title: Impact of clinical decision support on receipt of antibiotic prescriptions for acute bronchitis and upper respiratory tract infection.
abstract: OBJECTIVE
  Antibiotics are commonly recognized as non-indicated for acute bronchitis and upper respiratory tract infection (URI), yet their widespread use persists. Clinical decision support in the form of electronic warnings is hypothesized to prevent non-indicated prescriptions. The purpose of this study was to identify the effect of clinical decision support on a common type of non-indicated prescription.
  
  
  METHODS
  Using National Ambulatory Medical Care Survey data from 2006 to 2010, ambulatory visits with a primary diagnosis of acute bronchitis or URI and orders for antibiotic prescriptions were identified. Visits were classified on the basis of clinician report of decision-support use. Generalized estimating equations were used to assess the effect of decision support on likelihood of antibiotic prescription receipt, controlling for patient, provider, and practice characteristics.
  
  
  RESULTS
  Clinician use of decision support increased sharply between 2006 (16% of visits) and 2010 (55%). Antibiotic prescribing for acute bronchitis and URI increased from ∼35% of visits in 2006 to ∼45% by 2010. Use of decision support was associated with a 19% lower likelihood of receiving an antibiotic prescription, controlling for patient, provider, and practice characteristics.
  
  
  CONCLUSIONS
  In spite of the increased use of decision-support systems and the relatively fewer non-indicated antibiotic prescriptions resulting from the use of decision support, a secular upward trend in non-indicated antibiotic prescribing offset these improvements.
  
  
  CONCLUSIONS
  The overall effect of decision support suggests an important role for technology in reducing non-indicated prescriptions. Decision support alone may not be sufficient to eliminate non-indicated prescriptions given secular trends.
authors.affiliation: School for the Science of Health Care Delivery, Arizona State University, Phoenix, Arizona, USA.
authors.forename: J Mac
authors.initials: JM
authors.lastname: McCullough
authors.affiliation: Department of Health Policy and Management, University of California, Los Angeles Fielding School of Public Health, Los Angeles, California, USA.
authors.forename: Frederick J
authors.initials: FJ
authors.lastname: Zimmerman
authors.affiliation: Department of Health Policy and Management, University of California, Berkeley School of Public Health, Berkeley, California, USA.
authors.forename: Hector P
authors.initials: HP
authors.lastname: Rodriguez
mesh_terms: D000208:Acute Disease; D000553:Ambulatory Care; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D001991:Bronchitis / Q000188:drug therapy*; D020000:Decision Support Systems, Clinical / Q000706:statistics & numerical data; D011307:Drug Prescriptions / Q000706:statistics & numerical data; D004360:Drug Therapy, Computer-Assisted; D004363:Drug Utilization / Q000706:statistics & numerical data*; D006801:Humans; D057970:Inappropriate Prescribing / Q000517:prevention & control*; D015999:Multivariate Analysis; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data; D012141:Respiratory Tract Infections / Q000188:drug therapy*; D014481:United States
chemical_list: D000900:Anti-Bacterial Agents
keywords: Acute bronchitis; Antibiotics; Health information technology