Literature DB >> 24956454

Adherence to guidelines for the management of local anesthetic systemic toxicity is improved by an electronic decision support tool and designated "Reader".

Matthew D McEvoy1, William R Hand, W David Stoll, Cory M Furse, Paul J Nietert.   

Abstract

BACKGROUND AND OBJECTIVES: A hardcopy or paper cognitive aid has been shown to improve performance during the management of simulated local anesthetic systemic toxicity (LAST) when given to the team leader. However, there remains room for improvement to ensure a system that can achieve perfect adherence to the published guidelines for LAST management. Recent research has shown that implementing a checklist via a designated reader may be of benefit. Accordingly, we sought to investigate the effect of an electronic decision support tool (DST) and designated "Reader" role on team performance during an in situ simulation of LAST.
METHODS: Participants were randomized to Reader + DST (n = 16, rDST) and Control (n = 15, memory alone). The rDST group received the assistance of a dedicated Reader on the response team who was equipped with an electronic DST. The primary outcome measure was adherence to guidelines.
RESULTS: For overall and critical percent correct scores, the rDST group scored higher than Control (99.3% vs 72.2%, P < 0.0001; 99.5% vs 70%, P < 0.0001, respectively). In the LAST scenario, 0 (0%) of 15 in the control group performed 100% of critical management steps, whereas 15 (93.8%) of 16 in the rDST group did so (P < 0.0001).
CONCLUSIONS: In a prospective, randomized single-blinded study, a designated Reader with an electronic DST improved adherence to guidelines in the management of an in situ simulation of LAST. Such tools are promising in the future of medicine, but further research is needed to ensure the best methods for implementing them in the clinical arena.

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Year:  2014        PMID: 24956454      PMCID: PMC4068273          DOI: 10.1097/AAP.0000000000000097

Source DB:  PubMed          Journal:  Reg Anesth Pain Med        ISSN: 1098-7339            Impact factor:   6.288


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