title: Improving antibiotic prescribing for adults with community acquired pneumonia: Does a computerised decision support system achieve more than academic detailing alone?--A time series analysis.
abstract: BACKGROUND
  The ideal method to encourage uptake of clinical guidelines in hospitals is not known. Several strategies have been suggested. This study evaluates the impact of academic detailing and a computerised decision support system (CDSS) on clinicians' prescribing behaviour for patients with community acquired pneumonia (CAP).
  
  
  METHODS
  The management of all patients presenting to the emergency department over three successive time periods was evaluated; the baseline, academic detailing and CDSS periods. The rate of empiric antibiotic prescribing that was concordant with recommendations was studied over time comparing pre and post periods and using an interrupted time series analysis.
  
  
  RESULTS
  The odds ratio for concordant therapy in the academic detailing period, after adjustment for age, illness severity and suspicion of aspiration, compared with the baseline period was OR = 2.79 [1.88, 4.14], p < 0.01, and for the computerised decision support period compared to the academic detailing period was OR = 1.99 [1.07, 3.69], p = 0.02. During the first months of the computerised decision support period an improvement in the appropriateness of antibiotic prescribing was demonstrated, which was greater than that expected to have occurred with time and academic detailing alone, based on predictions from a binary logistic model.
  
  
  CONCLUSIONS
  Deployment of a computerised decision support system was associated with an early improvement in antibiotic prescribing practices which was greater than the changes seen with academic detailing. The sustainability of this intervention requires further evaluation.
authors.affiliation: Victorian Infectious Diseases Service, The Royal Melbourne Hospital, Parkville, Victoria 3050, Australia. kirsty.buising@mh.org.au
authors.forename: Kirsty L
authors.initials: KL
authors.lastname: Buising
authors.forename: Karin A
authors.initials: KA
authors.lastname: Thursky
authors.forename: James F
authors.initials: JF
authors.lastname: Black
authors.forename: Lachlan
authors.initials: L
authors.lastname: MacGregor
authors.forename: Alan C
authors.initials: AC
authors.lastname: Street
authors.forename: Marcus P
authors.initials: MP
authors.lastname: Kennedy
authors.forename: Graham V
authors.initials: GV
authors.lastname: Brown
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D001315:Australia; D015331:Cohort Studies; D017714:Community-Acquired Infections / Q000188:drug therapy; D020000:Decision Support Systems, Clinical; D004360:Drug Therapy, Computer-Assisted; D004632:Emergency Medical Services; D005260:Female; D019983:Guideline Adherence; D006784:Hospitals, Teaching; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011014:Pneumonia / Q000188:drug therapy*; D017410:Practice Guidelines as Topic; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*
chemical_list: D000900:Anti-Bacterial Agents