24,607 research outputs found

    SEND: a system for electronic notification and documentation of vital sign observations

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    Background: Recognising the limitations of a paper-based approach to documenting vital sign observations and responding to national clinical guidelines, we have explored the use of an electronic solution that could improve the quality and safety of patient care. We have developed a system for recording vital sign observations at the bedside, automatically calculating an Early Warning Score, and saving data such that it is accessible to all relevant clinicians within a hospital trust. We have studied current clinical practice of using paper observation charts, and attempted to streamline the process. We describe our user-focussed design process, and present the key design decisions prior to describing the system in greater detail. Results: The system has been deployed in three pilot clinical areas over a period of 9 months. During this time, vital sign observations were recorded electronically using our system. Analysis of the number of observations recorded (21,316 observations) and the number of active users (111 users) confirmed that the system is being used for routine clinical observations. Feedback from clinical end-users was collected to assess user acceptance of the system. This resulted in a System Usability Scale score of 77.8, indicating high user acceptability. Conclusions: Our system has been successfully piloted, and is in the process of full implementation throughout adult inpatient clinical areas in the Oxford University Hospitals. Whilst our results demonstrate qualitative acceptance of the system, its quantitative effect on clinical care is yet to be evaluated

    A manifesto for a socio-technical approach to NHS and social care IT-enabled business change - to deliver effective high quality health and social care for all

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    80% of IT projects are known to fail. Adopting a socio-technical approach will help them to succeed in the future. The socio-technical proposition is simply that any work system comprises both a social system (including the staff, their working practices, job roles, culture and goals) and a technical system (the tools and technologies that support and enable work processes). These elements together form a single system comprising interacting parts. The technical and the social elements need to be jointly designed (or redesigned) so that they are congruent and support one another in delivering a better service. Focusing on one aspect alone is likely to be sub-optimal and wastes money (Clegg, 2008). Thus projects that just focus on the IT will almost always fail to deliver the full benefits

    Enabling ubiquitous data mining in intensive care: Features selection and data pre-processing

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    Ubiquitous Data Mining and Intelligent Decision Support Systems are gaining interest by both computer science researchers and intensive care doctors. Previous work contributed with Data Mining models to predict organ failure and outcome of patients in order to support and guide the clinical decision based on the notion of critical events and the data collected from monitors in real-time. This paper addresses the study of the impact of the Modified Early Warning Score, a simple physiological score that may allow improvements in the quality and safety of management provided to surgical ward patients, in the prediction sensibility. The feature selection and data pre-processing are also detailed. Results show that for some variables associated to this score the impact is minimal.Fundação para a Ciência e a Tecnologia (FCT

    Risk of acute deterioration and care complexity individual factors associated with health outcomes in hospitalised patients with COVID-19: a multicentre cohort study

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    Background: Evidence about the impact of systematic nursing surveillance on risk of acute deterioration of patients with COVID-19 and the effects of care complexity factors on inpatient outcomes is scarce. The aim of this study was to determine the association between acute deterioration risk, care complexity factors and unfavourable outcomes in hospitalised patients with COVID-19. Methods: A multicentre cohort study was conducted from 1 to 31 March 2020 at seven hospitals in Catalonia. All adult patients with COVID-19 admitted to hospitals and with a complete minimum data set were recruited retrospectively. Patients were classified based on the presence or absence of a composite unfavourable outcome (in-hospital mortality and adverse events). The main measures included risk of acute deterioration (as measured using the VIDA early warning system) and care complexity factors. All data were obtained blinded from electronic health records. Multivariate logistic analysis was performed to identify the VIDA score and complexity factors associated with unfavourable outcomes. Results: Out of a total of 1176 patients with COVID-19, 506 (43%) experienced an unfavourable outcome during hospitalisation. The frequency of unfavourable outcomes rose with increasing risk of acute deterioration as measured by the VIDA score. Risk factors independently associated with unfavourable outcomes were chronic underlying disease (OR: 1.90, 95% CI 1.32 to 2.72; p<0.001), mental status impairment (OR: 2.31, 95% CI 1.45 to 23.66; p<0.001), length of hospital stay (OR: 1.16, 95% CI 1.11 to 1.21; p<0.001) and high risk of acute deterioration (OR: 4.32, 95% CI 2.83 to 6.60; p<0.001). High-tech hospital admission was a protective factor against unfavourable outcomes (OR: 0.57, 95% CI 0.36 to 0.89; p=0.01). Conclusion: The systematic nursing surveillance of the status and evolution of COVID-19 inpatients, including the careful monitoring of acute deterioration risk and care complexity factors, may help reduce deleterious health outcomes in COVID-19 inpatients
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