title: Methodological variability in detecting prescribing errors and consequences for the evaluation of interventions.
abstract: OBJECTIVE
  To compare four methods of detecting prescribing errors (PE) in the same patient cohorts before and after an intervention (computerised physician order entry; CPOE) and to determine whether the impact of CPOE is identified consistently by all methods.
  
  
  METHODS
  PEs were identified using (1) prospective detection by ward pharmacist; (2) retrospective health record review; (3) retrospective use of a trigger tool and (4) spontaneous reporting over two separate 4-week periods on one surgical ward in a UK teaching hospital.
  
  
  RESULTS
  We reviewed 93 patients pre- and 114 post-CPOE. Using all four methods, we identified 135 PE (10.7% of all medication orders) pre-CPOE, and 127 (7.9%) post-CPOE. There was little overlap in PE detected by the different methods: prospective detection identified 48 (36% of all PE) pre- and 30 (24%) post-CPOE; retrospective review (RR) revealed 93 (69%) pre- and 105 (83%) post-CPOE, trigger tool 0 pre- and 2 (2%) post-CPOE and spontaneous reporting 1 (1%) pre- and 1 (1%) post-CPOE. The calculated relative reduction in risk of PE was 50% using prospective data, 12% with RR and 26% using data from all four methods.
  
  
  CONCLUSIONS
  In this study, each method predominantly identified different PE. A combination of methods may be required to understand the true effectiveness of different interventions.
authors.affiliation: Centre for Medication Safety and Service Quality, Imperial College Healthcare NHS Trust, London, UK.
authors.forename: Bryony Dean
authors.initials: BD
authors.lastname: Franklin
authors.forename: Sylvia
authors.initials: S
authors.lastname: Birch
authors.forename: Imogen
authors.initials: I
authors.lastname: Savage
authors.forename: Ian
authors.initials: I
authors.lastname: Wong
authors.forename: Maria
authors.initials: M
authors.lastname: Woloshynowych
authors.forename: Ann
authors.initials: A
authors.lastname: Jacklin
authors.forename: Nick
authors.initials: N
authors.lastname: Barber
mesh_terms: D011307:Drug Prescriptions / Q000592:standards*; D017598:Efficiency, Organizational; D006784:Hospitals, Teaching; D006801:Humans; D008131:London; D050316:Medical Order Entry Systems / Q000458:organization & administration* / Q000592:standards / Q000706:statistics & numerical data; D008508:Medication Errors / Q000517:prevention & control* / Q000706:statistics & numerical data*; D008510:Medication Systems, Hospital / Q000458:organization & administration* / Q000592:standards / Q000706:statistics & numerical data; D011446:Prospective Studies; D012189:Retrospective Studies