Crisis management during anaesthesia: the development of an anaesthetic crisis management manual.
BACKGROUND
All anaesthetists have to handle life threatening crises with little or no warning. However, some cognitive strategies and work practices that are appropriate for speed and efficiency under normal circumstances may become maladaptive in a crisis. It was judged in a previous study that the use of a structured "core" algorithm (based on the mnemonic COVER ABCD-A SWIFT CHECK) would diagnose and correct the problem in 60% of cases and provide a functional diagnosis in virtually all of the remaining 40%. It was recommended that specific sub-algorithms be developed for managing the problems underlying the remaining 40% of crises and assembled in an easy-to-use manual. Sub-algorithms were therefore developed for these problems so that they could be checked for applicability and validity against the first 4000 anaesthesia incidents reported to the Australian Incident Monitoring Study (AIMS).


METHODS
The need for 24 specific sub-algorithms was identified. Teams of practising anaesthetists were assembled and sets of incidents relevant to each sub-algorithm were identified from the first 4000 reported to AIMS. Based largely on successful strategies identified in these reports, a set of 24 specific sub-algorithms was developed for trial against the 4000 AIMS reports and assembled into an easy-to-use manual. A process was developed for applying each component of the core algorithm COVER at one of four levels (scan-check-alert/ready-emergency) according to the degree of perceived urgency, and incorporated into the manual. The manual was disseminated at a World Congress and feedback was obtained.


RESULTS
Each of the 24 specific crisis management sub-algorithms was tested against the relevant incidents among the first 4000 reported to AIMS and compared with the actual management by the anaesthetist at the time. It was judged that, if the core algorithm had been correctly applied, the appropriate sub-algorithm would have been resolved better and/or faster in one in eight of all incidents, and would have been unlikely to have caused harm to any patient. The descriptions of the validation of each of the 24 sub-algorithms constitute the remaining 24 papers in this set. Feedback from five meetings each attended by 60-100 anaesthetists was then collated and is included.


CONCLUSIONS
The 24 sub-algorithms developed form the basis for developing a rational evidence-based approach to crisis management during anaesthesia. The COVER component has been found to be satisfactory in real life resuscitation situations and the sub-algorithms have been used successfully for several years. It would now be desirable for carefully designed simulator based studies, using naive trainees at the start of their training, to systematically examine the merits and demerits of various aspects of the sub-algorithms. It would seem prudent that these sub-algorithms be regarded, for the moment, as decision aids to support and back up clinicians' natural responses to a crisis when all is not progressing as expected.
Runciman
W B
WB
Department of Anaesthesia and Intensive Care, University of Adelaide and Royal Adelaide Hospital, Adelaide, South Australia, Australia. research@apsf.net.au
Kluger
M T
MT
Morris
R W
RW
Paix
A D
AD
Watterson
L M
LM
Webb
R K
RK
D000465:Algorithms; D000776:Anesthesiology / Q000592:standards*; D001315:Australia; D032921:Consensus; D004630:Emergencies; D006801:Humans; D007431:Intraoperative Complications / Q000628:therapy*; D008370:Manuals as Topic; D016343:Monitoring, Intraoperative; D017410:Practice Guidelines as Topic; D012151:Resuscitation / Q000592:standards*; D012308:Risk Management; D013647:Task Performance and Analysis