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Emergency Department Inefficiency Drives Poor Quality

By James J. Augustine, MD, FACEP | on November 16, 2018 | 1 Comment
Benchmarking Alliance
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Bottom line: Opportunities to improve patient flow do exist, and improved patient flow will reduce the rate of incomplete patient encounters.

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ACEP Now: Vol 37 – No 11 – November 2018

References

  1. Wiler JL, Welch S, Pines J, et al. Emergency department performance measures updates: proceedings of the 2014 Emergency Department Benchmarking Alliance consensus summit. Acad Emerg Med. 2015;22(5):542-553.
  2. Sun BC, Binstadt ES, Pelletier A, et al. Characteristics and temporal trends of “left before being seen” visits in U.S. emergency departments, 1995–2002. J Emerg Med. 2007;32(2):211-215.
  3. Anderson D, Pimentel L, Golden B, et al. Drivers of emergency department efficiency: a statistical and cluster analysis of volume, staffing, and operations. Am J Emerg Med. 2016;34(2):155-161.
  4. Augustine JJ. Long ED boarding times drive walkaways, revenue losses. ACEP Now. 2016;35(7):16.

Pages: 1 2 3 | Single Page

Topics: Door-To-ProviderEmergency Department Benchmarking AllianceLeft Before Treatment CompleteLength of StayOperationsPractice ManagementQuality & Safety

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About the Author

James J. Augustine, MD, FACEP

James J. Augustine, MD, FACEP, is national director of prehospital strategy for US Acute Care Solutions in Canton, Ohio; clinical professor of emergency medicine at Wright State University in Dayton, Ohio; and vice president of the Emergency Department Benchmarking Alliance.

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One Response to “Emergency Department Inefficiency Drives Poor Quality”

  1. December 2, 2018

    Rob Beatty, MD FACEP Reply

    Good article. In the time frame reported, there has been a major push for EMR conversion due to meaningful use requirements. Some of those EMRs impact house-wide processes as a whole, which could cause significant increases in lab/radiology turnaround time, and add additional human steps to workflow that were not in practice previously. Have you considered evaluating these additional data points and seeing how they fit into your analysis?

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