Abstract

Augmenting clinical decision-making in intensive care

This report presents the outputs of a week-long collaboration between The Alan Turing Institute and Great Ormond Street Hospital. The purpose was to scope how vital signs monitoring data can be better used to inform the removal of a breathing tube (i.e. ‘extubation’) in intensive care units (ICUs). The main objectives were evaluating the effectiveness of different modelling methods for predicting whether an extubation attempt was successful (a failed attempt was defined as re-intubation within 48 hours of attempted extubation).

Citation information

Data Study Group team. (2020, February 17). Data Study Group Final Report: Great Ormond Street Hospital. Zenodo. http://doi.org/10.5281/zenodo.3670726

Additional information

Evangelos Kafantaris, University of Edinburgh
Farhad Hatami, Lancaster University
Hareem Naveed, MunichRe
Jialin Yi, London School of Economics
Jo French, Health Data Insight
Leigh Shlomovich, Imperial College London
Magda Bucholc, Ulster University
Markus Loning, UCL
Ming Li
Oliver Crook, University of Cambridge
Pablo Leon Villagra, Edinburgh University
Piotr Oleskiewicz, Durham University,

Ben Margetts, Great Ormond Street Hospital.
Christina Pagel, UCL’s Clinical Operational Research Unit (CORU)
John Booth, Great Ormond Street Hospital.
Samiran Ray, Great Ormond Street Hospital

 

Turing affiliated authors