Warning scores in triage – Is there any point?

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Warning scores in triage – Is there any point?

Les scores d’alerte dans le triage: Est-ce vraiment utile?

Sean B. Gottschalk

a,

*

_{, Chris Warner}

b

_{, Vanessa C. Burch}

c

_{, Lee A. Wallis}

a

Department of Emergency Medicine, University of Cape Town, Cape Town 8005, South Africa

b

Delft Community Health Centre, Cape Town, South Africa

c

Department of Medicine, University of Cape Town, Cape Town, South Africa Received 9 August 2011; revised 10 April 2012; accepted 10 April 2012 Available online 20 July 2012

KEYWORDS Emergency Centre; Warning score; MEWS; Triage

Abstract Introduction: The South African Triage Scale (SATS), a novel triage system for Emer-gency Centres, was initially proposed in 2006. The system incorporates an adapted version of the Modiﬁed Early Warning Score (MEWS).

Methods: A prospective study was conducted to evaluate the use of the MEWS as a triage tool in EC settings in the Western Cape, South Africa. A total of 1867 cases were prospectively assessed. The MEWS was correlated with Emergency Centre outcome

Results: The data show clear potential for use of the MEWS as a triage instrument for medical patients. Its use for trauma cases is more limited.

Conclusion: The MEWS in its un-adapted form is unsuitable as a uniﬁed triage scoring system for both medical and trauma cases in Emergency Centres.

* Corresponding author. Address: Department of Emergency Med-icine, University of Cape Town, Ravenscraig Road, Green Point, Cape Town 8005, South Africa. Tel.: +27 835800619.

E-mail address:chalk1@cybersmart.co.za(S.B. Gottschalk). Peer review under responsibility of African Federation for Emergency Medicine.

Production and hosting by Elsevier

African Federation for Emergency Medicine

African Journal of Emergency Medicine

www.afjem.com

www.sciencedirect.com

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KEYWORDS Emergency Centre; Warning score; MEWS; Triage

Abstract Introduction: L’ećhelle de triage d’Afrique du Sud (SATS), un nouveau syste`me de tri-age pour les centres d’urgence, a e´teínitiallementproposeé en 2006. Le syste`meinte`greune version adapteé du syste`med’alerteprećoce de modification (CHME).

Me´thodes: Unee´tude prospective a e´te´reáliseéafind’e´valuerl’utilisation du CHME en tantqu’outil de triage dans les centres d’urgencee´tablisdans la province du Cap Occidental, en Afrique du Sud. Un total de 1 867 cas a e´teé´value´prospectivement. La notation du CHME e´tait en corre´lation-avec lesre´sultats des centres d’urgence.

Re´sultats: Les donne´esmontrentunpotentiele´vident pour l’utilisation de la notation du CHME en tantqu’outil de triage pour les patients en me´decinege´ne´rale. Son utilisation pour les cas de traumat-ismesest plus limite´.

Conclusion: Le CHME, danssaforme non-adapteé, ne convient pas en tantquesyste`me de notation de triage unifie´ a` la fois pour la me´decinegeńe´rale et pour les cas de traumatismesdans les centres d’urgence.

African relevance

MEWS is easy to calculate.

MEWS uses simple parameters only.

Basic equipment only is required for the score calculation. Junior staff are able to calculate the score.

MEWS has been incorporated in the South African Triage Scale.

What’s new?

MEWS is useful for medical Emergency Centre (EC) triage. MEWS is predictive of hospital admission from the EC

(medical cases).

MEWS is not useful for trauma EC triage.

MEWS cannot be used for combined (medical + trauma) EC triage.

MEWS needs to be adapted for combined EC triage pur-poses (medicine + trauma).

Introduction

Triage in South Africa

Pre-hospital ambulance personnel in South Africa have been using a four-level colour-based triage system for many years.1 The system advocates prioritisation based on ‘physiological instability’. Wide discrepancies in triaging were common, how-ever, owing to lack of robust parameters deﬁning ‘instability’ and varying levels of personnel clinical expertise.2 _Similarly,

in hospital Emergency Centres (ECs) there was no standard-ised triage system; decisions regarding urgency of care were left to nursing staff and even receptionists (ﬁrst point of contact in ECs). Given these limitations, the Cape Triage Group (later the South African Triage Group) set about developing a simple triage tool for use in the pre-hospital and EC setting.3

The South African Triage Scale4uses a two-stage stepwise approach to assigning triage priority colour; this is based on simple physiological parameters as well as a list of readily iden-tiﬁable clinical presentations (e.g. chest pain). The physiologi-cal parameters used are based on the Modiﬁed Early Warning Score (MEWS) (Table 1). The MEWS has been shown to iden-tify medical patients at risk of acute deterioration and in-hospital death5–7as well as medical patients requiring admis-sion.8_{A concern regarding the MEWS as the basis for a triage}

tool is that it has not been adequately evaluated in ECs admit-ting both trauma and non-trauma (incl. medical and surgical) emergencies.9In a recent study it was shown that MEWS did not add any additional information to the Manchester Triage Score10when used in the EC setting; however, a comparison of the performance of the MEWS in trauma and non-trauma pa-tients was not reported.11

The purpose of this study was to evaluate the utility of the MEWS in an EC setting, analysing its predictive ability in trauma and non-trauma patients.

