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J Am Coll Radiol. 2016 Jun;13(6):680-7. doi: 10.1016/j.jacr.2016.01.017. Epub 2016 Mar 4.

Tracking and Resolving CT Dose Metric Outliers Using Root-Cause Analysis.

Author information

1
Department of Medical Imaging, St Michael's Hospital, Toronto, Ontario, Canada; Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada. Electronic address: yingming.chen@utoronto.ca.
2
Department of Medical Imaging, St Michael's Hospital, Toronto, Ontario, Canada.
3
Department of Medical Imaging, St Michael's Hospital, Toronto, Ontario, Canada; University of Toronto, Scarborough, Ontario, Canada.
4
Department of Medical Imaging, St Michael's Hospital, Toronto, Ontario, Canada; Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
5
Department of Medical Imaging, St Michael's Hospital, Toronto, Ontario, Canada; Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Keenan Research Centre, Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada.

Abstract

PURPOSE:

The aim of this study was to examine the frequency and type of outlier dose metrics for three common CT examination types on the basis of a root-cause analysis (RCA) approach.

METHODS:

Institutional review board approval was obtained for this retrospective observational study. The requirement to obtain informed consent was waived. Between January 2010 and December 2013, radiation dose metric data from 34,615 CT examinations, including 26,878 routine noncontrast CT head, 2,992 CT pulmonary angiographic (CTPA), and 4,745 renal colic examinations, were extracted from a radiation dose index monitoring database and manually cleaned. Dose outliers were identified on the basis of the statistical distribution of volumetric CT dose index and dose-length product for each examination type; values higher than the 99th percentile and less than the 1st percentile were flagged for RCA.

RESULTS:

There were 397 noncontrast CT head, 52 CTPA, and 80 renal colic outliers. Root causes for high-outlier examinations included repeat examinations due to patient motion (n = 122 [31%]), modified protocols mislabeled as "routine" (n = 69 [18%]), higher dose examinations for patients with large body habitus (n = 27 [7%]), repeat examinations due to technical artifacts (n = 20 [5%]), and repeat examinations due to suboptimal contrast timing (CTPA examinations) (n = 18 [5%]). Root causes for low-outlier examinations included low-dose protocols (n = 112 [29%]) and aborted examinations (n = 8 [2%]). On the basis of examination frequency over a 3-month period, the 90th and 10th percentile values were set in the radiation dose index monitoring database as thresholds for sending notifications to staff members responsible for outlier investigations.

CONCLUSIONS:

Systematic RCA of dose outliers identifies sources of variation and dose excess and pinpoints specific protocol and technical shortcomings for corrective action.

KEYWORDS:

Automated dose tracking; causal analysis; computed tomography; outliers; radiation dose

PMID:
26953644
DOI:
10.1016/j.jacr.2016.01.017
[Indexed for MEDLINE]

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