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

doi:10.1055/s-0039-3402730

Applied Clinical Informatics, Table of Contents

Appl Clin Inform 2020; 11(01): 079-087
DOI: 10.1055/s-0039-3402730

Research Article

Georg Thieme Verlag KG Stuttgart · New York

Detection and Remediation of Misidentification Errors in Radiology Examination Ordering

Scott E. Sheehan

¹Department of Radiology, William S. Middleton Veterans Hospital, Madison, Wisconsin, United States

,

Nasia Safdar

²Department of Medicine, William S. Middleton Memorial Veterans Hospital and University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States

,

Hardeep Singh

³Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center and Department of Medicine, Baylor College of Medicine, Houston, Texas, United States

,

Dean F. Sittig

⁴School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, United States

,

Michael A. Bruno

⁵Department of Radiology, Penn State Hershey, Hershey, Pennsylvania, United States

,

Kelli Keller

¹Department of Radiology, William S. Middleton Veterans Hospital, Madison, Wisconsin, United States

,

Samantha Kinnard

¹Department of Radiology, William S. Middleton Veterans Hospital, Madison, Wisconsin, United States

,

Michael C. Brunner

⁶Department of Radiology, William S. Middleton Memorial Veterans Hospital and University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States

› Author Affiliations

Abstract

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.

Keywords

radiology - domain - clinical care - error management and prevention - process improvement - system improvement - checklist - trigger tool - safety - process improvement - system improvement

