Electronic health record-based decision support to improve asthma care: a cluster-randomized trial

Journal Name: 
Pediatrics
Authors: 
Bell,L.M.
Grundmeier,R.
Localio,R.
Zorc,J.
Fiks,A.G.
Zhang,X.
Stephens,T.B.
Swietlik,M.
Guevara,J.P.
Abstract: 
OBJECTIVE: Asthma continues to be 1 of the most common chronic diseases of childhood and affects approximately 6 million US children. Although National Asthma Education Prevention Program guidelines exist and are widely accepted, previous studies have demonstrated poor clinician adherence across a variety of populations. We sought to determine if clinical decision support (CDS) embedded in an electronic health record (EHR) would improve clinician adherence to national asthma guidelines in the primary care setting. METHODS: We conducted a prospective cluster-randomized trial in 12 primary care sites over a 1-year period. Practices were stratified for analysis according to whether the site was urban or suburban. Children aged 0 to 18 years with persistent asthma were identified by International Classification of Diseases, Ninth Revision codes for asthma. The 6 intervention-practice sites had CDS alerts imbedded in the EHR. Outcomes of interest were the proportion of children with at least 1 prescription for controller medication, an up-to-date asthma care plan, and the performance of office-based spirometry. RESULTS: Increases in the number of prescriptions for controller medications, over time, was 6% greater (P = .006) and 3% greater for spirometry (P = .04) in the intervention urban practices. Filing an up-to-date asthma care plan improved 14% (P = .03) and spirometry improved 6% (P = .003) in the suburban practices with the intervention. CONCLUSION: In our study, using a cluster-randomized trial design, CDS in the EHR, at the point of care, improved clinician compliance with National Asthma Education Prevention Program guidelines
4
2010
Volume: 
125
Pages: 
e770-e777
Keywords: 
adherence, Adolescent, Affect, Aged, analysis, Asthma, Child, Child,Preschool, Chronic Disease, classification, clinical, Cluster Analysis, Comparative Study, Cross-Sectional Studies, decision, Decision Support Systems,Clinical, Diagnosis, Disease, education, electronic, Electronic Health Records, Guidelines, Health, hospital, Humans, International Classification of Diseases, intervention, Methods, Multicenter Studies, Pediatrics, Philadelphia, population, Prescriptions, primary care, Prospective Studies, Record, Research, Research Support, Spirometry, Standards, support, therapy, Time, trends