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CLINICAL EVIDENCE GUIDE

EARLY WARNING SCORES Early warning scores can help you know when the first signs of patient deterioration appear — so you can intervene faster.

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NEWS

OVERVIEW

MEWS

SEWS

WEWS

REFERENCES

2

TABLE OF CONTENTS

TABLE OF CONTENTS

3 OVERVIEW Overview of the utilization of early warning scores (EWS) and systems that support clinical decision making

4NATIONAL EARLY WARNING SCORE (NEWS)

Overview of NEWS and summary of: Smith GB, Prytherch DR, Meredith P, Schmidt PE, Featherstone PI. The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death. Resuscitation. 2013;84(4):465-470.

6MODIFIED EARLY WARNING SCORE (MEWS)

Overview of MEWS and summary of: Mitchell IA, McKay H, Van Leuvan C, et al. A prospective controlled trial of the effect of a multi-faceted intervention on early recognition and intervention in deteriorating hospital patients. Resuscitation. 2010;81(6):658-666.

8SCOTTISH (STANDARDISED) EARLY WARNING SCORE (SEWS)

Overview of SEWS and summary of: Paterson R, MacLeod DC, Thetford D, et al. Prediction of in-hospital mortality and length of stay using an early warning scoring system: clinical audit. Clin Med (Lond). 2006;6(3):281-284.

10WELLINGTON EARLY WARNING SCORE (WEWS)

Overview of WEWS, the EWS from Wellington Regional Hospital developed in 2011

11 REFERENCES List of works cited

NEWS

TABLE OF CONTENTS

MEWS

SEWS

WEWS

REFERENCES

3

OVERVIEW

Early warning scores (EWS) are tools used to identify patients with potential for clinical deterioration or with established critical illness. An EWS is a derived parameter based on data from physiological readings (e.g., systolic blood pressure, heart rate, respiratory rate, body temperature) and observations (e.g., level of consciousness [AVPU]). Determining an EWS involves assigning a number between 0 and 3 to each of the vital signs and observations, based on how far the parameter value (or observation) is from normal ranges. The sum of the scores of the different parameters yields the patient’s total EWS. The higher the EWS, the more serious the patient’s condition.1,2

Several hundred unique yet similar EWS are in use worldwide.2 Table 1 provides a brief comparison of the national early warning score (NEWS), the modified early warning score (MEWS), the Scottish (or standardised) early warning score (SEWS), and the Wellington early warning score (WEWS).

Table 1. Comparison of Selected Early Warning Scores

Parameter NEWS MEWS SEWS WEWS

Respiration rate X X X X

Heart rate X X X X

Systolic blood pressure X X X X

SpO2 X X

Supplemental O2 X

Level of consciousness (AVPU) X X X X

Temperature X X X

Urine output X X

NEWS indicates national early warning score; MEWS, modified early warning score; SEWS, Scottish (or standardised) early warning score; WEWS, Wellington early warning score.

Early warning systems have been shown to reasonably predict the occurrence of cardiac arrest and death within 48 hours of measurement.3 Evidence also suggests they may predict risk of ICU admission, death, and length of hospital stay.4,5 While there may not be sufficient evidence to support the argument that the use of an EWS alone is the answer, many studies have provided evidence of improvements in early detection of deterioration and/or outcome measures since the introduction of an EWS. The following studies provide specific evidence on the potential of NEWS-, MEWS-, SEWS-, and WEWS-based systems in medical and surgical patient populations.

OVERVIEW

TABLE OF CONTENTS

OVERVIEW

MEWS

SEWS

WEWS

REFERENCES

4

NEWS

In 2007, the Acute Medicine Task Force of the Royal College of Physicians (RCP) made recommendations for the development of a NEWS to be used throughout the National Health System (NHS) at all stages in the acute medicine pathway. The recommended early warning system included the recording of a minimum clinical dataset6 to identify the severity of a patient’s illness, linked to a graded response strategy to facilitate appropriate intervention.7 The NEWS evolved from the VitalPAC early warning score (ViEWS). ViEWS was developed with the cutoffs for its scoring assignments being interatively adjusted over time to maximize the ability to predict in-hospital death within 24 hours of a calculated score. Members of the RCP National Early Warning Score Design and Implementation Group made minor adjustments to ViEWS, based on clinical opinion, to develop NEWS.8

