An asthma management system in a pediatric emergency department

Abstract

Introduction Pediatric asthma exacerbations account for >1.8 million emergency department (ED) visits annually. Asthma guidelines are intended to guide time-dependent treatment decisions that improve clinical outcomes; however, guideline adherence is inadequate. We examined whether an automatic disease detection system increases clinicians' use of paper-based guidelines and decreases time to a disposition decision. Methods We evaluated a computerized asthma detection system that triggered NHLBI-adopted, evidence-based practice to improve care in an urban, tertiary care pediatric ED in a 3-month (7/09–9/09) prospective, randomized controlled trial. A probabilistic system screened all ED patients for acute asthma. For intervention patients, the system generated the asthma protocol at triage for intervention patients to guide early treatment initiation, while clinicians followed standard processes for control patients. The primary outcome measures included time to patient disposition. Results The system identified 1100 patients with asthma exacerbations, of which 704 had a final asthma diagnosis determined by a physician-established reference standard. The positive predictive value for the probabilistic system was 65%. The median time to disposition decision did not differ among the intervention (289 min; IQR = (184, 375)) and control group (288 min; IQR = (185, 375)) (p= 0.21). The hospital admission rate was unchanged between intervention (37%) and control groups (35%) (p= 0.545). ED length of stay did not differ among the intervention (331 min; IQR =(226, 581)) and control group (331 min; IQR = (222, 516)) (p = 0.568). Conclusion Despite a high level of support from the ED leadership and staff, a focused education effort, and implementation of an automated disease detection, the use of the paper-based asthma protocol remained low and time to patient disposition did not change.

Implementation and evaluation of an integrated computerized asthma management system in a pediatric emergency department: A randomized clinical trial

“…The asthma system includes two components: 1) the automatic disease detection system, and 2) a computerized management system that has been reported previously [14]. The automatic disease detection system was based on a Bayesian network [9, 15, 16] developed in the same pediatric ED as the study.…”

The soft computing-based approach to investigate allergic diseases: a systematic review

“…Predicting the correct category of exacerbation severity is challenging in order to assess the appropriate hospitalization of the patient [9]. Sanders et al [10] first proposed an SC model to detect asthma exacerbation in patients from the pediatric emergency department.…”

Clinical pathway improves pediatrics asthma management in the emergency department and reduces admissions

“…Few pathways have been able to reduce ED LOS, [13, 26] while others have had no impact [15, 51]. The former institutions had much higher baseline ED LOS than us (6–8 hours vs under 4 hours, respectively) and perhaps more opportunity for improvement.…”

“…[30] By comparison, there are few ED pediatric asthma management systems or protocols that have been rigorously studied in the US. [50, 51] Dexheimer et al developed a computerized asthma detection system for the early identification and treatment of patients with asthma exacerbations. However, the treatment protocol was 8 pages long and was underutilized.…”