Performance of externally validated enhanced computer-aided versions of the National Early Warning Score in predicting mortality following an emergency admission to hospital in England: a cross-sectional study

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dc.contributor.authorFaisal, Muhammad
dc.contributor.authorRichardson, Donald
dc.contributor.authorScally, Andy
dc.contributor.authorHowes, Robin
dc.contributor.authorBeatson, Kevin
dc.contributor.authorMohammed, Mohammed
dc.contributor.funderHealth Foundationen
dc.contributor.funderNational Institute for Health Researchen
dc.date.accessioned2019-12-04T12:14:53Z
dc.date.available2019-12-04T12:14:53Z
dc.date.issued2019-11-02
dc.description.abstractObjectives: In the English National Health Service, the patient’s vital signs are monitored and summarised into a National Early Warning Score (NEWS) to support clinical decision making, but it does not provide an estimate of the patient’s risk of death. We examine the extent to which the accuracy of NEWS for predicting mortality could be improved by enhanced computer versions of NEWS (cNEWS). Design: Logistic regression model development and external validation study. Setting: Two acute hospitals (YH—York Hospital for model development; NH—Northern Lincolnshire and Goole Hospital for external model validation). Participants: Adult (≥16 years) medical admissions discharged over a 24-month period with electronic NEWS (eNEWS) recorded on admission are used to predict mortality at four time points (in-hospital, 24 hours, 48 hours and 72 hours) using the first electronically recorded NEWS (model M0) versus a cNEWS model which included age+sex (model M1) +subcomponents of NEWS (including diastolic blood pressure) (model M2). Results: The risk of dying in-hospital following emergency medical admission was 5.8% (YH: 2080/35 807) and 5.4% (NH: 1900/35 161). The c-statistics for model M2 in YH for predicting mortality (in-hospital=0.82, 24 hours=0.91, 48 hours=0.88 and 72 hours=0.88) was higher than model M0 (in-hospital=0.74, 24 hours=0.89, 48 hours=0.86 and 72 hours=0.85) with higher Positive Predictive Value (PPVs) for in-hospital mortality (M2 19.3% and M0 16.6%). Similar findings were seen in NH. Model M2 performed better than M0 in almost all major disease subgroups.Conclusions: An externally validated enhanced computer-aided NEWS model (cNEWS) incrementally improves on the performance of a NEWS only model. Since cNEWS places no additional data collection burden on clinicians and is readily automated, it may now be carefully introduced and evaluated to determine if it can improve care in hospitals that have eNEWS systems.en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.articleide031596en
dc.identifier.citationFaisal, M., Richardson, D., Scally, A., Howes, R., Beatson, K. and Mohammed, M. (2019) 'Performance of externally validated enhanced computer-aided versions of the National Early Warning Score in predicting mortality following an emergency admission to hospital in England: a cross-sectional study', BMJ Open, 9(11), e031596. (8pp.) doi: 10.13128/Phe_Mi-26070en
dc.identifier.doi10.13128/Phe_Mi-26070en
dc.identifier.eissn2239-4028
dc.identifier.endpage8en
dc.identifier.issn2280-7853
dc.identifier.issued11en
dc.identifier.journaltitlePhenomenology and Minden
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/9323
dc.identifier.volume9en
dc.language.isoenen
dc.publisherFirenze University Pressen
dc.rights©Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en
dc.subjectPerformanceen
dc.subjectComputer-aideden
dc.subjectNational Early Warning Scoreen
dc.subjectPredicting mortalityen
dc.titlePerformance of externally validated enhanced computer-aided versions of the National Early Warning Score in predicting mortality following an emergency admission to hospital in England: a cross-sectional studyen
dc.typeArticle (peer-reviewed)en
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