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Improving intraoperative handoffs for ambulatory anesthesia: challenges and solutions for the anesthesiologist

Authors Dexter F, Osman BM, Epstein RH

Received 28 January 2019

Accepted for publication 6 May 2019

Published 24 May 2019 Volume 2019:12 Pages 37—46


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Stefan Wirz

Franklin Dexter,1 Brian Mark Osman,2 Richard H Epstein2

1Division of Management Consulting, Department of Anesthesia, University of Iowa, Iowa City, IA 52242, USA; 2Department of Anesthesiology, University of Miami, Miami, FL, USA

Abstract: Permanent transitions of care from one anesthesia provider to another are associated with adverse events and mortality. There are currently no available data on how to mitigate these poor patient outcomes other than to reduce the occurrence of such handoffs. We used data from an ambulatory surgery center to demonstrate the steps that can be taken to achieve this goal. First, perform statistical forecasting using many months of historical data to create optimal, as opposed to arbitrary shift durations. Second, consider assigning the anesthesia providers designated to work late, if necessary, to the ORs estimated to finish the earliest, rather than latest. We performed multiple analyses showing the quantitative advantage of this strategy for the ambulatory surgery center with multiple brief cases. Third, sequence the cases in the 1 or 2 ORs with the latest scheduled end times so that the briefest cases are finished last. If a supervising anesthesiologist needs to be relieved early for administrative duties (eg, head of the group to meet with administrators or surgeons), assign the anesthesiologist to an OR that finishes with several brief cases. The rationale for these recommendations is that such strategies provide multiple opportunities for a different anesthesia provider to assume responsibility for the patients between cases, thus avoiding a handoff altogether.

Keywords: handoff, staffing, staff scheduling, staff assignment, case sequencing, case duration prediction
Corrigendum for this paper has been published 

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