title: Predicting asthma exacerbations employing remotely monitored adherence.
abstract: This Letter investigated the efficacy of a decision-support system, designed for respiratory medicine, at predicting asthma exacerbations in a multi-site longitudinal randomised control trial. Adherence to inhaler medication was acquired over 3 months from patients with asthma employing a dose counter and a remote monitoring adherence device which recorded participant's inhaler use: n = 184 (23,656 audio files), 61% women, age (mean ± sd) 49.3 ± 16.4. Data on occurrence of exacerbations was collected at three clinical visits, 1 month apart. The relative risk of an asthma exacerbation for those with good and poor adherence was examined employing a univariate and multivariate modified Poisson regression approach; adjusting for age, gender and body mass index. For all months dose counter adherence was significantly (p < 0.01) higher than remote monitoring adherence. Overall, those with poor adherence had a 1.38 ± 0.34 and 1.42 ± 0.39 (remotely monitored) and 1.25 ± 0.32 and 1.18 ± 0.31 (dose counter) higher relative risk of an exacerbation in model 1 and model 2, respectively. However, this was not found to be statistically significantly different. Remotely monitored adherence holds important clinical information and future research should focus on refining adherence and exacerbation measures. Decision-support systems based on remote monitoring may enhance patient-physician communication, possibly reducing preventable adverse events.
authors.affiliation: Clinical Research Centre, Beaumont Hospital, Royal College of Surgeons in Ireland, Dublin, Ireland; Trinity Centre for Bioengineering, School of Engineering, Trinity College, University of Dublin, Dublin 2, Ireland.
authors.forename: Isabelle
authors.initials: I
authors.lastname: Killane
authors.affiliation: Clinical Research Centre, Beaumont Hospital , Royal College of Surgeons in Ireland , Dublin , Ireland.
authors.forename: Imran
authors.initials: I
authors.lastname: Sulaiman
authors.affiliation: Clinical Research Centre, Beaumont Hospital , Royal College of Surgeons in Ireland , Dublin , Ireland.
authors.forename: Elaine
authors.initials: E
authors.lastname: MacHale
authors.affiliation: Clinical Research Centre, Beaumont Hospital , Royal College of Surgeons in Ireland , Dublin , Ireland.
authors.forename: Aoife
authors.initials: A
authors.lastname: Breathnach
authors.affiliation: Trinity Centre for Bioengineering, School of Engineering, Trinity College , University of Dublin , Dublin 2 , Ireland.
authors.forename: Terence E
authors.initials: TE
authors.lastname: Taylor
authors.affiliation: Trinity Centre for Bioengineering, School of Engineering, Trinity College , University of Dublin , Dublin 2 , Ireland.
authors.forename: Martin S
authors.initials: MS
authors.lastname: Holmes
authors.affiliation: Trinity Centre for Bioengineering, School of Engineering, Trinity College, University of Dublin, Dublin 2, Ireland; School of Medicine, Trinity College, University of Dublin, Dublin 2, Ireland.
authors.forename: Richard B
authors.initials: RB
authors.lastname: Reilly
authors.affiliation: Clinical Research Centre, Beaumont Hospital, Royal College of Surgeons in Ireland, Dublin, Ireland; Department of Medicine, Beaumont Hospital, Royal College of Surgeons in Ireland, Dublin, Ireland.
authors.forename: Richard W
authors.initials: RW
authors.lastname: Costello
keywords: Poisson distribution; age; asthma exacerbations; body mass index; decision support systems; decision-support system; diseases; dose counter adherence; gender; inhaler medication; multisite longitudinal randomised control trial; multivariate modified Poisson regression; patient monitoring; pneumodynamics; regression analysis; remote monitoring adherence device; respiratory medicine; univariate modified Poisson regression