The NEWS is based on heart rate, respiratory rate, systolic blood pressure, arterial oxygen saturation, temperature, and consciousness level, with an additional weighting if the patient is being given oxygen therapy (Table 2).8 Patients who acutely require any supplemental oxygen (via face mask or nasal cannula) to maintain oxygen saturation are, by the fact they need oxygen, recognized to be at a higher risk of deterioration. For this reason, a score of 2 is added to the NEWS when supplemental oxygen is used on any patient. Patients are then risk stratified into low-, medium-, and high-risk groups based on the resulting aggregate score. Patients who score in the highest category for any single observation are classified as at least medium risk, regardless of their aggregate score.9

Table 2. The National Early Warning Score

Score 3 2 1 0 1 2 3

Respiration rate (min-1) ≤8 9-11 12-20 21-24 ≥25

Heart rate (min-1) ≤40 41-50 51-90 91-110 111-130 ≥131

Systolic blood pressure (mmHg) ≤90 91-100 101-110 111–219 ≥220

SpO2 (%) ≤91 92-93 94-95 ≥96

Any supplemental O2 Yes No

Temperature (°C) ≤35 35.1-36 36.1-38 38.1-39 ≥39.1

Neurological (AVPU) A V, P, or U

A indicates alert; V, reacting to voice; P, reacting to pain; U, unresponsive. Modified from Smith et al.14

Two recent large validation studies on the ViEWS system validated NEWS for use on both medical and surgical patients.11,12 NEWS has been retrospectively validated against other EWS and found to be more sensitive than 33 other scores.13,14 In a 2013 study, Smith et al reported NEWS performed better than 33 other early warning scores tested at identifying patients at risk of the combined outcome of cardiac arrest, unanticipated ICU admission, or death within 24 hours of a vital sign dataset.

NATIONAL EARLY WARNING SCORE (NEWS)

TABLE OF CONTENTS

OVERVIEW

MEWS

SEWS

WEWS

REFERENCES

5

NATIONAL EARLY WARNING SCORE (NEWS) (cont’d.)Smith GB, et al. The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death. Resuscitation. 2013;84(4):465-470.

STUDY INFORMATION

METHODS ∙ A database was developed of vital signs collected over an approximate 2-year period from patients admitted to a hospital’s medical assessment unit (MAU), the common entry point for all medical emergency patients.

∙ Outcome measures included death, cardiac arrest, and unanticipated ICU admission, each within 24 hours of a vital signs dataset.

∙ Area under the receiver-operating characteristic (AUROC) curve was calculated to assess the ability of NEWS to discriminate between patients suffering and those not suffering an adverse outcome.

∙ The authors also applied 33 unique EWS to the same database using a range of adverse outcomes at 24 hours after observation to put the performance of NEWS into context.

RESULTS ∙ A total of 198,755 sets of vital signs were obtained from 35,585 patient episodes.

∙ Within 24 hours of collection, 199 of the observation sets were followed by cardiac arrest, 1161 by unanticipated ICU admission, 1789 by death, and 3149 by any of the adverse outcomes.

∙ The AUROCs (95% CI) for NEWS compared with the other 33 EWS, within 24 hours of the observation set, were:

∙ With the exception of cardiac arrest, none of the 95% CIs for the best performing of the 33 EWS were superior to those of NEWS.

∙ Calculation of an “EWS efficiency curve” for NEWS for the combined outcomes demonstrated a 23% reduction in workload resulting from the use of NEWS compared with the workload from the use of the EWS described by Paterson.15 Specifically, the authors calculated that ~75% of the patients who will die, suffer a cardiac arrest, or require an unplanned ICU transfer requires a response to only ~17% of NEWS values compared with ~22% for the EWS described by Paterson.

CONCLUSIONS ∙ NEWS performed better than 33 other early warning scores tested at identifying patients at risk of the combined outcome of cardiac arrest, unanticipated ICU admission, or death as well as for the individual adverse outcomes of unplanned ICU transfer or death within 24 hours of a vital signs dataset.

NEWS Other 33 EWS

Cardiac arrest 0.722 (0.685−0.759) 0.611 (0.568−0.654) to 0.710 (0.675−0.745)

Unanticipated ICU admission 0.857 (0.847−0.868) 0.570 (0.553−0.568) to 0.827 (0.814−0.840)

Death 0.894 (0.887−0.902) 0.813 (0.802−0.824) to 0.858 (0.849−0.867)

Any of these outcomes 0.873 (0.866−0.879) 0.736 (0.727−0.745) to 0.834 (0.826−0.842)

NEWS

NEWS

TABLE OF CONTENTS

OVERVIEW

SEWS

WEWS

REFERENCES

6

MEWS

Morgan et al created MEWS in 1997,16 and in 1999, Stenhouse et al proposed a modification of the EWS created by Morgan et al.17 The MEWS value is based on common vital signs such as temperature, respiratory rate, heart rate, and systolic blood pressure, as well as nursing assessments of mental status or consciousness level of the patient, and hourly urine output (Table 3).