Methods

Study design and setting

A prospective observational study was conducted over a 2-month period in the ECs of two privately funded hospitals

Table 1 Modiﬁed Early Warning Score (MEWS).

3 2 1 0 1 2 3

Systolic BP <70 71–80 81–100 101–199 P200

Heart rate <40 41–50 51–100 101–110 111–129 P130

Respiratory rate <9 9–14 15–20 21–29 P30

Temperature <35 35–38.5 P38.5

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in Cape Town, South Africa.12Both hospitals admit both trau-ma and non-trautrau-ma patients to a single EC setting. MEWS on EC admission was correlated with EC outcome (in-hospital ward admission or discharge) for both trauma and non-trauma cases.

Study population

Patients were eligible for inclusion in the study if they were 16 years or older and presented as ‘ﬁrst visit’. Follow-up cases, direct referrals for hospital admission and patients booked for minor surgical procedures were excluded. Data were prospec-tively collected over 2 months.

Data collection

Nursing staff captured the following information on admission to the EC: respiratory rate, systolic blood pressure (DINA-MAP, GE Healthcare, ST Giles, UK), pulse, temperature (Sure-Temp, Welch-Allyn, USA) and level of consciousness (standard AVPU scale). MEWS was calculated based on these physiological parameters (Table 1). The primary endpoints of the study were EC discharge or admission to hospital, or death in the ED.

Statistical analysis

An internet database site was developed enabling multiple data-entry sites using a web-based interface. Data ﬁles were re-viewed by the principal investigator to check data capture completeness. Data were imported into Excel (Microsoft cor-poration, USA) and statistical analysis performed using Statis-tica V7 (Statsoft, Tulsa, USA).

MEWSs were analysed in four endpoint subgroups: trauma admissions, trauma discharges, non-trauma admissions and non-trauma discharges.

The Krusskal–Wallis (KW) test was used to determine if there was a difference between any of the four subgroups. A p-value of 0.05 or less was considered to be signiﬁcant.

The Mann–Whitney U (MWU) test was then used to com-pare each of the four subgroups against one another. A p-value of 0.008 or less was considered signiﬁcant (0.05 divided by 6 as six tests performed comparing each of the subgroups against one another).

Ethical considerations

Approval to conduct the study was granted by both the private hospital group as well as the Human Research Ethics Commit-tee of the University of Cape Town.

Results Demographics

A total of 1875 case records were captured on the database. Eight patients refused hospital treatment and were excluded from the study leaving 1867 records for analysis (1175 hospi-tal A and 692 hospihospi-tal B). Fifty-one percent of the sample was men; the median age was 39 years (range 16–94). A total of 74% of cases were between the ages of 20–59 years. A total of 562 cases (30%) were trauma-related EC visits. Twenty-seven percent of the total sample was admitted. There were 3 EC deaths which were grouped with the admissions. 1.1 1.8 1.6 2.7 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Non-Trauma Admit Non-Trauma D/C Trauma Admit Trauma D/C Scor e

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Patient outcome vs. MEWS

The mean MEWS for trauma admissions was 1.8 vs. 1.1 for discharges; the non-trauma admissions scored a mean MEWS of 2.8 vs. a discharge mean of 1.6 points. The mean MEWS for admissions was signiﬁcantly greater than for discharged patients in both the trauma and non-trauma groups (p < 0.001). Comparison of the mean MEWS of trauma admissions and non-trauma admissions shows that trauma cases scored signiﬁcantly less than non-trauma (p < 0.001); this was also the case comparing the trauma vs. non-trauma discharge groups (p < 0.001). Furthermore, the mean MEWS of trauma admissions was similar to that of non-trauma discharges from the EC (p = 0.037) (Fig. 1).

Percentage endpoints reached

The percentage endpoints achieved (i.e. admissions) climbed progressively with an increasing MEWS. Endpoints reached were 100% from a MEWS of 7 upwards.

Discussion

The value of the MEWS in triage has been questioned,11 par-ticularly as an addition to current systems such as the Man-chester Triage Score (MTS).10 However, the MTS is being used in a mature system with different stafﬁng and case-mix to our environment. The South African Triage Group set out to design a concise triage tool which junior staff were capa-ble of using, hence the interest in the MEWS.

