Table 6.
Study details and results from all identified studies of Propeller (adherence, clinical outcomes, and health care resources use)
| Study name | Study objective | Study design | Indication | Sample size | Follow-up period | Key results |
|---|---|---|---|---|---|---|
| Barrett et al (2018)63 | To evaluate the extent to which digital health intervention improves asthma outcomes in a real-world setting | Prospective, single-arm | Asthma | 497 | 12 months | • Patient mean age was 38 years (range 4–90 years) and 80% were adults • At 12 months of follow-up, there was a 78% reduction in SABA use, an 84% reduction in night-time SABA use, and a 48% improvement in symptom-free days from baseline to month 12 (P<0.0001) • The number of symptom-free days increased from 62% (first week) to 83% (2 months), to 88% (6 months), and to 90% (12 months) (P<0.0001) |
| Carl et al (2018)64 | To determine whether a quality improvement program employing a digital health platform could improve pediatric asthma outcomes | Prospective, single-arm | Asthma | 82 | 12 months | • Patient age varied from 4 to 18 years • Aggregate average controller adherence at 1, 2, 3, and 6 months post-enrollment timepoints demonstrated rates of 58%, 64%, 62%, and 55%, respectively • Average weekly rescue event rate at these time points demonstrated decreased events from baseline (0.597/week) to 0.21 (63%), 0.20 (69%), 0.25 (59%), and (75%), respectively |
| Chen et al (2017)62 | To assess the feasibility and clinical impact of a digital health intervention in a Medicare population with COPD or asthma | Prospective, single-arm | Asthma or COPD | 236 (198 COPD, 38 asthma) | 6 months | • Among asthma patients: • 65% of patients were 60 years or older • At 6 months, SABA use decreased from 1.15 (first week) to 0.56 uses/person/day (last week); significant decrease of 51.4% (P<0.05) • Increase in symptom-free days was 28% (46% at first week to 59% at last week) • Among COPD patients: • 78% of patients were 60 years or older • At 6 months, SABA use decreased from 1.53 (first week) to 0.74 uses/person/day (last week); significant decrease of 51.7% (P<0.01) |
| Hoch et al (2017)65 | To evaluate the feasibility of Propeller Health monitoring device, along with clinical outcomes | Prospective, single-arm | Asthma | 25 | 3 months | • Patient age varied from 6 to 17 years • Average weekly adherence ranged from 76% (week 1) to 36% (week 12). The overall average weekly adherence for the cohort was 56% (SD 12%) • Significant decrease in the rate of rescue medication; 76% (week 1) of study vs 40% (week 12) (P=0.012) • Average weekly number of rescue medications declined from 9.9±14 (week 1) to 2.4±5.2 (week 12) • There was no difference in the rate of night-time events between week 1 and week 12 of the study (P=0.727) • Average number of asthma-free days increased from 4.8 days (±2.2) to 6 days (±1.6) • FEV1 and FVC increased during the study period; however, the difference did not reach significance. FEF25–75 increased from an average of 80% predicted to 84% predicted (P=0.02) |
| Kenyon et al (2018)66 | To assess the feasibility of a mobile health, ICS adherence reminder intervention and to characterize adherence trajectories immediately following severe asthma exacerbation in high-risk urban children with persistent asthma | RCT | Asthma | 41 | 30 days | • Patient age (mean ± SD) was 5.9±2.1 years • Electronic monitoring of ICS use and adherence reminders delivered via text message were feasible for most participants, but there was no signal of effect • After adjusting for age and parental education, mean adherence rates were 36% for the intervention group and 32% for the control group (P=0.73) • Age had no significant impact on adherence rate. After adjusting for impact of intervention and education level, ICS adherence rates in <5 years old were 6% (95% CI 7, 44) compared with 43% (95% CI 30, 55) in those aged ≥5 years (P=0.14) • Mean daily medication adherence trends over the 30-day intervention interval were also similar between the two groups, with broadly overlapping SDs • Mean change in parent-reported portion of the cACT score over the 30 days of the intervention was not statistically significantly different between controls (3.1) and intervention (1.2) (P=0.16) |
| Merchant et al (2016)55 | To measure real-world effectiveness of Propeller Health Asthma Platform to reduce use of SABA and improve asthma control | RCT | Asthma | 495 | 12 months | • Patient mean age was 36.6 years in the intervention group and 36.0 years in the routine care group. Approximately 30% of patients in both the groups were between 5 and 17 years of age. • Daily mean number of SABA uses/person decreased by 0.41 for intervention group and by 0.31 for routine care between first week and remainder of the study (P<0.001) • Proportion of SABA-free days increased 21% (intervention) and 17% (control) (P<0.01) • ACT scores were not significantly different between arms; initially uncontrolled adults: • Significantly larger improvement in ACT scores in the intervention group vs routine care (+6.2 and +4.6, respectively, P<0.01) • Significantly larger improvement in the proportion with controlled asthma in intervention group vs routine care (63% controlled in the study period vs 49%, respectively; P<0.05) |