Table 3. The Modified Early Warning Score

Score 3 2 1 0 1 2 3

Respiration rate (min-1) ≤8 9-14 15-20 21-29 > 29

Heart rate (min-1) ≤40 41-50 51-100 101-110 111-129 > 129

Systolic blood pressure (mmHg) ≤70 71-80 81-100 101-199 ≥200

Urine output (mL/kg/hr) Nil <0.5

Temperature (°C) ≤35 35.1-36 36.1-38 38.1-38.5 ≥38.6

Neurological (AVPU) A V P U

Ward doctor is informed with a score of ≥ 4. A indicates alert; V, reacting to voice; P, reacting to pain; U, unresponsive. Modified from Gardner-Thorpe et al.10

A number of recent studies have validated the use of MEWS in a variety of patient populations and have indicated that using MEWS as a referral tool can lead to reduced ICU admissions and length of hospitalization.5,18-22 Evidence also suggests that MEWS is predictive of in-hospital mortality, with higher MEWS values (typically ≥ 4) predictive of increased risk of death.5,22-28 In addition, van Galen found that MEWS had predictive value for serious adverse events in a general hospital population.29 The UK-based Intensive Care Outreach Services found that summarizing abnormal physiology into MEWS was a particularly useful tool in identifying medical patients in need of ICU admission.30 Burch et al demonstrated the utility of the MEWS as a triage tool for medical emergencies seen in emergency department settings where resource and personnel constraints limit the use of more complex triage systems.31 In addition to general medical and surgical patient populations, MEWS also has been validated in patients with upper gastrointestinal bleeding,21 cancer,22 sepsis,32 and in prehospital patients.33

In a large prospective study in 2010, Mitchell et al reported that the introduction of a multifaceted intervention to detect clinical deterioration, including MEWS, led to reductions in unplanned ICU admissions (0.5 vs. 1.8%, p = 0.0006) and deaths (0.2 vs. 1.0%, p = 0.03) along with improved vital signs documentation and increased medical reviews.34

MODIFIED EARLY WARNING SCORE (MEWS)

NEWS

TABLE OF CONTENTS

OVERVIEW

SEWS

WEWS

REFERENCES

7

MODIFIED EARLY WARNING SCORE (MEWS) (cont’d.)Mitchell IA, et al. A prospective controlled trial of the effect of a multi-faceted intervention on early recognition and intervention in deteriorating hospital patients. Resuscitation. 2010;81(6):658-666.

STUDY INFORMATION

METHODS ∙ A prospective, controlled pre- and post-intervention trial of adult patients admitted to medical and surgical wards at two teaching hospitals, to determine the impact on clinical reviews and the rate of adverse outcomes.

∙ Intervention included implementation of a MEWS vital signs observation chart, a medical emergency team (MET) activation plan, and an educational program.

∙ The pre- and post-intervention outcome measures included frequency of vital signs documentation and number of medical reviews following clinical deterioration, unexpected hospital deaths, unplanned admissions to the intensive care unit (ICU), and MET reviews.

RESULTS ∙ A total of 1157 patients were included in the 4-month control period compared with 985 patients during the 4-month intervention period. A subgroup of ~ 25% of patients were randomly selected for an in-depth analysis of vital sign measurements and associated communications.

∙ Reductions were seen in unplanned admissions to ICU (1.8% vs. 0.5%, p = 0.006) and unexpected hospital deaths (1.0% vs. 0.2%, p = 0.03) during the intervention period.

∙ The number of medical reviews increased during the intervention period for patients with significant clinical instability (43.6% vs. 69.6%, p < 0.001) and the patients receiving a MET review increased (2.2% vs. 3.9%, p = 0.03).

∙ Mean daily frequency of documentation of all vital signs increased during the intervention period (3.4 vs. 4.5 per day, p = 0.001).

CONCLUSIONS The introduction of a multifaceted intervention to detect clinical deterioration, including MEWS, led to reductions in unplanned ICU admissions and deaths along with improved vital signs documentation and increased medical reviews.

