title: Physician order entry or nurse order entry? Comparison of two implementation strategies for a computerized order entry system aimed at reducing dosing medication errors.
abstract: BACKGROUND
  Despite the significant effect of computerized physician order entry (CPOE) in reducing nonintercepted medication errors among neonatal inpatients, only a minority of hospitals have successfully implemented such systems. Physicians' resistance and users' frustration seem to be two of the most important barriers. One solution might be to involve nurses in the order entry process to reduce physicians' data entry workload and resistance. However, the effect of this collaborative order entry method in reducing medication errors should be compared with a strictly physician order entry method.
  
  
  OBJECTIVE
  To investigate whether a collaborative order entry method consisting of nurse order entry (NOE) followed by physician verification and countersignature is as effective as a strictly physician order entry (POE) method in reducing nonintercepted dose and frequency medication errors in the neonatal ward of an Iranian teaching hospital.
  
  
  METHODS
  A four-month prospective study was designed with two equal periods. During the first period POE was used and during the second period NOE was used. In both methods, a warning appeared when the dose or frequency of the prescribed medication was incorrect that suggested the appropriate dosage to the physicians. Physicians' responses to the warnings were recorded in a database and subsequently analyzed. Relevant paper-based and electronic medical records were reviewed to increase credibility.
  
  
  RESULTS
  Medication prescribing for 158 neonates was studied. The rate of nonintercepted medication errors during the NOE period was 40% lower than during the POE period (rate ratio 0.60; 95% confidence interval [CI] .50, .71;P < .001). During the POE period, 80% of nonintercepted errors occurred at the prescription stage, while during the NOE period, 60% of nonintercepted errors occurred in that stage. Prescription errors decreased from 10.3% during the POE period to 4.6% during the NOE period (P < .001), and the number of warnings with which physicians complied increased from 44% to 68% respectively (P < .001). Meanwhile, transcription errors showed a nonsignificant increase from the POE period to the NOE period. The median error per patient was reduced from 2 during the POE period to 0 during the NOE period (P = .005). Underdose and curtailed and prolonged interval errors were significantly reduced from the POE period to the NOE period. The rate of nonintercepted overdose errors remained constant between the two periods. However, the severity of overdose errors was lower in the NOE period (P = .02).
  
  
  CONCLUSIONS
  NOE can increase physicians' compliance with warnings and recommended dose and frequency and reduce nonintercepted medication dosing errors in the neonatal ward as effectively as POE or even better. In settings where there is major physician resistance to implementation of CPOE, and nurses are willing to participate in the order entry and are capable of doing so, NOE may be considered a beneficial alternative order entry method.
authors.affiliation: Department of Learning, Informatics, Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden. alireza.kazemi@ki.se
authors.forename: Alireza
authors.initials: A
authors.lastname: Kazemi
authors.forename: Uno G H
authors.initials: UG
authors.lastname: Fors
authors.forename: Shahram
authors.initials: S
authors.lastname: Tofighi
authors.forename: Mesfin
authors.initials: M
authors.lastname: Tessma
authors.forename: Johan
authors.initials: J
authors.lastname: Ellenius
mesh_terms: D000046:Academic Medical Centers / Q000706:statistics & numerical data; D003201:Computers; D020000:Decision Support Systems, Clinical; D019983:Guideline Adherence; D006801:Humans; D007231:Infant, Newborn; D007492:Iran; D050316:Medical Order Entry Systems; D008508:Medication Errors / Q000517:prevention & control* / Q000706:statistics & numerical data; D009726:Nurses; D010820:Physicians; D011446:Prospective Studies; D012449:Safety