To evaluate performance of a computerized decision support tool to standardize usual care regimens for asthma management in randomized controlled trials (RCTs).The study included a total of 1443 participants with persistent, uncontrolled asthma who were enrolled in 3 published Inner-City Asthma Consortium multicenter trials; the trials were the Asthma Control Evaluation, the Inner-City Anti-IgE Therapy for Asthma, and the Preventative Omalizumab or Step-Up Therapy for Severe Falls Exacerbations trials. Participants were between 6 and 20 years of age, predominantly black or Hispanic, and highly sensitized to common aeroallergens, and a majority resided in households with annual incomes of <$15 000.Children and adolescents with persistent uncontrolled asthma living in urban areas in the United States were recruited into 3 multicenter RCTs of the Inner-City Asthma Consortium between 2004 and 2014, each with a usual care arm. A computerized decision support tool, the Asthma Control Evaluation and Treatment (ACET) Program, scored asthma control on the basis of parent- and patient-provided answers to questions about daytime and nighttime symptoms, along with forced expiratory volume in 1 second, and assigned an appropriate treatment step on the basis of National Asthma Education and Prevention Program guidelines. Control-level determinants were composed of symptoms, rescue medication use, pulmonary function measure, and adherence estimates; these data were collected at visits and entered into the ACET tool. Changes in control levels and treatment steps were evaluated during the trials.At screening, a majority of participants were assessed as asthma that was not well controlled or poorly controlled. There was a significant increase in the proportion of participants who gained good control between screening and random assignment in all 3 trials. There were 51% to 70% of participants who had symptoms well controlled by random assignment with careful adherence to ACET Program step recommendations, and the proportion of participants with well-controlled asthma remained constant or improved slightly from random assignment until the last posttreatment visit. Nighttime symptoms were the most common control-level determinant contributing to asthma control level compared with daytime symptoms and pulmonary function (forced expiratory volume in 1 second). Study physicians agreed with the ACET step recommendations in 90% or more visits, and there were few instances in which there was a study physician override. Poor medication adherence affected treatment algorithm in 5% to 10% of visits.Investigators in the study found that the application of the ACET computerized decision support tool enabled standardized asthma assessment and treatment in RCTs and was associated with attaining and maintaining good asthma in control in most participants.The study is the largest to examine performance of a computerized decision support tool to standardize usual care regimens for asthma management in RCTs among high-risk populations. This tool allowed for an algorithmic approach based on published guidelines to rate control and assign a treatment step. And furthermore, it allowed monitoring of treatment decisions longitudinally, minimized variability in decision-making across multiple centers, studied the alignment of decision support with clinical judgment, and determined when adjustments were made on the basis of adherence versus symptom or exacerbation occurrences. Although thus far focused on clinical trials, there is no reason that this approach could not eventually be applied clinically, better equipping health care providers to assess asthma control and link with evidence-based guidelines for asthma management, especially if integrated into the electronic health record.
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May 18, 2020
Ann-Marie Malby Schoos + 6
Open Access