MEWS

NEWS

TABLE OF CONTENTS

OVERVIEW

MEWS

WEWS

REFERENCES

8

SEWS

In Scotland, the 2004 report of the NHS Quality Improvement Scotland Emergency Medical Admissions Scoping Group proposed the introduction of SEWS and produced standardized documentation for use in prehospital and hospital care, staff training, and audit. Their specific recommendations were for an aggregate-weighted scoring system with a color-coded chart and a defined response algorithm. The inclusion of oxygen saturation, shown to have a significant relationship with short- to medium-term mortality in emergency medical admissions,35 distinguishes SEWS from MEWS.5 SEWS includes scoring parameters for heart rate, respiratory rate, systolic blood pressure, level of consciousness, oxygen saturation, and temperature (Table 4).15,36

Table 4. The Standardised Early Warning Score

Score 3 2 1 0 1 2 3

Respiration rate (min-1) ≤8 9-20 21-30 31-35 ≥36

Heart rate (min-1) ≤29 30-39 40-49 50-99 100-109 110-129 ≥130

Systolic blood pressure (mmHg) ≤69 70-79 80-99 100–199 ≥200

SaO2 ≤85 85-89 90-92 ≥93

Temperature (°C) ≤33.9 34-34.9 35-35.9 36-37.9 38–38.9 ≥39

Neurological (AVPU) A V P U

A indicates alert; V, reacting to voice; P, reacting to pain; U, unresponsive. Modified from Paterson et al.15

To date, the largest study evaluating the performance of the SEWS system is the 2006 study by Paterson et al.15 In this study of approximately 850 emergency medical and surgical patients, SEWS at admission was significantly correlated with both in-hospital mortality (p < 0.001) and length of stay (p = 0.001).15

SCOTTISH (STANDARDISED) EARLY WARNING SCORE (SEWS)

NEWS

TABLE OF CONTENTS

OVERVIEW

MEWS

WEWS

REFERENCES

9

SCOTTISH (STANDARDISED) EARLY WARNING SCORE (SEWS) (cont’d.)Paterson R, et al. Prediction of in-hospital mortality and length of stay using an early warning scoring system: clinical audit. Clin Med (Lond). 2006;6(3):281-284.

STUDY INFORMATION

METHODS ∙ A clinical audit was performed on two cohorts of emergency medical and surgical admissions to a combined assessment area (CAA).

∙ Observations were made on admission for all emergency referrals to the CAA.

∙ Outcome measures included completeness of documentation of physiological parameters, in-hospital mortality, and hospital length of stay.

RESULTS ∙ Data were collected for a total of 848 patients, including 413 pre-SEWS and 435 post-SEWS.

∙ Completed documentation of physiological parameter sets increased 69% after the introduction of the SEWS chart, with significant improvements observed in the recording of respiratory rate (15.3% pre-SEWS vs. 86.6% post-SEWS) and level of consciousness (16.0% pre-SEWS vs. 92.6% post-SEWS).

∙ A significant linear relationship was demonstrated in the SEWS cohort between in-hospital mortality and SEWS score calculated on admission (chi 34.3, p < 0.001) with mortality shown to be eight-fold higher in patients with a score of ≥4 compared with those patients with a score of ≤3 (difference in proportions 15.3%, p < 0.01).

∙ Implementation of the SEWS chart was accompanied by a reduction in overall in-hospital mortality (pre-SEWS 5.8% vs. post-SEWS 3.0% , p = 0.046).

∙ Increasing SEWS value was associated with increased median length of stay. A patient with a SEWS score of ≥4 experienced a hospital stay more than twice as long as patients with a SEWS scores ≤3 (5 to 7 days vs. 2 days, p = 0.0001).

∙ Of hospital staff responding to a questionnaire on utility of the SEWS as a clinical tool, 80% agreed or strongly agreed the SEWS chart was useful in signaling illness severity, and 60% agreed it facilitated earlier intervention.

CONCLUSIONS A SEWS system improves documentation of physiological parameters, helps predict length of stay, and should be standard practice in the acute setting, representing a simple and effective means of alerting less experienced staff to severity of illness and inpatient mortality risk.

SEWS

NEWS

TABLE OF CONTENTS

OVERVIEW

MEWS

SEWS

REFERENCES

10

WEWS

In June 2011, Wellington Regional Hospital introduced a new adult EWS system based on NEWS with modifications to include emergency escalation for patients at high risk of imminent death. The Wellington early warning score (WEWS) system includes mandatory MET calling for patients whose observations indicated they are severely ill and in need of urgent medical attention (Table 5). A graded scoring system precedes this activation with mandatory steps including an increase in observation frequency or intervention including modification of treatment or enhancing bedside caregiver expertise to reverse deterioration.

