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06/05/26

Wrong-side imaging orders: automated detection using electronic health record data - a retrospective cohort study.

Kneifati-Hayek, Jerard Z; Peabody, Isaac; Baillie, Charles; Park, Jiheum; Gu, Tian; Elias, Jonathan; Hentel, Keith; Kang, Stella; Weng, Chunhua; Shelton, Rachel C; Weintraub, Joshua; Rinke, Michael; Fertel, Baruch S; Adelman, Jason S. BMJ Open Quality

Collection Topics
Health IT Measurement, Monitoring, and Event Analysis Tests, Screening, and Laboratory Processes
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Summary

Wrong-side imaging orders are preventable but can go undetected due to reporting gaps. This six-site retrospective cohort study validated a decently accurate EHR-based method to flag these errors, which were more common in outpatient settings and patients with unknown race/ethnicity. The scalable approach supports surveillance and targeted interventions to improve diagnostic safety and reduce patient harm.
Read the paper
Kneifati-Hayek JZ, Peabody I, Baillie C, et al. Wrong-side imaging orders: automated detection using electronic health record data - a retrospective cohort study. BMJ Open Qual. 2026;15(2):e003969.