report (median (IQR): 0.8 (0.0, 2.0)) was greater than objectively measured (median (IQR): 0.43 (0.1, 2.1)) SABA use, but the difference was not statistically significant (P = 0.64). Participant self-report (median (IQR): 97 (67, 100)) was significantly greater than objectively measured (median (IQR): 75 (54, 93)) ICS adherence (P = 0.002). CONCLUSIONS: Significant discrepancies between self-report and objective ICS usage were observed. EMM can provide clinicians with accurate data on ICS medication taking behavior, thus reducing medication regimen complexity, side effects, and costs.

The relationship between objective app engagement and medication adherence in asthma and COPD: a retrospective analysis.

Digital health tools can promote disease self-management, but the association of smartphone app engagement and medication adherence is unclear. We assessed the relationship between objective smartphone app engagement and controller medication use in adults with asthma and COPD. We retrospectively analyzed data from participants enrolled in a digital self-management platform for asthma and COPD. Eligible adults had a smartphone and a paired electronic medication monitor (EMM). Longitudinal, mixed-effects logistic regressions estimated the relationship between daily app engagement (app opens, session duration) and daily controller medication use. Data from 2309 participants (71% asthma; 29% COPD) was analyzed. Opening the app (vs. not opening the app) was associated with significantly greater odds (OR (95% CI)) of using controller medications in asthma (2.08 (1.98, 2.19)) and COPD (1.61 (1.49, 1.75). Longer session duration was also associated with greater odds of using controller medications in asthma and COPD, but the odds of use attenuated with longer session duration in COPD. This study presents a novel assessment of the relationship between objectively-measured smartphone app engagement and controller medication use in asthma and COPD. Such insights may help develop targeted digital health tools and interventions.

Concurrent Improvement Observed in Patient-Reported Burden and Sensor-Collected Medication Use Among Patients Enrolled in a COPD Digital Health Program.

Background: The COPD assessment test (CAT) is an 8-item questionnaire widely used in clinical practice to assess patient burden of disease. Digital health platforms that leverage electronic medication monitors (EMMs) are used to track the time and date of maintenance and short-acting beta-agonist (SABA) inhaler medication use and record patient-reported outcomes. The study examined changes in CAT and SABA inhaler use in COPD to determine whether passively collected SABA and CAT scores changed in a parallel manner. Methods: Patients with self-reported COPD enrolled in a digital health program, which provided EMMs to track SABA and maintenance inhaler use, and a companion smartphone application ("app") to provide medication feedback and reminders. Patients completing the CAT questionnaire in the app at enrollment and at 6 months were included in the analysis. Changes in CAT burden category [by the minimally important difference (MID)] and changes in EMM-recorded mean SABA inhaler use per day were quantified at baseline and 6 months. Results: The analysis included 611 patients. At 6 months, mean CAT improved by -0.9 (95% CI: -1.4, -0.4; p < 0.001) points, and mean SABA use decreased by -0.6 (-0.8, -0.4; p < 0.001) puffs/day. Among patients with higher burden (CAT ≥ 21) at enrollment, CAT improved by -2.0 (-2.6, -1.4; p < 0.001) points, and SABA use decreased by -0.8 (-1.1, -0.6; p < 0.001) puffs/day. Conclusion: Significant and parallel improvement in CAT scores and SABA use at 6 months were noted among patients enrolled in a digital health program, with greater improvement for patients with higher disease burden.

Pilot Study of a Patient Experience with an ELLIPTA Inhaler Electronic Medication Monitor and Associated Integrated System: A Prospective Observational Study Using the COPD Patient-Powered Research Network.

BACKGROUND: Electronic medication monitors (EMMs) are associated with decreased rescue inhaler use, symptom burden, and increased medication adherence in asthma. However, the use of EMMs in people with chronic obstructive pulmonary disease (COPD) using the ELLIPTA dry powder inhaler has not been studied. METHODS: This was an open-label, single-arm, prospective observational study of EMMs and associated application (app) use over 12 weeks and up to 24 weeks (April-October 2019) in people with self-reported COPD aged ≥40 years enrolled in the COPD Patient-Powered Research Network, using an ELLIPTA inhaler. The primary outcome was daily active use of the app over 12 weeks. Treatment adherence, rescue inhaler use, and participant satisfaction were assessed over the same period. RESULTS: Among the 122 participants, mean (standard deviation [SD]) proportion of days participants opened the app was 59.5% (31.4), 51.1% (33.5) and 41.3% (34.2) for Days 1-30, 31-60 and 61-90, respectively. Mean (SD) adherence to maintenance medication remained stable: 80.2% (22.7) and 79.9% (26.7) for Days 1-30 and 61-90, respectively. In participants using a rescue inhaler and EMM, mean (SD) rescue-free days increased from 18.5 (10.0; Days 1-30, n=51) to 21.4 (9.6; Days 61-90, n=48). Participants reported high levels of confidence in using the EMM, valued app reminders highly and reported high system satisfaction (mean [SD] scale: 1=low, 5=high; 4.6 [1.1], 4.3 [1.1] and 4.1 [1.1], respectively). CONCLUSIONS: Use of an ELLIPTA EMM with frequent app engagement, high participant satisfaction and decreased rescue medication use may aid COPD management.