In this study, the EC outcome was used as a proxy marker of illness acuity. The original MEWS on EC presentation was correlated with the EC outcome. The MEWS was originally designed as a warning tool for medical in-patients5; its exten-sion to non-trauma cases in the EC seems to be a viable option. An under-triage rate of 15% in rural South Africa has recently been reported for the MEWS in triage for cases requiring admission.13_{The MEWS was not originally designed to assess}

trauma cases; it certainly seems to be less successful in this re-gard (overall underscoring). If used in a mixed EC environ-ment as a lone triage tool, the trauma cases would be underscored and therefore under-triaged in relation to the medical cases. The tool can therefore not be used as a uniﬁed instrument for both medical and trauma cases in triage in its original format. However, a graduated increase in admission rate with increasing MEWS is evident, an important quality for a scoring system in a triage setting.

Despite potential as a medical triage tool, further work needs to be done to adapt the MEWS to function effectively in a mixed Emergency Centre environment.

Due to the weakness of the MEWS in its original form, there appears to be a need to modify it for use in triage. The MEWS has been signiﬁcantly modiﬁed in the SATS(4); further improvements have been proposed and will be described in future.

Limitations

As outcome measures were grouped, deﬁnitive conclusions may be difﬁcult to draw from small numbers of critically ill cases.

This study was done on cases age 16 or older. The MEWS is not a paediatric score in its current format. A modiﬁed ver-sion is used in the child SATS.4

Conclusions

In the private sector setting in South Africa, MEWS predicts in-patient admission from the Emergency Centre. This works reasonably well for medical patients. It is less effective for trau-ma cases. In its original form MEWS is not suitable as a com-bined triage early warning tool.

Competing interests None.

Contributors

S.G. – Conceived the idea, wrote the ﬁrst draft; C.W. – techni-cal data analysis; All authors contributed to the ﬁnal draft; S.G. is the guarantor of the paper.

Funding

There was no external funding.

Acknowledgements

The Medi-Clinic Group and their respective heads of unit, Drs. Bonner and Kow, for participation in this study.

Mr. A. Melzer of Eighty20 data management company for set-ting up the website and hosset-ting the database website: http:// www.eighty20.co.za/ accessed December 2010.

Mr. A.R. Sayed, Senior Biostatistician, Faculty of Health Sci-ences, University of Cape Town for assistance on statistical data analysis.

Welch-Allyn for sponsorship of Sure-Temp thermometers.

Appendix A. Short answer questions

1. Warning Scores are used primarily to detect deterioration of the following group of patients:

a. EC trauma cases b. All EC cases

c. Medical hospital in-patients d. Medical staff

e. EC procedural cases

2. The MEWS in EC triage is shown to be a predictive tool in the following:

a. EC Hospital admission of trauma cases b. EC Hospital admission of medical cases

c. EC discharge of trauma cases d. EC hospital admission of all cases

e. EC ICU admission of trauma cases

3. In its unaltered format, the MEWS can be used as a triage tool for Emergency Centres

a. True b. False

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References

1. Mac Mahon AG. Sorting out triage in urban disasters. SAMJ 1985;67(4):555–6.

2. Gottschalk SB. Triage – a South African perspective. CME SA J CPD Emerg Med2004;22(6):325–7.

3. Gottschalk SB, Wood D, DeVries S, et al. The Cape triage score: a new triage system for South Africa. Proposal from the Cape triage group. Emerg Med J 2006;23(2):149–53.http://dx.doi.org/ 10.1136/emj.2005.028332.

4. Emergency Medicine society of South Africa homepage on the Internet. Cape Town, SA; 2009 [cited February 2012]. South African Triage Scale. Available from:<http://emssa.org.za/sats/>. 5. Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modiﬁed early warning score in medical admissions. QJM 2001;94(10):521–6.

6. Buist M, Berbard S, Nguyen TV, et al. Association between clinically abnormal observations and subsequent in-hospital mortality: a prospective study. Resuscitation 2004;62(2): 137–41.

7. Goldhill DR, McNarry AF. Physiological abnormalities in early warning scores are related to mortality in adult patients. Br J Anaesth2004;92(6):882–4.

8. Burch VC, Tarr G, Morroni C. Modiﬁed early warning score predicts the need for hospital admission and in hospital mortality. Emerg Med J2008;25(10):674–8.

9. Bruijns SR, Wallis LA, Burch VC. A prospective evaluation of the Cape triage score in the emergency department of an urban public hospital in South Africa. Emerg Med J 2008;25(7):398–402. 10. Manchester Triage Group. Emergency triage. Manchester: BMJ

Publishing Group; 1997.

11. Subbe CP, Slater A, Menon D, et al. Validation of physiological scoring systems in the accident and emergency department. Emerg Med J2006;23(11):841–5.

12. Gottschalk SB. Evaluation of the modiﬁed early warning score as a triage instrument in the Western Cape private health care setting. University of Cape Town, M.Phil. degree; 2007.

13. Rosedale K, Smith AZ, Wood D. The effectiveness of the South African Triage Score (SATS) in a rural emergency department. SAMJ2011;101:537–40.