• Anaesthesia · Jul 2021

    Randomized Controlled Trial Multicenter Study

    The Haemostasis Traffic Light, a user-centred coagulation management tool for acute bleeding situations: a simulation-based randomised dual-centre trial.

    The Haemostasis Traffic Light is a cognitive aid integrating clinical judgement & point-of-care testing to improve management of periooperative bleeding.

    pearl
    • E D Kataife, S Said, J Braun, T R Roche, J Rössler, A Kaserer, D R Spahn, F G Mileo, and D W Tscholl.
    • Department of Anaesthesiology, Hospital Italiano de Buenos Aires, Argentina.
    • Anaesthesia. 2021 Jul 1; 76 (7): 902-910.

    AbstractThe Haemostasis Traffic Light is a cognitive aid with a user-centred design to enhance and simplify situation awareness and decision-making during peri-operative bleeding. Its structure helps to prioritise therapeutic interventions according to the pathophysiology and the severity of the bleeding. This investigator-initiated, randomised, prospective, international, dual-centre study aimed to validate the Haemostasis Traffic Light by adapting it to the local coagulation protocols of two university hospitals. Between 9 January and 12 May 2020, we recruited 84 participants at the University Hospital Zurich, Switzerland, and the Italian Hospital of Buenos Aires, Argentina. Each centre included 21 resident and 21 staff anaesthetists. Participants were randomly allocated to either the text-based algorithm or the Haemostasis Traffic Light. All participants managed six bleeding scenarios using the same algorithm. In simulated bleeding scenarios, the design of the Haemostasis Traffic Light algorithm enabled more correctly solved cases, OR (95%CI) 7.23 (3.82-13.68), p < 0.001, and faster therapeutic decisions, HR (95%CI) 1.97 (1.18-3.29, p = 0.010). In addition, the tool improved therapeutic confidence, OR (95%CI) 4.31 (1.67-11.11, p = 0.003), and reduced perceived work-load coefficient (95%CI) -6.1 (-10.98 to -1.22), p = 0.020). This study provides empirical evidence for the importance of user-centred design in the development of haemostatic management protocols.© 2020 Association of Anaesthetists.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

    pearl
    1

    The Haemostasis Traffic Light is a cognitive aid integrating clinical judgement & point-of-care testing to improve management of periooperative bleeding.

    Daniel Jolley  Daniel Jolley
    summary
    0

    Kataife et al. (2021) describe a cognitive aid for better managing perioperative haemorrhage, the Haemostasis Traffic Light algorithm. Using a simulation-based RCT across two centres (University Hospital Zurich & the Italian Hospital of Buenos Aires, N=84), they showed that using the HTL improved case solutions (OR 7.23, 3.82-13.68), quickened therapeutic decisions, (HR 1.97, 1.18-3.29), improved therapeutic confidence, (OR 4.31, 1.67-11.11) and reduced workload perception.

    The aim of the HTL is to improve both situational awareness and decision making, by integrating clinical judgement and point-of-care testing (ROTEM) within an accessible, structured algorithm.

    Haemostasis Traffic Light takeaway:

    Kataife's study again shows the benefit of cognitive aids, particularly in critical, time-sensitive situations. The anaesthesia and critical care community's historical resistance to decision-support tools requires challenge.

    Daniel Jolley  Daniel Jolley
     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…