The main purpose of this study is to look at whether clinicians and their patients with asthma can satisfactorily perform remote asthma management at home (not visiting clinic) by using an artificial intelligence tool called Asthma-Guidance and Prediction System combined with a home monitoring device called AsthmaTuner.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
47
Phone application and spirometer for self-management of asthma
Artificial Intelligence (AI)-assisted clinical decision support system which extracts pertinent patient data related to asthma management from electronic health record
Mayo Clinic
Rochester, Minnesota, United States
Change in satisfaction of asthma care
Measured by single question to assess satisfaction about asthma care using a Likert scale where 1=strongly disagree and 5=strongly agree. Higher score indicates greater satisfaction.
Time frame: Baseline, 6 months
Time allocated to asthma visits
Total time allocated to asthma visits which includes time spent with pediatric participant, EHR review, and completion of timed clinical task.
Time frame: 6 months
Number of on-site visits
Total number of on-site visits for related asthma care
Time frame: 6 months
Frequency of poorly controlled asthma
Number of subjects to have poorly controlled asthma defined as Asthma Control Test or Childhood Asthma Control Test score less than 20.
Time frame: Baseline, 6 months
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