An electronic sepsis surveillance system (ESSV) was developed to identify severe sepsis and determine its time of onset. ESSV sensitivity and specificity were evaluated during an 11-day prospective pilot and a 30-day retrospective trial. ESSV diagnostic alerts were compared with care team diagnoses and with administrative records, using expert adjudication as the standard for comparison. ESSV was 100% sensitive for detecting severe sepsis but only 62.0% specific. During the pilot, the software identified 477 patients, compared with 18 by adjudication. In the 30-day trial, adjudication identified 164 severe sepsis patients, whereas ESSV detected 996. ESSV was more sensitive but less specific than care team or administrative data. ESSV-identified time of severe sepsis onset was a median of 0.00 hours later than adjudication (interquartile range = 0.05). The system can be a useful tool when implemented appropriately but lacks specificity, largely because of its reliance on discreet data fields.

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IntroductionAll aspects of medical training have experienced an exponential acceleration in the application of technology for learning needs.1 Research promotes the use of high fidelity models and ever more complex training methods with organisations keen to adopt and implement new technology. Models are utilised to minimise potential risks to patients through bedside learning and refine established technique.2 Simulation practice can also be used to develop non-technical skills pertinent to safe clinical practice.2–4 Simulation training can be employed from early stages of undergraduate education through to use in professional postgraduate exams giving a large scope of use in a multiplicity of environments.1 4 5MethodsForty Foundation Year 1 Doctors were taught clinical skills utilising Low fidelity part task training models. Four clinical skills were selected from pre-determined postgraduate curricula. Self assessment pre and post procedure were recorded with qualitative feedback sought as a secondary measure.ResultsGlobal increases are seen across 4 sampled clinical skills. Participants self-reported increased confidence and competence. A high value was placed upon trainees perceived value in training.ConclusionFidelity has been shown to play an integral role in simulation.4 The authors conclude that simple part task trainers, low fidelity models, still have a valuable part to play in medical education. They remain cost effective, adaptable and accessible training tools in the era of increasing complexity.1 5 Simulation provides a safe space to develop both technical and non-technical aspects.3 4 Low fidelity simulation can be used to underpin the learning objectives of trainees through effective feedback in real time, access to repetitive practice and remain a feasible training tool for trainers and trainees alike.2 4 High fidelity simulation should not be excluded completely however appears to be best suited to defined roles in more complex moulage.1 4Take home messageTechnology has the ability to improve and evolve medical education. With the potential for increased feedback, self and peer assessment along with pragmatic assessment, simulation has firmly entrenched itself in medical education. Care should be taken however not to disregard lower fidelity models as they still provide proven effective learning, enable the teaching of non-technical skills and facilitate knowledge delivery.ReferencesSarmah P, et al. Low vs. high fidelity: the importance of ‘realism’ in the simulation of a stone treatment procedure. Curr Opin Urol 2017;27(4):316–322.Naik VN, Brein SE. Review article: simulation: a means to address and improve patient safety. Can J Anaesth 2013;60(2):192–200.Aebersold M. The history of simulation and its impact on the future. AACN Adv Crit Care 2016;27(1):56–61.Lewis R, Strachan A, Smith MM. Is high fidelity simulation the most effective method for the development of non-technical skills in nursing? A review of the current evidence. Open Nurs J 2012;6:82–89.Aggarwal R, et al. Training and simulation for patient safety. Qual Saf Health Care 2010;19(Suppl 2):i34–i43.

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