Elsevier

Resuscitation

Volume 81, Issue 8, August 2010, Pages 932-937
Resuscitation

Clinical paper
ViEWS—Towards a national early warning score for detecting adult inpatient deterioration

https://doi.org/10.1016/j.resuscitation.2010.04.014Get rights and content

Abstract

Aim of study

To develop a validated, paper-based, aggregate weighted track and trigger system (AWTTS) that could serve as a template for a national early warning score (EWS) for the detection of patient deterioration.

Materials and methods

Using existing knowledge of the relationship between physiological data and adverse clinical outcomes, a thorough review of the literature surrounding EWS and physiology, and a previous detailed analysis of published EWSs, we developed a new paper-based EWS – VitalPAC™ EWS (ViEWS). We applied ViEWS to a large vital signs database (n = 198,755 observation sets) collected from 35,585 consecutive, completed acute medical admissions, and also evaluated the comparative performance of 33 other AWTTSs, for a range of outcomes using the area under the receiver-operating characteristics (AUROC) curve.

Results

The AUROC (95% CI) for ViEWS using in-hospital mortality with 24 h of the observation set was 0.888 (0.880–0.895). The AUROCs (95% CI) for the 33 other AWTTSs tested using the same outcome ranged from 0.803 (0.792–0.815) to 0.850 (0.841–0.859). ViEWS performed better than the 33 other AWTTSs for all outcomes tested.

Conclusions

We have developed a simple AWTTS – ViEWS – designed for paper-based application and demonstrated that its performance for predicting mortality (within a range of timescales) is superior to all other published AWTTSs that we tested. We have also developed a tool to provide a relative measure of the number of “triggers” that would be generated at different values of EWS and permits the comparison of the workload generated by different AWTTSs.

Introduction

In 2007, the National Institute for Health and Clinical Excellence (NICE) recommended that physiological track and trigger systems (TTS), which employ multiple-parameter or aggregate weighted scoring systems, should be used to monitor all adult patients in acute hospital settings to facilitate the recognition of patient deterioration and a timely escalation of care.1 NICE also recommended that the chosen system should measure heart rate, respiratory rate, systolic blood pressure, level of consciousness, oxygen saturation and temperature.1 In the UK, the majority of hospitals using a TTS use an aggregate weighted scoring system (AWTTS), generally derived from that described by Morgan in 1997.2 However, there is considerable variation in the variables included and the weightings assigned and these are, generally, largely based on clinical experience and intuition.3 There is also considerable variation in their performance.3

The report of the Acute Medicine Task Force of the Royal College of Physicians of London (RCPL) recommended that “… physiological assessment of all patients should be standardised across the NHS with the recording of a minimum clinical data set result in an NHS early warning (NEW) score …”4 Our research efforts3, 5, 6 have been focused on the development of a validated, computer-based, early warning score (EWS) for deployment in the VitalPAC™ system7 which is a collaborative development between Portsmouth Hospitals and The Learning Clinic Ltd. (7 Lyric Square London W6 0ED). VitalPAC™ has given us a wealth of data and insight into the relationship between physiological data and adverse clinical outcomes.

On the basis that not all hospitals yet use electronic charting systems, we felt it might be useful to use our experience and data to develop a freely available, paper-based, EWS that could, perhaps, serve as a template for a national EWS (nEWS) as recommended by the RCPL.4

Section snippets

Method

Local research ethics committee approval was obtained for this study.

Results

During the study period, there were 39,992 patient episodes. On 4407 occasions (11%), the patient was considered well enough to be discharged from hospital before midnight on the day of admission. This left a total of 35,585 patient episodes (male: 17,059, 47.9%), where the patient either died in hospital or stayed in hospital past midnight on their admission day. From these 35,585 patient episodes, 198,755 vital signs datasets (male 94,376, 47.5%) were obtained. The mean (median) ages of the

Discussion

This paper describes the development of a new AWTTS – ViEWS – and its application to a large vital signs database from unselected acute medical admissions to an MAU. It presents the ability of ViEWS to discriminate death at a range of times post-vital signs observation (and therefore post-EWS) and also presents a comparison with other existing published AWTTSs. The AUROC value obtained for ViEWS of 0.888 (95% CI 0.880–0.895), when using in-hospital mortality within 24 h of the observation set as

Conclusions

Whilst the very large database of vital signs used in this study was collected using a computer-based system at the point of care, we have developed a simple, AWTTS – ViEWS – designed for paper-based application. We have demonstrated that its performance for predicting mortality (within a range of timescales) is superior to all other published AWTTSs that we tested. We have also developed a tool to provide a relative measure of the number of “triggers” that would be generated at different

Conflict of interest statement

The electronic vital signs data gathering system used in this study, VitalPAC™, is a collaborative development of The Learning Clinic Ltd and Portsmouth Hospitals NHS Trust. The wives of both Professor Smith and Dr Prytherch hold shares in The Learning Clinic Ltd. Dr Schmidt is a director of a UK registered company that holds a minority shareholding in The Learning Clinic Ltd.

Acknowledgements

The authors would like to acknowledge the help and support of the nursing and medical staff from Portsmouth Hospitals NHS Trust who collected the vital signs used in this study and The Learning Clinic Ltd., whose system, VitalPAC™, was essential to the collection of the vital signs database.

References (16)

There are more references available in the full text version of this article.

Cited by (411)

View all citing articles on Scopus

A Spanish translated version of the abstract of this article appears as Appendix in the online version at doi:10.1016/j.resuscitation.2010.04.014.

View full text