Asthma
Conditions
Interventions
eHealth home-monitoring of respiratory physiology and online communication.
Sponsors
Philips
Eligibility
Age
2 Years to 11 Years
Inclusion criteria
Inclusion criteria: o Children with moderate-to-severe asthma. o Children in the age group from 4 up to and included 11 years old. o Children living in a house with WIFI
Exclusion criteria
Exclusion criteria: o Prior participation in eHealth care trial. o Children/Parents with an inability to understand or speak Dutch. o Children with divorced parents or other reasons that causes them to be less than 80% on the same living address. o Children of whom family members have already participated in this trial. o Children using an inhaler that is not compatible with the FindAir smart inhaler cap, which cannot be replaced by a compatible alternative. o Children for whom it is not possible to perform at least one of the two discontinuous dyspnea assessment (lung function/pulse oximetry). o Children with chronic diseases other than asthma (i.e. inflammatory bowel disease, behavioral disorders, mental retardation). o Children with currently displaying COVID-19-related symptoms, namely a fever, cough and/or difficulty breathing (during inclusion) or being infected with COVID-19 in the past 14days.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| This study aims to evaluate the effect of pediatric asthma eHealth care on the amount, type and costs of healthcare utilization. The essence of this study is to evaluate the difference in healthcare utilization by the use of eHealth. | — |
Secondary
| Measure | Time frame |
|---|---|
| 1) To evaluate the effect of pediatric asthma eHealth care on the asthma outcomes and quality of life. 2) To assess how long the learning effects of the healthcare utilization, asthma outcomes and quality of life effects after 3 months of follow up in theof eHealth interventions compared to the control groupon asthma outcomes. healthcare utilization last and to assess the time to first healthcare events in the follow-up period in both the intervention and control group. (survival analysis). 3) To assess the effect of eHealth interventions (i.e. education on self-management, treatment change or providing a personalized action plan) on the asthma outcomes, such as lung function and asthma control score. 4) To assess the effect of personalized real-time monitoring and education of inhalation (based on objective smart inhaler data) on the inhalation technique/adherence. 5) To investigate the effect of (via eHealth communication) supervised nebulizer therapy (with Sami the Seal). (amount of events, % solved at home, % that still result in referral to hospital) 6) To correlate monitoring parameters (nocturnal symptoms, lung function, oxygen saturation, cough/wheeze, medication use and air parameters (indoor + outdoor + pollen) univariately and multivariate with reported symptoms and asthma control. 7) To assess the perception of dyspnea in children by correlating the self-reported dyspnea with the visual analogue scale versus home-measured lung function. 8) To analyze the preluding period before an asthma exacerbation for predictors in the home-measured signals using predictive modelling. 9) To explore the feasibility and acceptance of the monitoring devices for home-use in children. 10) To identify the patient characteristics of children with successful eHealth care outcomes. | — |
Countries
Netherlands
Outcome results
None listed