Abstract
Acute hospital wards in the UK are required to use Early Warning Scoring (EWS) systems to monitor patients’ vital-signs. These are often paper-based, and involve the use of heuristics to score the vital signs which are measured every 2-4 hours by nursing staff. If these scores exceed pre-defined thresholds, the patient is deemed to be at risk of deterioration. In this paper we compare the performance of EWS systems, that use different approaches to score abnormal vital-signs, to identify acutely-ill patients, while attending the Emergency Department (ED). We incorporate the use of data acquired from bed-side monitors into the EWS system, thereby offering the possibility of performing patient observations automatically, between manual observations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
NICE: Acutely ill patients in hospital, CG50 (2007), http://www.nice.org.uk/
Gao, H., McDonnell, A., Harrison, D.A., Moore, T., Adam, S., Daly, K., Esmonde, L., Goldhill, D.R., Parry, G.J., Rashidian, A., Subbe, C.P., Harvey, S.: Systematic review and evaluation of physiological track and trigger warning systems for identifying at-risk patients on the ward. Intensive Care Medicine 33(4), 667–679 (2007)
Kyriacos, U., Jelsma, J., Jordan, S.: Monitoring vital signs using early warning scoring systems: a review of the literature. Journal of Nursing Management 19(3), 311–330 (2011)
Tsien, C.L., Fackler, J.C.: Poor prognosis for existing monitors in the intensive care unit. Critical Care Medicine 25(4), 614–619 (1997)
DeVita, M., Braithwaite, R., Mahidhara, R., Stuart, S., Foraida, M., Simmons, R.: Use of medical emergency team responses to reduce hospital cardiopulmonary arrests. Quality & Safety in Health Care 13(4), 251–254 (2004)
Etter, R., Ludwig, R., Lersch, F., Takala, J., Merz, T.: Early prognostic value of the medical emergency team calling criteria in patients admitted to intensive care from the emergency department. Critical Care Medicine 36(3), 775–781 (2008)
Subbe, C.P., Kruger, M., Rutherford, P., Gemmel, L.: Validation of a modified early warning score in medical admissions. QJM: Monthly Journal of the Association of Physicians 94(10), 521–526 (2001)
Clifton, D.A., Wong, D., Fleming, S., Wilson, S.J., Way, R., Pullinger, R., Tarassenko, L.: Novelty detection for identifying deterioration in emergency department patients. In: Yin, H., Wang, W., Rayward-Smith, V. (eds.) IDEAL 2011. LNCS, vol. 6936, pp. 220–227. Springer, Heidelberg (2011)
Tarassenko, L., Clifton, D.A., Pinsky, M.R., Hravnak, M.T., Woods, J.R., Watkinson, P.J.: Centile-based early warning scores derived from statistical distributions of vital signs. Resuscitation 82(8), 1013–1018 (2011)
RCP London: National early warning score (NEWS): standardising the assessment of acute-illness severity in the NHS - report of a working party (2012)
Tarassenko, L., Hann, A., Young, D.: Integrated monitoring and analysis for early warning of patient deterioration. British Journal of Anaesthesia 97(1), 64–68 (2006)
Clifton, D., Wong, D., Clifton, L., Wilson, S., Way, R., Pullinger, R., Tarassenko, L.: A large-scale clinical validation of an integrated monitoring system in the emergency department. IEEE Journal of Biomedical and Health Informatics 17(4), 835–842 (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Santos, M.D., Clifton, D.A., Tarassenko, L. (2014). Performance of Early Warning Scoring Systems to Detect Patient Deterioration in the Emergency Department. In: Gibbons, J., MacCaull, W. (eds) Foundations of Health Information Engineering and Systems. FHIES 2013. Lecture Notes in Computer Science, vol 8315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53956-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-53956-5_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-53955-8
Online ISBN: 978-3-642-53956-5
eBook Packages: Computer ScienceComputer Science (R0)