title: Factors contributing to an increase in duplicate medication order errors after CPOE implementation.
abstract: OBJECTIVE
  To evaluate the incidence of duplicate medication orders before and after computerized provider order entry (CPOE) with clinical decision support (CDS) implementation and identify contributing factors.
  
  
  METHODS
  CPOE with duplicate medication order alerts was implemented in a 400-bed Northeastern US community tertiary care teaching hospital. In a pre-implementation post-implementation design, trained nurses used chart review, computer-generated reports of medication orders, provider alerts, and staff reports to identify medication errors in two intensive care units (ICUs).
  
  
  METHODS
  Medication error data were adjudicated by a physician and a human factors engineer for error stage and type. A qualitative analysis of duplicate medication ordering errors was performed to identify contributing factors.
  
  
  RESULTS
  Data were collected for 4147 patient-days pre-implementation and 4013 patient-days post-implementation. Duplicate medication ordering errors increased after CPOE implementation (pre: 48 errors, 2.6% total; post: 167 errors, 8.1% total; p<0.0001). Most post-implementation duplicate orders were either for the identical order or the same medication. Contributing factors included: (1) provider ordering practices and computer availability, for example, two orders placed within minutes by different providers on rounds; (2) communication and hand-offs, for example, duplicate orders around shift change; (3) CDS and medication database design, for example confusing alert content, high false-positive alert rate, and CDS algorithms missing true duplicates; (4) CPOE data display, for example, difficulty reviewing existing orders; and (5) local CDS design, for example, medications in order sets defaulted as ordered.
  
  
  CONCLUSIONS
  Duplicate medication order errors increased with CPOE and CDS implementation. Many work system factors, including the CPOE, CDS, and medication database design, contributed to their occurrence.
authors.affiliation: Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53705, USA. tbw@medicine.wisc.edu
authors.forename: Tosha B
authors.initials: TB
authors.lastname: Wetterneck
authors.forename: James M
authors.initials: JM
authors.lastname: Walker
authors.forename: Mary Ann
authors.initials: MA
authors.lastname: Blosky
authors.forename: Randi S
authors.initials: RS
authors.lastname: Cartmill
authors.forename: Peter
authors.initials: P
authors.lastname: Hoonakker
authors.forename: Mark A
authors.initials: MA
authors.lastname: Johnson
authors.forename: Evan
authors.initials: E
authors.lastname: Norfolk
authors.forename: Pascale
authors.initials: P
authors.lastname: Carayon
mesh_terms: D000328:Adult; D020000:Decision Support Systems, Clinical; D006780:Hospitals, Rural; D006784:Hospitals, Teaching; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration / Q000706:statistics & numerical data*; D050316:Medical Order Entry Systems; D008505:Medical Staff, Hospital; D008508:Medication Errors / Q000706:statistics & numerical data*; D009511:New England; D009741:Nursing Staff, Hospital; D011795:Surveys and Questionnaires