Table 5. The Wellington Early Warning Score

Score MET Call 3 2 1 0 1 2 3 MET Call

Zone Pink Orange Gold Yellow White Yellow Gold Orange Pink

Respiration rate (min-1) <5 5-8 9-20 21-30 31-35 >35

Heart rate (min-1) <40 40-49 50-100 101-110 111-130 131-140 >140

Systolic blood pressure (mmHg) <70 70-79 80-89 90-99 100-180 >180

4-hr Urine output (mL) <80 80-120 >120

Neurological (AVPU) U P A/C V AA indicates alert; V, voice; A/C, agitation/confusion; P, pain; U, unresponsive. Modified from reference 37.

While peer-reviewed validation studies of WEWS are limited, available data suggest that, in its first year of use in the Wellington Regional Hospital, WEWS implementation and its accompanying vital sign chart reduced inpatient cardiac arrests by 30%.37

WELLINGTON EARLY WARNING SCORE (WEWS)

NEWS

TABLE OF CONTENTS

OVERVIEW

MEWS

SEWS

WEWS

REFERENCES

1. Department of Health and Modernisation Agency. The National Outreach Report. London: DH, 2003.

2. Jansen JO, Cuthbertson BH. Detecting critical illness outside the ICU: the role of track and trigger systems. Curr Opin Crit Care. 2010;16(3):184-190.

3. Smith ME, Chiovaro JC, O’Neil M, et al. Early warning system scores for clinical deterioration in hospitalized patients: a systematic review. Ann Am Thorac Soc. 2014;11(9):1454-1465.

4. Groarke JD, Gallagher J, Stack J, et al. Use of an admission early warning score to predict patient morbidity and mortality and treatment success. Emerg Med J. 2008;25(12):803-806.

5. Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modified Early Warning Score in medical admissions. QJM. 2001;94(10):521-526.

6. Royal College of Physicians. Acute medical care. The right person, in the right setting – first time. Report of the Acute Medicine Task Force. London, UK: Royal College of Physicians; 2007.

7. National Institute for Health and Clinical Excellence. Acutely ill patients in hospital: Recognition of and response to acute illness in adults in hospital. London, UK: National Institute for Health and Clinical Excellence; 2007.

8. Royal College of Physicians. National Early Warning Score (NEWS): Standardising the assessment of acute-illness severity in the NHS. Report of a working party. London, UK: Royal College of Physicians; 2012.

9. Silcock DJ, Corfield AR, Gowens PA, Rooney KD. Validation of the National Early Warning Score in the prehospital setting. Resuscitation. 2015;89:31-35.

10. Gardner-Thorpe J, Love N, Wrightson J, Walsh S, Keeling N. The value of Modified Early Warning Score (MEWS) in surgical in-patients: a prospective observational study. Ann R Coll Surg Engl. 2006;88(6):571-575.

11. Bleyer AJ, Vidya S, Russell GB, et al. Longitudinal analysis of one million vital signs in patients in an academic medical center. Resuscitation. 2011;82(11):1387-1392.

12. Kellett J, Kim A. Validation of an abbreviated Vitalpac Early Warning Score (ViEWS) in 75,419 consecutive admissions to a Canadian regional hospital. Resuscitation. 2012;83(3):297-302.

13. Prytherch DR, Smith GB, Schmidt PE, Featherstone PI. ViEWS--Towards a national early warning score for detecting adult inpatient deterioration. Resuscitation. 2010;81(8):932-937.

14. Smith GB, Prytherch DR, Meredith P, Schmidt PE, Featherstone PI. The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death. Resuscitation. 2013;84(4):465-470.

15. Paterson R, MacLeod DC, Thetford D, et al. Prediction of in-hospital mortality and length of stay using an early warning scoring system: clinical audit. Clin Med (Lond). 2006;6(3):281-284.

16. Morgan RJM, Williams F, Wright MM. An early warning scoring system for detecting developing critical illness. Clin Intensive Care. 8:100.

17. Stenhouse C, Coates S, Tivey M, Allsop P, Parker T. Prospective evaluation of a modified Early Warning Score to aid earlier detection of patients developing critical illness on a general surgical ward. Br J Anaesth. 2000;84(5):663.

