title: Impact of vendor computerized physician order entry in community hospitals.
abstract: BACKGROUND
  It is uncertain if computerized physician order entry (CPOE) systems are effective at reducing adverse drug event (ADE) rates in community hospitals, where mainly vendor-developed applications are used.
  
  
  OBJECTIVE
  To evaluate the impact of vendor CPOE systems on the frequency of ADEs.
  
  
  METHODS
  Prospective before-and-after study conducted from January 2005 to September 2010 at five Massachusetts community hospitals. Participants were adults admitted during the study period. A total of 2,000 charts were reviewed for orders, medication lists, laboratory reports, admission histories, notes, discharge summaries, and flow sheets.
  
  
  METHODS
  The primary outcome measure was the rate of preventable ADEs. Rates of potential ADEs and overall ADEs were secondary outcomes.
  
  
  RESULTS
  The rate of preventable ADEs decreased following implementation (10.6/100 vs. 7.0/100 admissions; p = 0.007) with a similar effect observed at each site. However, the associated decrease in preventable ADEs was balanced against an increase in potential ADEs (44.4/100 vs. 57.5/100 admissions; p < 0.001). We observed a reduction of 34.0% for preventable ADEs, but an increase of 29.5% in potential ADEs following implementation. The overall rate of ADEs increased (14.6/100 vs. 18.7/100 admissions; p = 0.03), which was driven by non-preventable events (4.0/100 vs. 11.7/100 admissions; p < 0.001).
  
  
  CONCLUSIONS
  Adoption of vendor CPOE systems was associated with a decrease in the preventable ADE rate by a third, although the rates of potential ADEs and overall ADEs increased. Our findings support the use of vendor CPOE systems as a means to reduce drug-related injury and harm. The potential ADE rate could be reduced by making refinements to the vendor applications and their associated decision support.
authors.affiliation: Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA 02120-1613, USA.
authors.forename: Alexander A
authors.initials: AA
authors.lastname: Leung
authors.forename: Carol
authors.initials: C
authors.lastname: Keohane
authors.forename: Mary
authors.initials: M
authors.lastname: Amato
authors.forename: Steven R
authors.initials: SR
authors.lastname: Simon
authors.forename: Michael
authors.initials: M
authors.lastname: Coffey
authors.forename: Nathan
authors.initials: N
authors.lastname: Kaufman
authors.forename: Bismarck
authors.initials: B
authors.lastname: Cadet
authors.forename: Gordon
authors.initials: G
authors.lastname: Schiff
authors.forename: Eyal
authors.initials: E
authors.lastname: Zimlichman
authors.forename: Diane L
authors.initials: DL
authors.lastname: Seger
authors.forename: Catherine
authors.initials: C
authors.lastname: Yoon
authors.forename: Peter
authors.initials: P
authors.lastname: Song
authors.forename: David W
authors.initials: DW
authors.lastname: Bates
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003132:Commerce; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology / Q000517:prevention & control*; D006302:Health Services Research / Q000379:methods; D006764:Hospitals, Community / Q000458:organization & administration*; D006801:Humans; D008404:Massachusetts / Q000453:epidemiology; D050316:Medical Order Entry Systems / Q000458:organization & administration*; D008508:Medication Errors / Q000517:prevention & control* / Q000706:statistics & numerical data; D008510:Medication Systems, Hospital / Q000458:organization & administration; D008875:Middle Aged; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D055815:Young Adult