TY - JOUR
T1 - Understanding and preventing wrong-patient electronic orders
T2 - A randomized controlled trial
AU - Adelman, Jason S.
AU - Kalkut, Gary E.
AU - Schechter, Clyde B.
AU - Weiss, Jeffrey M.
AU - Berger, Matthew A.
AU - Reissman, Stan H.
AU - Cohen, Hillel W.
AU - Lorenzen, Stephen J.
AU - Burack, Daniel A.
AU - Southern, William N.
PY - 2013
Y1 - 2013
N2 - Objective: To evaluate systems for estimating and preventing wrong-patient electronic orders in computerized physician order entry systems with a two-phase study. Materials and methods: In phase 1, from May to August 2010, the effectiveness of a 'retract-and-reorder' measurement tool was assessed that identified orders placed on a patient, promptly retracted, and then reordered by the same provider on a different patient as a marker for wrong-patient electronic orders. This tool was then used to estimate the frequency of wrong-patient electronic orders in four hospitals in 2009. In phase 2, from December 2010 to June 2011, a three-armed randomized controlled trial was conducted to evaluate the efficacy of two distinct interventions aimed at preventing these errors by reverifying patient identification: an 'ID-verify alert', and an 'ID-reentry function'. Results: The retract-and-reorder measurement tool effectively identified 170 of 223 events as wrong-patient electronic orders, resulting in a positive predictive value of 76.2% (95% CI 70.6% to 81.9%). Using this tool it was estimated that 5246 electronic orders were placed on wrong patients in 2009. In phase 2, 901 776 ordering sessions among 4028 providers were examined. Compared with control, the ID-verify alert reduced the odds of a retract-and-reorder event (OR 0.84, 95% CI 0.72 to 0.98), but the ID-reentry function reduced the odds by a larger magnitude (OR 0.60, 95% CI 0.50 to 0.71). Discussion and conclusion: Wrong-patient electronic orders occur frequently with computerized provider order entry systems, and electronic interventions can reduce the risk of these errors occurring.
AB - Objective: To evaluate systems for estimating and preventing wrong-patient electronic orders in computerized physician order entry systems with a two-phase study. Materials and methods: In phase 1, from May to August 2010, the effectiveness of a 'retract-and-reorder' measurement tool was assessed that identified orders placed on a patient, promptly retracted, and then reordered by the same provider on a different patient as a marker for wrong-patient electronic orders. This tool was then used to estimate the frequency of wrong-patient electronic orders in four hospitals in 2009. In phase 2, from December 2010 to June 2011, a three-armed randomized controlled trial was conducted to evaluate the efficacy of two distinct interventions aimed at preventing these errors by reverifying patient identification: an 'ID-verify alert', and an 'ID-reentry function'. Results: The retract-and-reorder measurement tool effectively identified 170 of 223 events as wrong-patient electronic orders, resulting in a positive predictive value of 76.2% (95% CI 70.6% to 81.9%). Using this tool it was estimated that 5246 electronic orders were placed on wrong patients in 2009. In phase 2, 901 776 ordering sessions among 4028 providers were examined. Compared with control, the ID-verify alert reduced the odds of a retract-and-reorder event (OR 0.84, 95% CI 0.72 to 0.98), but the ID-reentry function reduced the odds by a larger magnitude (OR 0.60, 95% CI 0.50 to 0.71). Discussion and conclusion: Wrong-patient electronic orders occur frequently with computerized provider order entry systems, and electronic interventions can reduce the risk of these errors occurring.
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U2 - 10.1136/amiajnl-2012-001055
DO - 10.1136/amiajnl-2012-001055
M3 - Article
C2 - 22753810
AN - SCOPUS:84874761572
SN - 1067-5027
VL - 20
SP - 305
EP - 310
JO - Journal of the American Medical Informatics Association
JF - Journal of the American Medical Informatics Association
IS - 2
ER -