18. Pittard AJ. Out of our reach? Assessing the impact of introducing a critical care outreach service. Anaesthesia. 2003;58(9):882-885.

19. Subbe CP, Davies RG, Williams E, Rutherford P, Gemmell L. Effect of introducing the Modified Early Warning score on clinical outcomes, cardio-pulmonary arrests and intensive care utilisation in acute medical admissions. Anaesthesia. 2003;58(8):797-802.

20. Bokhari SW, Munir T, Memon S, Byrne JL, Russell NH, Beed M. Impact of critical care reconfiguration and track-and-trigger outreach team intervention on outcomes of haematology patients requiring intensive care admission. Ann Hematol. 2010;89(5):505-512.

21. Bozkurt S, Kose A, Arslan ED, et al. Validity of modified early warning, Glasgow Blatchford, and pre-endoscopic Rockall scores in predicting prognosis of patients presenting to emergency department with upper gastrointestinal bleeding. Scand J Trauma Resusc Emerg Med. 2015;23:109.

22. Cooksley T, Kitlowski E, Haji-Michael P. Effectiveness of Modified Early Warning Score in predicting outcomes in oncology patients. QJM. 2012;105(11):1083-1088.

23. Alrawi YA, Parker RA, Harvey RC, et al. Predictors of early mortality among hospitalized nursing home residents. QJM. 2013;106(1):51-57.

24. Delgado-Hurtado JJ, Berger A, Bansal AB. Emergency department Modified Early Warning Score association with admission, admission disposition, mortality, and length of stay. J Community Hosp Intern Med Perspect. 2016;6(2):31456.

25. Dundar ZD, Ergin M, Karamercan MA, et al. Modified Early Warning Score and VitalPac Early Warning Score in geriatric patients admitted to emergency department. Eur J Emerg Med. 2015.

26. Goldhill DR, McNarry AF, Mandersloot G, McGinley A. A physiologically-based early warning score for ward patients: the association between score and outcome. Anaesthesia. 2005;60(6):547-553.

REFERENCES

11

NEWS

TABLE OF CONTENTS

OVERVIEW

MEWS

SEWS

WEWS

27. Stark AP, Maciel RC, Sheppard W, Sacks G, Hines OJ. An Early Warning Score Predicts Risk of Death after In-hospital Cardiopulmonary Arrest in Surgical Patients. Am Surg. 2015;81(10):916-921.

28. Tavares RC, Vieira AS, Uchoa LV, Peixoto Junior AA, Meneses FA. Validation of an early warning score in pre-intensive care unit. Rev Bras Ter Intensiva. 2008;20(2):124-127.

29. van Galen LS, Dijkstra CC, Ludikhuize J, Kramer MH, Nanayakkara PW. A Protocolised Once a Day Modified Early Warning Score (MEWS) Measurement Is an Appropriate Screening Tool for Major Adverse Events in a General Hospital Population. PLoS One. 2016;11(8):e0160811.

30. Goldhill DR. The critically ill: following your MEWS. QJM. 2001;94(10):507-510.

31. Burch VC, Tarr G, Morroni C. Modified early warning score predicts the need for hospital admission and inhospital mortality. Emerg Med J. 2008;25(10):674-678.

32. Yoo JW, Lee JR, Jung YK, et al. A combination of early warning score and lactate to predict intensive care unit transfer of inpatients with severe sepsis/septic shock. Korean J Intern Med. 2015;30(4):471-477.

33. Leung SC, Leung LP, Fan KL, Yip WL. Can prehospital Modified Early Warning Score identify non-trauma patients requiring life-saving intervention in the emergency department? Emerg Med Australas. 2016;28(1):84-89.

34. Mitchell IA, McKay H, Van Leuvan C, et al. A prospective controlled trial of the effect of a multi-faceted intervention on early recognition and intervention in deteriorating hospital patients. Resuscitation. 2010;81(6):658-666.

35. Bowton DL, Scuderi PE, Haponik EF. The incidence and effect on outcome of hypoxemia in hospitalized medical patients. AM J Med. 1994;97(1):38-46.

36. National Health Service QIS. Emergency Medical Admissions Scoping Group Final Report. Edinburgh, Scotland: National Health Service, Quality Improvement Scotland; 2004.

37. Early Warning Scores and Medical Emergency Teams. Wellington Intensive Care Unit. http://www.wellingtonicu.com/AboutUs/Services/EWS/. Updated September 1, 2016. Accessed July 2016.

REFERENCES (cont’d.)

REFERENCES

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