Individual Early Warning Score (I-EWS)

Individual Early Warning Score (I-EWS) - Does Clinical Assessment Improve Detection of Acute Deterioration in Hospitalized Patients - a Cluster-randomized Trial

Early Warning Score (EWS) is a clinical scoring system used in hospitals in Denmark and internationally to systematically observe admitted patients using a standardised response algorithm. Consisting of a score based on the patients' vital signs, it only leaves limited space for individual assessment. Patient safety but also resource utilisation is a key issue in health systems today. We have developed a new individual EWS system (I-EWS) that reintroduces the individual clinical assessment for a more personalised observation. Our hypothesis is that I-EWS will not increase the mortality among hospitalised patients compared to EWS but will improve workflow by reducing unnecessary observations and freeing staff resources, potentially leading to improved patient care. The impact of I-EWS on mortality, the occurrence of critical illness, and usage of staff resources will be evaluated in a prospective, cluster randomised, non-inferiority study conducted at eight hospitals in Denmark.

Study Overview

• Status: Completed
• Conditions: Risk Stratification; Early Warning Score
• Intervention / Treatment: Behavioral: Standard EWS - Control (Trigger Tool); Behavioral: I-EWS with incorporated clinical assessment (Trigger Tool)

Detailed Description

Every year more than 250,000 patients are admitted in the Capital Region of Denmark. During admissions, the clinical track and trigger system "Early Warning Score" (EWS) is used to systematically observe and detect acutely deteriorating patients. The system is designed to prevent serious adverse events like unanticipated transfer to the intensive care unit, cardiac arrest and unexpected death. EWS consists of standardized measurements of the patient's vital signs and an escalation protocol that determines further actions based on the aggregated EWS score. At admission, and as a minimum twice a day, nurses measure vital signs on all hospitalized patients. Depending on the predetermined cut-off values (i.e. heart rate above 150 bpm = 3 points) an aggregated score is calculated. Based on the total score, the escalation protocol determines the time interval for the next measurement as well as a clinical action (i.e. call for attending doctor). EWS is developed to detect and to treat potentially deterioration of disease that might lead to critical illness and death. In its current form, there is only limited room for individual clinical assessment.

A standardized track and trigger system like EWS does not differentiate between different types of disease or the patient's individual physiological response. Therefore, there is a potential risk that the system fails to detect a patient with an abnormal stress response. Additionally; patients suffering from chronic illness might have different normal values than healthy patients, leading to unnecessarily excess observation, measurement, and suboptimal usage of limited staff resources.

Previous studies have shown that Early Warning System scores perform well for prediction of cardiac arrest and death within 48 hours, although the impact on health outcomes and resource utilization remains uncertain, often owing to methological limitations.

It is possible, but never studied before, whether the combination of vital signs with individual clinical assessment is a better tool for identifying hospitalized high-risk patients than the existing algorithms.

Further improvement and optimizing of the EWS is necessary, as there is potential to improve patient care and use staff resources more appropriate.

The purpose of the study is to investigate the impact of the I-EWS that has a systematic involvement of clinical assessment and the possibility to adjust the score, whilst keeping the same escalation protocol. I-EWS will be compared to the existing EWS with a focus on mortality, critical illness, and the use of staff resources.

Our hypothesis is that I-EWS, where clinical assessment is given a more prominent role will not increase the mortality among hospitalized patients but can reallocate personnel resources.

I-EWS is built in to electronic patient journal system "Sundhedsplatformen" it is only available in Sundhedsplatformen (SP) at hospitals assigned to I-EWS. Four hospitals are randomized to use I-EWS for 6,5 months, the remaining four hospitals are control hospitals using the current EWS in this period.

After 6,5 months a single cross-over will be preformed, and the previous control hospitals will use I-EWS over the next 6,5 months and the previous intervention hospitals, will go back to the current EWS for this period.