Full Text

References

References
1 Applying the universal protocol to improve patient safety in radiology. Vol 8. Pennsylvania Patient Safety Advisory 2011; 8 (02) 63-70
2 Danaher LA, Howells J, Holmes P, Scally P. Is it possible to eliminate patient identification errors in medical imaging?. J Am Coll Radiol 2011; 8 (08) 568-574
3 Duman BD, Chyung SYY, Villachica SW, Winiecki D. Root causes of errant ordered radiology exams: results of a needs assessment. Perform Improv 2011; 50 (01) 17-24
4 Field C. Adapting verification process to prevent wrong radiology events. Pennsylvania Patient Safety Advisory 2018; 15 (03) 1-13
5 Schultz SR, Watson Jr RE, Prescott SL. , et al. Patient safety event reporting in a large radiology department. AJR Am J Roentgenol 2011; 197 (03) 684-688
6 Rubio EI, Hogan L. Time-out: it's radiology's turn--incidence of wrong-patient or wrong-study errors. AJR Am J Roentgenol 2015; 205 (05) 941-946
7 Duman B, Martin P. Reducing errant ordered radiology exams. Radiol Manage 2012; 34 (01) 18-22 , quiz 23–24
8 Universal protocol for preventing wrong site, wrong procedure, wrong person surgery. Available at: http://www.jointcommission.org/NR/rdonlyres/E3C600EB-043B-4e86-B04E-CA4a89AD5433/0/universal_protocol.pdf . Accessed September 2007
9 Stahel PF, Sabel AL, Victoroff MS. , et al. Wrong-site and wrong-patient procedures in the universal protocol era: analysis of a prospective database of physician self-reported occurrences. Arch Surg 2010; 145 (10) 978-984
10 Angle JF, Nemcek Jr AA, Cohen AM. , et al; SIR Standards Division; Joint Commission Universal Protocol for Preventing Wrong Site, Wrong Procedure, Wrong Person Surgery. Quality improvement guidelines for preventing wrong site, wrong procedure, and wrong person errors: application of the joint commission “Universal Protocol for Preventing Wrong Site, Wrong Procedure, Wrong Person Surgery” to the practice of interventional radiology. J Vasc Interv Radiol 2008; 19 (08) 1145-1151
11 Brook OR, O'Connell AM, Thornton E, Eisenberg RL, Mendiratta-Lala M, Kruskal JB. Quality initiatives: anatomy and pathophysiology of errors occurring in clinical radiology practice. Radiographics 2010; 30 (05) 1401-1410
12 Aspden P. ; Institute of Medicine. (U.S.) Committee on Data Standards for Patient Safety. Patient safety: achieving a new standard for care. Washington, D.C.: National Academies Press; 2004. PMID: 25009854
13 Paull DE, Mazzia LM, Neily J. , et al. Errors upstream and downstream to the Universal Protocol associated with wrong surgery events in the Veterans Health Administration. Am J Surg 2015; 210 (01) 6-13
14 Reason J. Human error: models and management. BMJ 2000; 320 (7237): 768-770
15 Chassin MR, Loeb JM. High-reliability health care: getting there from here. Milbank Q 2013; 91 (03) 459-490
16 Adelman JS, Kalkut GE, Schechter CB. , et al. Understanding and preventing wrong-patient electronic orders: a randomized controlled trial. J Am Med Inform Assoc 2013; 20 (02) 305-310
17 Classen DC, Resar R, Griffin F. , et al. ‘Global trigger tool’ shows that adverse events in hospitals may be ten times greater than previously measured. Health Aff (Millwood) 2011; 30 (04) 581-589
18 Galanter W, Falck S, Burns M, Laragh M, Lambert BL. Indication-based prescribing prevents wrong-patient medication errors in computerized provider order entry (CPOE). J Am Med Inform Assoc 2013; 20 (03) 477-481
19 Murphy DR, Laxmisan A, Reis BA. , et al. Electronic health record-based triggers to detect potential delays in cancer diagnosis. BMJ Qual Saf 2014; 23 (01) 8-16
20 Murphy DR, Meyer AN, Sittig DF, Meeks DW, Thomas EJ, Singh H. Application of electronic trigger tools to identify targets for improving diagnostic safety. BMJ Qual Saf 2018
21 Murphy DR, Thomas EJ, Meyer AN, Singh H. Development and validation of electronic health record-based triggers to detect delays in follow-up of abnormal lung imaging findings. Radiology 2015; 277 (01) 81-87
22 Resar RK, Rozich JD, Classen D. Methodology and rationale for the measurement of harm with trigger tools. Qual Saf Health Care 2003; 12 (Suppl. 02) ii39-ii45
23 Sharek PJ. The emergence of the trigger tool as the premier measurement strategy for patient safety. AHRQ WebM&M 2012; 2012 (05) 120
24 Wilcox AB, Chen YH, Hripcsak G. Minimizing electronic health record patient-note mismatches. J Am Med Inform Assoc 2011; 18 (04) 511-514
25 Burlison JD, McDaniel RB, Baker DK. , et al. Using EHR data to detect prescribing errors in rapidly discontinued medication orders. Appl Clin Inform 2018; 9 (01) 82-88
26 Kalenderian E, Obadan-Udoh E, Yansane A. , et al. Feasibility of electronic health record-based triggers in detecting dental adverse events. Appl Clin Inform 2018; 9 (03) 646-653
27 Kane-Gill SL, MacLasco AM, Saul MI. , et al. Use of text searching for trigger words in medical records to identify adverse drug reactions within an intensive care unit discharge summary. Appl Clin Inform 2016; 7 (03) 660-671
28 Rutberg H, Borgstedt-Risberg M, Gustafson P, Unbeck M. Adverse events in orthopedic care identified via the Global Trigger Tool in Sweden - implications on preventable prolonged hospitalizations. Patient Saf Surg 2016; 10 (01) 23
29 Koppel R, Leonard CE, Localio AR, Cohen A, Auten R, Strom BL. Identifying and quantifying medication errors: evaluation of rapidly discontinued medication orders submitted to a computerized physician order entry system. J Am Med Inform Assoc 2008; 15 (04) 461-465
30 R Core Team. (2015). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available at: http://www.R-project.org/
31 van der Veen W, van den Bemt PMLA, Wouters H. , et al; BCMA Study Group. Association between workarounds and medication administration errors in bar-code-assisted medication administration in hospitals. J Am Med Inform Assoc 2018; 25 (04) 385-392
32 Patient Safety 2015: final technical report. National Quality Forum; Feb 12, 2016. Available at: https://www.qualityforum.org/Publications/2016/02/Patient_Safety_2015_Final_Report.aspx
33 Sittig DF, Singh H. A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. Qual Saf Health Care 2010; 19 (Suppl. 03) i68-i74
34 Wang J, Liang H, Kang H, Gong Y. Understanding health information technology induced medication safety events by two conceptual frameworks. Appl Clin Inform 2019; 10 (01) 158-167