Literature DB >> 29894258

Limitations of track and trigger systems and the National Early Warning Score. Part 1: areas of contention.

Steven Grant1.   

Abstract

Evidence suggests that the identification and response to the deteriorating patient continues to be an ongoing concern, despite the widespread use of track and trigger score (TTS) systems. This article discusses the variations in the parameters included in the different TTS systems in use across the NHS and their sensitivity. Clinical guidelines and physiological theory are used to appraise the parameters allocated in the National Early Warning Score (NEWS 1 and 2), highlighting potential limitations of the tool. The findings lead to the conclusion that registered nurses should not rely solely on NEWS, but should use it to support their clinical judgement.

Entities:  

Keywords:  Acutely ill patients; Deteriorating patient; Haemodynamic observations; National Early Warning Score; Track and trigger systems; Vital signs

Mesh:

Year:  2018        PMID: 29894258     DOI: 10.12968/bjon.2018.27.11.624

Source DB:  PubMed          Journal:  Br J Nurs        ISSN: 0966-0461


  5 in total

1.  Implementation of the National Early Warning Score in UK care homes: a qualitative evaluation.

Authors:  Siân Russell; Rachel Stocker; Robert Oliver Barker; Jennifer Liddle; Joy Adamson; Barbara Hanratty
Journal:  Br J Gen Pract       Date:  2020-10-29       Impact factor: 5.386

2.  Selecting intervention content to target barriers and enablers of recognition and response to deteriorating patients: an online nominal group study.

Authors:  Duncan Smith; Martin Cartwright; Judith Dyson; Jillian Hartin; Leanne M Aitken
Journal:  BMC Health Serv Res       Date:  2022-06-10       Impact factor: 2.908

3.  What items should be included in an early warning score for remote assessment of suspected COVID-19? qualitative and Delphi study.

Authors:  Trisha Greenhalgh; Paul Thompson; Sietse Weiringa; Ana Luisa Neves; Laiba Husain; Merlin Dunlop; Alexander Rushforth; David Nunan; Simon de Lusignan; Brendan Delaney
Journal:  BMJ Open       Date:  2020-11-12       Impact factor: 2.692

4.  Comparing the prehospital NEWS with in-hospital ESI in predicting 30-day severe outcomes in emergency patients.

Authors:  Peyman Saberian; Atefeh Abdollahi; Parisa Hasani-Sharamin; Maryam Modaber; Ehsan Karimialavijeh
Journal:  BMC Emerg Med       Date:  2022-03-14

5.  Explainable machine learning for real-time deterioration alert prediction to guide pre-emptive treatment.

Authors:  Aida Brankovic; Hamed Hassanzadeh; Norm Good; Kay Mann; Sankalp Khanna; Ahmad Abdel-Hafez; David Cook
Journal:  Sci Rep       Date:  2022-07-11       Impact factor: 4.996

  5 in total

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