Defining Optimal Medication Adherence for Persistent Asthma and COPD.

Adherence to prescribed medications for chronic respiratory disease is considered a keystone for successful management. There is little consensus, though, on how to measure adherence, what is optimal adherence, or the goals of appropriate medication utilization. These criteria may differ when studying medication utilization at the patient or population level. The role of consistent medication use in chronic respiratory disease is associated with better outcomes. Shared decision-making is one strategy to achieve appropriate levels of adherence that requires negotiation, compromise by both patient and provider. It also recognizes that both success and failure to achieve goals of adherence are shared. As such, we discuss the current understanding of adherence measures in respiratory disease and identify the need for more nuanced approaches to evaluate adherence to reach acceptable patient outcomes.

Assessing asthma control: comparison of electronic-recorded short-acting beta-agonist rescue use and self-reported use utilizing the asthma control test.

Background: Question 4 (Q4) of the Asthma Control Test (ACT) asks patients to report their SABA use over the prior 4 weeks, a criterion for evaluating the impairment domain of asthma control. Biases in recall may lead to a misclassification of asthma control and has implications for asthma control determination and management strategies.Objective: To correlate objective electronic-recorded short-acting beta-agonist (SABA) use with self-reported use via Q4 of the ACT.Methods: Patients ≥18 years of age with a self-reported diagnosis of asthma were enrolled in a digital health electronic medication monitoring (EMM) platform, which recorded the date and time of SABA actuations and prompted the completion of the ACT. The correlations between ACT Q4 responses and EMM-recorded SABA use were evaluated using Spearman's rank correlation coefficients.Results: 1,062 patients (mean age: 35.4 years, mean ACT: 16.3) were included in analyses. Higher Q4 scores, indicating lower SABA use, were moderately and negatively correlated with EMM-recorded SABA use (ρ = -0.59 [95% CI: -0.63, -0.54]). Thirty-five percent of patients underreported SABA use when comparing Q4 to EMM-recorded SABA use.Conclusions: While ACT Q4 and EMM-recorded use were moderately correlated, underreported SABA use on the ACT highlights the need for objective measures of SABA use in asthma control assessments. The use of EMM-recorded SABA data has the potential for clinicians to more accurately determine asthma control, guide changes to controller therapy, and estimate imminent exacerbation risk.

The Impact of Patient Self-Monitoring Via Electronic Medication Monitor and Mobile App Plus Remote Clinician Feedback on Adherence to Inhaled Corticosteroids: A Randomized Controlled Trial.

BACKGROUND: Poor adherence to inhaled corticosteroids (ICSs) and overuse of short-acting beta2-agonists (SABAs) are associated with increased asthma morbidity. OBJECTIVE: To assess whether patient self-monitoring via electronic medication monitoring and smartphone application plus remote clinician feedback influences ICS and SABA use. METHODS: Adults with uncontrolled asthma and prescribed ICS and SABA were enrolled in this 14-week study. Inhalers were fitted with electronic medication monitoring to track real-time usage. After a 14-day baseline, participants were randomly assigned to the treatment group where they received reminders and feedback on ICS and SABA use via a smartphone application and clinician phone calls, or control group without feedback. Linear mixed models compared the baseline percentage of SABA-free days and ICS adherence to the last 14 study days. RESULTS: Participants (n = 100) had a mean age of 48.5 years, 80% were female, 68% white, and 80% privately insured. The percentage of SABA-free days increased significantly in the treatment group (19%; 95% CI, 12 to 26; P < .01) and nonsignificantly in the control group (6%, 95% CI, -3 to 16; P = .18), representing a 13% (95% CI, 1-26; P = .04) difference. ICS adherence changed minimally in the treatment group (-2%; 95% CI, -7 to 3; P = .40), but decreased significantly (-17%; 95% CI, -26 to -8; P < .01) in the control group, representing a 15% (95% CI, 4 to 25; P < .01) difference. CONCLUSIONS: Patient self-monitoring via a digital platform plus remote clinician feedback maintained high baseline ICS adherence and decreased SABA use.