EWS scores and subsequent actions are documented in real time in SP. The first two weeks and final four weeks of each period will be excluded due to a implementation period. Data regarding patients, interventions and serious adverse events during hospitalization (i.e., cardiac arrest, the request of MET or unexpected death) will be accessed through SP and the Danish Central Registries (The Danish National Patient Registry, the Civil Registration System, DanArrest). After extraction, all data will be depersonalization and stored at a secured network in accordance with the current guidelines for data management in the Capital Region of Denmark.

• Study Type: Interventional
• Enrollment (Actual): 150000
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Denmark
  • Capital Region Of Denmark
    • Copenhagen, Capital Region Of Denmark, Denmark, 2400
      • Bispebjerg Hospital
    • Copenhagen, Capital Region Of Denmark, Denmark, 2650
      • Amager & Hvidovre Hospital
    • Copenhagen, Capital Region Of Denmark, Denmark, 2730
      • Herlev & Gentofte Hospital
    • Glostrup, Capital Region Of Denmark, Denmark, 2600
      • Rigshospital, Glostrup, Medical Ward
    • Hillerød, Capital Region Of Denmark, Denmark, 3400
      • Nordsjaellands Hospital
  • Region Of Zealand
    • Holbæk, Region Of Zealand, Denmark, 4300
      • Holbaek Hospital
    • Roskilde, Region Of Zealand, Denmark, 4000
      • Zealand University Hospital (Roskilde & Køge)
    • Slagelse, Region Of Zealand, Denmark, 4200
      • Slagelse Sygehus

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• All patients ≥18 years of age admitted more than 24 hours to a ward at participating hospitals will be included.

Participating hospitals are

• Herlev & Gentofte Hospital
• Nordsjaellands Hospital
• Bispebjerg Hospital
• Rigshospitalet, Glostrup - Medical Ward
• Amager & Hvidovre Hospital
• Zealand University Hospital
• Slagelse Hospital
• Holbaek Hospital

Exclusion Criteria:

• Wards not using standard EWS, paediatric, obstetric and intensive, due to they use special variations (Pediatric early warning score, Obstetric Early warning Score or continous monitoring).

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: Control Arm - standard EWS procedure; Standard use of the current implement Early Warning System, based on the principles of the National Early Warning Score and with a standard escalation protocol.	Behavioral: Standard EWS - Control (Trigger Tool); Standard EWS - Based on principles of National Early Warning Score (NEWS)
Active Comparator: Intervention Arm - I-EWS; Implementation of Individual Early Warning Score (I-EWS) with a systematic clinical assessment with a standard escalation protocol as intervention 7 parameters (Respiration rate, pulse, saturation, systolic blood pressure, consciousness, temperature, Oxygen) are registered , an aggregated score is generated. In the electronic patient journal (Sundhedsplatformen), the nursing staff is asked to reevaluate the aggregated score based on their clinical assessment of the patient. The aggregated score can be upgraded with up to 6 points and downgraded with up to 4. This new I-EWS score interacts with the standard escalation protocol which defines the observation frequency and relevant clinical actions.	Behavioral: I-EWS with incorporated clinical assessment (Trigger Tool); In relation to systematic measurement of vital parameters the nursing staff will perform an individual clinical assessment of the patient and adjust the I-EWS score accordingly.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
All Cause mortality at 30 days	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day		Assessed after one year, after completion of the study

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Length of hospital stay	Calculated as days from date of index admission to date of discharge	30 days
All Cause mortality at 2 days	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	2 days (48 hours) after index admission
All Cause mortality at 7 days	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	7 days (168 hours) after index admission

