Risk factors for wrong-patient medication orders in the emergency department.

JAMIA Open

Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern 3012, Switzerland.

Published: December 2024

AI Article Synopsis

  • This research focuses on identifying risk factors for wrong-patient medication orders in emergency departments based on a specific metric called "retract-and-reorder" (RaR) events.
  • Over a five-year period, the study analyzed 561,099 medication orders and uncovered 1,031 RaR events, with a higher incidence among males and when patients were assigned to closer exam rooms in the electronic medical records layout.
  • The findings highlight that while factors like similar names and birthdates were not significant, proximity of exam rooms and matching sex were notable risk factors for these errors.

Article Abstract

Objectives: This paper investigates the risk factors for wrong-patient medication orders in an emergency department (ED) by studying intercepted ordering errors identified by the "retract-and-reorder" (RaR) metric (orders that were retracted and reordered for a different patient by the same provider within 10 min).

Materials And Methods: Medication ordering data of an academic ED were analyzed to identify RaR events. The association of RaR events with similarity of patient names and birthdates, matching sex, age difference, the month, weekday, and hour of the RaR event, the elapsed hours since ED shift start, and the proximity of exam rooms in the electronic medical record (EMR) dashboard's layout was evaluated.

Results: Over 5 years (2017-2021), 1031 RaR events were identified among a total of 561 099 medication orders leading to a proportional incidence of 184 per 100 000 ED orders (95% CI: 172; 195). RaR orders were less likely to be performed by nurses compared to physicians (OR 0.54 [0.47; 0.61],  < .001). Furthermore, RaR pairs were more likely to have the same sex (OR 1.26 [95% CI 1.10; 1.43],  = .001) and the proximity of the exam rooms was closer (-0.62 [95% CI -0.77; -0.47],  = .001) compared to control pairs. Patients' names, birthdates, age, and the other factors showed no significant association ( > .005).

Discussion And Conclusion: This study found no significant influence from factors such as similarity of patient names, age, or birthdates. However, the proximity of exam rooms in the user interface of the EMR as well as patients' same sex emerged as risk factors.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11512145PMC
http://dx.doi.org/10.1093/jamiaopen/ooae103DOI Listing

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