Detection and Remediation of Misidentification Errors in Radiology Examination Ordering

Scott E. Sheehan, Nasia Safdar, Hardeep Singh, Dean F. Sittig, Michael A. Bruno, Kelli Keller, Samantha Kinnard, Michael C. Brunner

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Background Despite progress in patient safety, misidentification errors in radiology such as ordering imaging on the wrong anatomic side persist. If undetected, these errors can cause patient harm for multiple reasons, in addition to producing erroneous electronic health records (EHR) data. Objectives We describe the pilot testing of a quality improvement methodology using electronic trigger tools and preimaging checklists to detect wrong-side misidentification errors in radiology examination ordering, and to measure staff adherence to departmental policy in error remediation. Methods We retrospectively applied and compared two methods for the detection of wrong-side misidentification errors among a cohort of all imaging studies ordered during a 1-year period (June 1, 2015-May 31, 2016) at our tertiary care hospital. Our methods included: (1) manual review of internal quality improvement spreadsheet records arising from the prospective performance of preimaging safety checklists, and (2) automated error detection via the development and validation of an electronic trigger tool which identified discrepant side indications within EHR imaging orders. Results Our combined methods detected misidentification errors in 6.5/1,000 of study cohort imaging orders. Our trigger tool retrospectively identified substantially more misidentification errors than were detected prospectively during preimaging checklist performance, with a high positive predictive value (PPV: 88.4%, 95% confidence interval: 85.4-91.4). However, two third of errors detected during checklist performance were not detected by the trigger tool, and checklist-detected errors were more often appropriately resolved (p < 0.00001, 95% confidence interval: 2.0-6.9; odds ratio: 3.6). Conclusion Our trigger tool enabled the detection of substantially more imaging ordering misidentification errors than preimaging safety checklists alone, with a high PPV. Many errors were only detected by the preimaging checklist; however, suggesting that additional trigger tools may need to be developed and used in conjunction with checklist-based methods to ensure patient safety.

Original languageEnglish (US)
Pages (from-to)79-87
Number of pages9
JournalApplied Clinical Informatics
Issue number1
StatePublished - 2020

All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Computer Science Applications
  • Health Information Management


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