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Frequency of changes in I-EWS scores that lead to an escalation or de-escalation in the escalation protocol		Assessed after one year, after completion of the study
Comparison of changes in EWS score due to I-EWS modification (intervention group) and due to temporary or chronic acceptable values (control group)		Assessed after one year, after completion of the study
The number of Cardiac arrests* during hospital stay, reported in numbers (%)	*Definition - Presence of a clinical cardiac arrest (as defined in the resuscitation guidelines) in patients without a DNAR (Do Not Attempt Resuscitation) order. Registered in DANARREST.	Assessed after one year, after completion of the study
The number of Cardiac arrests* during hospital stay, reported in number per 10,000 ward days	*Definition - Presence of a clinical cardiac arrest (as defined in the resuscitation guidelines) in patients without a DNAR (Do Not Attempt Resuscitation) order. Registered in DANARREST.	Assessed after one year, after completion of the study
Scores generating a call for Mobile Emergency team (MET) reported in absolute number (%)		Assessed after one year, after completion of the study
Scores generating a call for Mobile Emergency team (MET) reported in absolute per 10,000 ward days		Assessed after one year, after completion of the study
Scores generating a call for the attending doctor, reported in absolute number (%)		Assessed after one year, after completion of the study
Scores generating a call for the attending doctor, reported per 10,000 ward days		Assessed after one year, after completion of the study
All cause mortality - Subgroup analysis of patients admitted to Herlev-Gentofte Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients admitted to Nordsjaellands Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients admitted to Bispebjerg Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients admitted to Glostrup Hospital (Medical Ward)	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients admitted to Amager-Hvidovre Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients admitted to Zealand University Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients admitted to Slagelse Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients admitted to Holbaek Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients Age ≤ 39 years	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients Age 40 to 69 years	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients Age ≥ 70 years	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients diagnosed with cardiovascular disease	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients diagnosed with cancer disease	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients diagnosed with pulmonary disease	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients diagnosed with infectious disease	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients diagnosed with neurological disease	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
All cause mortality - Subgroup analysis of patients diagnosed with surgical condition	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Herlev-Gentofte Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Nordsjaellands Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Bispebjerg Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Amager-Hvidovre Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Zealand University Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Slagelse Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Holbaek Hospital	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients Age ≤ 39 years	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients Age 40 to 69 years	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients Age ≥ 70 years	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with cancer	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with cardiovascular disease	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with pulmonary disease	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with infectious disease	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with neurological disease	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission
The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with surgical condition	Time frame starts at the beginning of the index admission, defined as first admission in the study period.	30 days after index admission

Collaborators and Investigators

• Sponsor: Herlev Hospital
• Investigators: Study Director: Kasper Iversen, MD, DMSci, Department of Cardiology, Herlev Hospital

Publications and helpful links

General Publications

• Nielsen PB, Langkjaer CS, Schultz M, Kodal AM, Pedersen NE, Petersen JA, Lange T, Arvig MD, Meyhoff CS, Bestle MH, Holge-Hazelton B, Bunkenborg G, Lippert A, Andersen O, Rasmussen LS, Iversen KK. Clinical assessment as a part of an early warning score-a Danish cluster-randomised, multicentre study of an individual early warning score. Lancet Digit Health. 2022 Jul;4(7):e497-e506. doi: 10.1016/S2589-7500(22)00067-X. Epub 2022 May 19. Erratum In: Lancet Digit Health. 2022 Dec;4(12):e861.
• Nielsen PB, Schultz M, Langkjaer CS, Kodal AM, Pedersen NE, Petersen JA, Lange T, Arvig MD, Meyhoff CS, Bestle M, Holge-Hazelton B, Bunkenborg G, Lippert A, Andersen O, Rasmussen LS, Iversen KK. Adjusting Early Warning Score by clinical assessment: a study protocol for a Danish cluster-randomised, multicentre study of an Individual Early Warning Score (I-EWS). BMJ Open. 2020 Jan 7;10(1):e033676. doi: 10.1136/bmjopen-2019-033676.

Study record dates

Study Major Dates

• Study Start (Actual): October 1, 2018
• Primary Completion (Actual): October 31, 2019
• Study Completion (Actual): October 31, 2019

Study Registration Dates

• First Submitted: September 26, 2018
• First Submitted That Met QC Criteria: September 27, 2018
• First Posted (Actual): October 1, 2018

Study Record Updates

• Last Update Posted (Actual): November 4, 2019
• Last Update Submitted That Met QC Criteria: November 1, 2019
• Last Verified: November 1, 2019

More Information

Terms related to this study

• Keywords: Monitoring; Patient Safety; Risk stratification; Clinical deterioration; Early Warning Score; Clinical assessment
• Other Study ID Numbers: 17017332

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: Undecided

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No