Off-console automated artificial intelligence enhanced workflow enables improved emergency department CT capacity.

Journal: Emergency radiology
PMID: 39661269

Abstract

PURPOSE: Increasing CT capacity to keep pace with rising ED demand is critical. The conventional process has inherent drawbacks. We evaluated an off-console automated AI enhanced workflow which moves all final series creation off-console. We hypothesized the off-console workflow would 1) decrease overall ED CT exam begin to end times and decrease length and variability of time CT is occupied at the individual exam level.

Authors

  • John McMenamy
    Department of Radiology, New York University School of Medicine, 550 1st Ave, New York, NY 10016, United States.
  • Sergey Kochkine
    Stony Brook University Hospital, Stony Brook, USA.
  • Mark Bernstein
    Boston Medical Center, Boston, USA.
  • Anthony Lucero
    Denver Health Medical Center, Denver, USA.
  • Randy Miles
    From the Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Mass (A.Y., T.S., R.B.); and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, WAC 240, Boston, Mass 02114-2698 (R.M., C.L.).
  • Adam Schwertner
    Denver Health Medical Center, Denver, USA.
  • Ashesh Thaker
    Denver Health Medical Center, Denver, USA.
  • David M Naeger
    Dartmouth-Hitchcock Medical Center, Lebanon, USA.

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