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Objective: To determine the effectiveness of the Spirometry 360 distance learning quality improvement (QI) program for enhancing the processes and outcomes of care for children with asthma., Methods: Cluster randomized controlled trial involving 25 matched pairs of pediatric primary care practices. Practices were recruited from 2 practice-based research networks: the Slone Center Office-based Research Network at Boston University, Boston, Mass, and the Puget Sound Pediatric Research Network, Seattle, Wash. Study participants included providers from one of the 50 enrolled pediatric practices and 626 of their patients with asthma. Process measures assessed included spirometry test quality and appropriate prescription of asthma controller medications. Outcome measures included asthma-specific health-related quality of life, and outpatient, emergency department, and inpatient utilization for asthma., Results: At baseline, 25.4% of spirometry tests performed in control practices and 50.4% of tests performed in intervention practices were of high quality. During the 6-month postintervention period, 28.7% of spirometry tests performed in control practices and 49.9% of tests performed in intervention practices were of high quality. The adjusted difference-of-differences analysis revealed no intervention effect on spirometry test quality. Adjusted differences-of-differences analysis also revealed no intervention effect on appropriate use of controller medications or any of the parent- or patient-reported outcomes examined., Conclusions: In this study, the Spirometry 360 distance learning QI program was ineffective in improving spirometry test quality or parent- or patient-reported outcomes. QI programs like the one assessed here may need to focus on practices with lower baseline performance levels or may need to be tailored for those with higher baseline performance., (Copyright © 2017 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.)

Spirometry plays a critical role in characterizing and improving outcomes related to chronic lung disease. However, patient error in performing the spirometry maneuver, such as from coughing or taking multiple breaths, can lead to clinically misleading results. As a result, spirometry must take place under the supervision of a trained specialist who can identify and correct patient errors. To reduce the need for specialists to coach patients during spirometry, we demonstrate the ability to automatically detect four common patient errors. Creating separate machine learning classifiers for each error based on features derived from spirometry data, we were able to successfully label errors on spirometry maneuvers with an F-score between 0.85 and 0.92. Our work is a step toward reducing the need for trained individuals to administer spirometry tests by demonstrating the ability to automatically detect specific errors and provide appropriate patient feedback. This will increase the availability of spirometry, especially in low resource and telemedicine contexts.

Objective: We evaluated the effectiveness of a virtually delivered quality improvement (QI) program designed to improve primary care management for children with asthma., Methods: Thirty-six physicians, nurses, and medical assistants from 14 primary care pediatric practices (7 matched practice pairs) participated in a cluster randomized trial from October 2007 to September 2008. All practices received a spirometer and standard vendor training. A 7-month QI program delivered during the study period included: 1) Spirometry Fundamentals™ CD-ROM, a multimedia tutorial; 2) case-based, interactive webinars led by clinical experts; and 3) an internet-based spirometry quality feedback reporting system. Practice pairs were compared directly to each other, and between-group differences were analyzed with the use of mixed effects regression models. Our main outcome measures were the frequency of spirometry testing, percentage of acceptable quality spirometry tests, asthma severity documentation, and appropriate controller medication prescribing., Results: Participating practices uploaded a total of 1028 spirometry testing sessions, of which 340 (33.1%) were of acceptable quality. During the 7-month intervention period, there was no difference between intervention and control practices in the frequency of spirometry tests performed. Intervention practices were estimated to have significantly greater odds of conducting tests with acceptable quality compared with matched control practices, adjusting for quality in the baseline period (odds ratio 2.85; 95% confidence interval 1.78-4.56, P < .001). Intervention providers also had significantly greater odds of documenting asthma severity during the intervention period (odds ratio 2.9, 95% confidence interval 1.8-4.5; P < .001). Although use of controller medications among patients with persistent asthma approached 100% for both groups, the proportion of asthma patients labeled as persistent increased from 43% to 62% among intervention practices, and decreased from 57% to 50% among controls (NS)., Conclusions: A multifaceted distance QI program resulted in increased spirometry quality and improved assessment of asthma severity levels. Successful participation in QI programs can occur over distance., (Copyright © 2012. Published by Elsevier Inc.)

Purpose: Spirometry has become an indispensable tool in primary care to exclude, diagnose, and monitor chronic respiratory conditions, but the quality of spirometry tests in family practices is a reason for concern. Aim of this study was to investigate whether a combination of e-learning and bimonthly performance feedback would improve spirometry test quality in family practices in the course of 1 year., Methods: Our study was a cluster trial with 19 family practices allocated to intervention or control conditions through minimization. Intervention consisted of e-learning and bimonthly feedback reports to practice nurses. Control practices received only the joint baseline workshop. Spirometry quality was assessed by independent lung function technicians. Two outcomes were defined, with the difference between rates of tests with 2 acceptable and repeatable blows being the primary outcome and the difference between rates of tests with 2 acceptable blows being the secondary outcome. We used multilevel logistic regression analysis to calculate odds ratios (ORs) for an adequate test in intervention group practices., Results: We analyzed 1,135 tests. Rate of adequate tests was 33% in intervention and 30% in control group practices (OR = 1.3; P=.605). Adequacy of tests did not differ between groups but tended to increase with time: OR = 2.2 (P = .057) after 3 and OR = 2.0 (P = .086) in intervention group practices after 4 feedback reports. When ignoring test repeatability, these differences between the groups were slightly more pronounced: OR = 2.4 (P = .033) after 3 and OR=2.2 (P = .051) after 4 feedback reports., Conclusions: In the course of 1 year, we observed a small and late effect of e-learning and repeated feedback on the quality of spirometry as performed by family practice nurses. This intervention does not seem to compensate the lack of rigorous training and experience in performing spirometry tests in most practices.