| Merchant et al (2017)68 | To assess the impact of digital health intervention, which leveraged sensors and app-based education, on ER visits, hospitalizations, inpatient days, and clinic visits | Retrospective, cohort | Asthma | 507 | Data collected between July 2011 and September 2016 | • Patient age was not reported • Significant reductions in hospitalizations (2.7 to 0.6 days; 79% reduction; P<0.0001), inpatient days (7.9 to 1.4 days; 82% reduction; P<0.001) and ER visits (19.2 to 8.3 days; 57% reduction; P<0.0001) • Non-acute asthma-related clinic visits increased (197–277 days; 41% increase; P<0.0001) |
| Su et al (2016)67 | To identify hotspots of asthma symptoms; evaluate associations between asthma symptoms and environmental covariates in real-time and space | Prospective, single-arm | Asthma | 140 | 20 months | • Patient age was not reported • By targeting environmental interventions that could have the largest impact on asthma within specific neighborhoods, 914,000 inhaler uses and $1.8 million of hospitalization costs could be avoided |
| Van Sickle et al (2010)58 | To investigate if online feedback about remotely monitored inhaled bronchodilators improves composite measures of asthma control | Prospective, single-arm | Asthma | 27 | NR | • Patient mean age was 35.5 years (range: 19–74 years) • Asthma control scores increased significantly after receiving email reports after first (P=0.01) and second month (P=0.007) • Patients reported more awareness of symptom frequency, level of control, asthma triggers, and increased adherence to preventive medication |
| Van Sickle et al (2011)59 | To investigate if weekly feedback summarizing use of remotely monitored rescue medication improves asthma control | Prospective, single-arm | Asthma | 34 | 4 months | • Patient mean age was 41.8 years (range: 20–82 years) • Mean ACT scores increased from 17.5 at entry to 19.5 at exit (P=0.01) • Days with asthma symptoms in preceding 2 weeks declined from 6 at entry to 2.8 at exit (P=0.001) • Nights with asthma symptoms in preceding 2 weeks declined from 2.7 at entry to 1.3 at exit (P=0.08) • The ACT scores of 64% participants improved, 11% had no change and 23% worsened |
| Van Sickle et al (2013)60 | To assess whether weekly email reports on monitored use of inhaled, short-acting bronchodilators improves composite asthma control measures | Prospective, single-arm | Asthma | 30 | 4 months | • Patient mean age was 36.8 years (range: 19–74 years) • No significant difference in ACT scores between entry and first month values (P=0.66) • ACT scores increased by 1.40 points (95% CI 0.61, 2.18) for each subsequent study month after patients received feedback |
| Van Sickle et al (2014)61 | To determine the effect of sensor-enabled, mobile health asthma program on individual-level asthma outcomes, including frequency of asthma rescue medication use, asthma-free days and control status | Prospective, single-arm | Asthma | NR | 12 months | • Patient age was not reported • Improved adherence to clinical guidelines reported; 57% of participants had asthma action plan at study end vs 41% at intake • The proportion considered well-controlled increased by 33% between intake and completion • Proportion with an asthma-free day in the first month was significantly different from all subsequent months (P<0.01) |
| Van Sickle et al (2015)57 | To determine whether mobile health asthma program could improve asthma outcomes, including frequency of rescue medication use, asthma-free days, and control | Prospective, single-arm | Asthma | 299 | 12 months | • Study participants included both children and adults. Mean/median age was not reported • 57% of participants reported having an asthma action plan at study end, compared with only 41% at intake • At study exit, rescue inhaler use declined by 75%, and the proportion of participants with an asthma-free day increased significantly by 39% |
| Van Sickle et al (2016)56 | To determine whether a sensor-enabled, clinically integrated mobile health asthma quality improvement program could reduce the frequency of SABA use, and increase asthma-free days, asthma control and controller medication adherence | RCT | Asthma | 125 | 6 months | • Study participants included only adults. Mean/median age was not reported • Significant improvements with intervention vs control on all clinical outcomes, including controller medication adherence, daily SABA use, asthma-free days, and asthma control (all P<0.001) • 21-point improvement in adherence for the intervention |
Abbreviations: ACT, Asthma Control Test; cACT, Childhood Asthma Control Test; ER, emergency room; FEF25–75, forced expiratory flow at 25%–75% of the pulmonary volume; ICS, inhaled corticosteroids; NR, not reported; RCT, randomized controlled trial; SABA, short-acting β-agonist.