Elsevier

Resuscitation

Volume 70, Issue 2, August 2006, Pages 173-178
Resuscitation

Clinical paper
Calculating early warning scores—A classroom comparison of pen and paper and hand-held computer methods

https://doi.org/10.1016/j.resuscitation.2005.12.002Get rights and content

Summary

To assist in the early detection of critical illness, many hospitals now use a “track and trigger” system that allocates points to routine vital signs measurements on the basis of their derangement from an arbitrarily agreed “normal” range. These points are summed to provide an early warning score (EWS). Little is known about the accuracy with which EWS are calculated and charted. We compared the speed and accuracy of charting the weighted value attributed to each vital sign, and of calculating the EWS, using the traditional pen and paper method with that using a specially programmed, personal digital assistant (VitalPAC™). Incorrect entries or omissions occurred in 24 (29%) of 84 EWS computed using pen/paper compared to 8 (10%) computed using the VitalPAC™ method. Fewer incorrect clinical actions were indicated using EWS derived via the VitalPAC™ method (4/84, 5%) than from those calculated using pen/paper (12/84, 14%). The mean time (±S.D.) taken for participants to calculate and chart a set of weighted values and EWS using the pen/paper method was 67.6 ± 35.3 s (n = 84). The corresponding time taken to enter a set of physiological data using the VitalPAC™ was 43.0 ± 23.5 s (n = 84). By comparison with the conventional pen/paper method, the use of VitalPAC™ was on average 1.6-times faster. The use of a device such as VitalPAC™ offers significant advantages both in speed and accuracy of recording of EWS.

Introduction

In recent years, the focus in managing critically ill patients has been on the prompt recognition of clinical deterioration and early treatment outside critical care units.1, 2, 3, 4, 5, 6 To assist in the early detection of critical illness, many hospitals now use a “track and trigger” system that allocates points to routine vital signs measurements on the basis of their derangement from an arbitrarily agreed “normal” range.7, 8, 9, 10 These points are summed to provide an early warning score (EWS). The weighted value of one or more individual vital signs measurements or, more usually, the EWS is often used to suggest an alteration in the frequency of vital signs monitoring to nurses, or to call ward doctors or critical care outreach teams to the patient.

Little is known about the accuracy with which EWS are calculated and charted, although individual physiological variables, such as heart rate, blood pressure and temperature are often measured accurately using regularly calibrated, electronic devices. Over-scoring may lead to the unnecessary calling of medical staff such that the use of an EWS system may fall into disrepute. Underscoring may lead to a delay in the detection of patient deterioration.

The process by which an EWS is obtained requires several complex activities. It involves the accurate collection of raw vital signs data, the correct ascription of a weighted value according to the degree of physiological derangement and the arithmetic addition of weighted values to form an EWS. Each of these stages can introduce error, which may influence the EWS. Errors may also occur in the transcription of raw or derived data on to paper charts.

Our hospital has developed a system for direct input of vital signs data into handheld personal digital assistants (PDA), linked via wi-fi to a central computer. The system is in use in the Medical Assessment Unit of the hospital and is being introduced to other clinical areas. It permits the rapid calculation of an EWS from raw physiological data, without the need for healthcare staff to know or consult EWS weightings. All raw physiological data, weighted values and EWS are stored on the central computer, with the PDA acting as a data input device. An up-to-date vital signs chart for any patient can be viewed on the PDA at any time.

In this classroom study we compared the speed and accuracy of charting the weighted value attributed to each vital sign, and of calculating an EWS, using the traditional pen and paper method with that using the PDA (VitalPAC™). We also assessed nurses’ preference for each system.

Section snippets

Method

Twenty-one nurses working in the Medical Assessment Unit of Queen Alexandra Hospital, Portsmouth agreed to participate in the study. All were familiar with the EWS used in the study, as this has been employed routinely in the hospital for over 3 years. The study involved the entry and charting of five different, fictitious, physiological vital signs datasets, each of which included measurements of heart rate, blood pressure, temperature, respiratory rate, urine output and neurological status.

Results

After removal of the first vital signs dataset for each technique a total of 168 (84 VitalPAC™; 84 pen/paper) dataset entries were available for analysis. As each dataset contained six individual physiological variables, participants were expected to process 504 (84 × 6) values and derive 84 EWS using each method.

Discussion

Government and Royal College sponsored publications 5, 6, 11, 12, 13, 14 in England and Wales strongly advocate the use of an EWS system as an adjunct to identifying and managing acutely ill patients. However, there is no published evidence about the accuracy with which clinical staff calculate and record EWS, or the time taken in so doing. The issue of accuracy is particularly important as EWS systems have been widely adopted with little validation, clinical responses have been linked to

Conflicts of interest

VitalPAC™ is a collaborative development of the Learning Clinic and Portsmouth Hospitals NHS Trust.

Acknowledgements

The authors wish to acknowledge the assistance of the MAU staff at Portsmouth Hospitals Trust for participating in the study and for the Department of Information & Communication Technologies for their support.

References (19)

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

Cited by (109)

  • The prevalence and management of deteriorating patients in an Australian emergency department

    2021, Australasian Emergency Care
    Citation Excerpt :

    An outcome which appears to be positive but is also associated with increased workload for staff and members of the response team [19]. Furthermore, multi parameter systems (e.g. NEWS) require some minor calculations which can be prone to user error up to 29% of the time [20]. While the implementation of RRS in the general ward area is well established, the application of a standard approach to a modified ED RRS is an emerging area of interest in the literature [8,21–25].

  • The effect of fractional inspired oxygen concentration on early warning score performance: A database analysis

    2019, Resuscitation
    Citation Excerpt :

    EWS systems are well established in the UK, with the heuristically developed NEWS being used in 75% of NHS hospitals.10,12 Since then, digital EWS platforms have been developed, meaning complex algorithms using vital sign observation sets can be introduced without increasing calculation error.14,22 NEWS2 is a new score being adopted nationally in the UK.

  • Short National Early Warning Score — Developing a Modified Early Warning Score

    2018, Australian Critical Care
    Citation Excerpt :

    Therein, both systems showed an excellent discriminating capability to the outcomes survival vs unanticipated intensive care unit admission (UICUA) and survival vs death.16 Some studies suggest that the collection of all the necessary data to complete EWS scores in short periods may be time consuming for health professionals.17–20 In addition, the absence of missing values or errors in these vital signs records are essential and may have consequences in the EWS use.16–18,21,22

View all citing articles on Scopus

A Spanish translated version of the summary of this article appears as Appendix in the online version at doi:10.1016/j.resuscitation.2005.12.002

View full text