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AJR 2002; 179:859-862
© American Roentgen Ray Society


Dedicated CT Scanner in an Emergency Department: Quantification of Factors That Contribute to Lack of Use

Diego B. Nuñez, Jr.1,2, M. Stephen Ledbetter1 and Lisa Farrell1

1 Department of Radiology, Brigham and Women's Hospital, 75 Francis St., Boston, MA 02115.
2 Present address: Department of Radiology, Hospital of St. Raphael, 1450 Chapel St., New Haven, CT 06511.

OBJECTIVE. The purpose of our study was to quantify the factors that contribute to the lack of use of a dedicated CT scanner in the emergency department of our institution and to identify possible changes to reduce scanner idle time.

MATERIALS AND METHODS. We designed a data collection form to record consecutive periods of patient scanning and periods between patients when the CT scanner was not in use. The contributing factors for each idle period were identified and logged according to an entry system previously decided in consensus. Data were collected continuously for 11 days. The factors we identified for measurement were no request for scanning, preventive maintenance, equipment failure, technologist unavailable, room cleaning and preparation, patient preparation for abdominal CT, patient undergoing other tests, transportation delays, pending laboratory workup, and miscellaneous factors. The time attributed to the most prevalent factors was also grouped into four 6-hr periods corresponding to our department's shifts.

RESULTS. The scanner was idle 73% of the total study time. The chief contributing factors to lack of use were having no patients to scan, patient undergoing preparation, and transportation delays, which accounted for 38.5%, 31%, and 11.7% of the aggregate idle time, respectively. The 6-hr periods of least use were the 7:00 A.M.—1:00 P.M. and the 1:00 A.M.—7:00 A.M. shifts, which accounted for 17% and 19% of idle time, respectively.

CONCLUSION. Dedicated emergency department CT scanners can have significant daily periods of consistent lack of use. The idle time can be reduced by identifying patterns of referral time and correcting specific operational delays.


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