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CompletedNCT03690128Updated Nov 4, 2019

Individual Early Warning Score (I-EWS)

An interventional study of I-EWS with incorporated clinical assessment (Trigger Tool) and Standard EWS - Control (Trigger Tool) in Early Warning Score and Risk Stratification, sponsored by Herlev Hospital. Completed at 8 sites in Denmark. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2019-11-04.

Sponsored by Herlev Hospital · Not applicable, Interventional, and Prevention

Phase
Not applicable
Study type
Interventional
Enrollment
150,000
Allocation
Randomized
Ages
18 Years and older
Sex
All
01

Study summary

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.

Read the 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.

02

Conditions studied

  • Early Warning Score
  • Risk Stratification

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Keywords

  • Clinical deterioration
  • Risk stratification
  • Patient Safety
  • Early Warning Score
  • Monitoring
  • Clinical assessment
03

In context

Clinical Deterioration

50 studies on the registry are indexed under Clinical Deterioration; 14 are open to participants now.

This study's enrollment of 150,000 is above the median of 300 across 24 interventional studies indexed under Clinical Deterioration.

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Lead sponsor

Herlev Hospital is the lead sponsor of 201 studies on the registry; 25 are open to participants now.

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Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

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

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).
05

Study design

Phase
Not applicable
Primary purpose
Prevention
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
150,000 participants (actual)

Study arms

  • 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)

  • 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)

Interventions

  • BehavioralI-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.

  • BehavioralStandard EWS - Control (Trigger Tool)

    Standard EWS - Based on principles of National Early Warning Score (NEWS)

06

What researchers measure

Primary outcomes

  1. All Cause mortality at 30 days

    Time frame starts at the beginning of the index admission, defined as first admission in the study period.

    Time frame: 30 days after index admission

  2. The number of NEWS/I-EWS scores per patient per day

    Time frame: Assessed after one year, after completion of the study

Secondary outcomes

  1. Length of hospital stay

    Calculated as days from date of index admission to date of discharge

    Time frame: 30 days

  2. All Cause mortality at 2 days

    Time frame starts at the beginning of the index admission, defined as first admission in the study period.

    Time frame: 2 days (48 hours) after index admission

  3. All Cause mortality at 7 days

    Time frame starts at the beginning of the index admission, defined as first admission in the study period.

    Time frame: 7 days (168 hours) after index admission

Other outcomes

  1. Frequency of changes in I-EWS scores that lead to an escalation or de-escalation in the escalation protocol

    Time frame: Assessed after one year, after completion of the study

  2. Comparison of changes in EWS score due to I-EWS modification (intervention group) and due to temporary or chronic acceptable values (control group)

    Time frame: Assessed after one year, after completion of the study

  3. 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.

    Time frame: Assessed after one year, after completion of the study

  4. 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.

    Time frame: Assessed after one year, after completion of the study

  5. Scores generating a call for Mobile Emergency team (MET) reported in absolute number (%)

    Time frame: Assessed after one year, after completion of the study

  6. Scores generating a call for Mobile Emergency team (MET) reported in absolute per 10,000 ward days

    Time frame: Assessed after one year, after completion of the study

  7. Scores generating a call for the attending doctor, reported in absolute number (%)

    Time frame: Assessed after one year, after completion of the study

  8. Scores generating a call for the attending doctor, reported per 10,000 ward days

    Time frame: Assessed after one year, after completion of the study

  9. 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.

    Time frame: 30 days after index admission

  10. 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.

    Time frame: 30 days after index admission

  11. 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.

    Time frame: 30 days after index admission

  12. 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.

    Time frame: 30 days after index admission

  13. 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.

    Time frame: 30 days after index admission

  14. 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.

    Time frame: 30 days after index admission

  15. 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.

    Time frame: 30 days after index admission

  16. 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.

    Time frame: 30 days after index admission

  17. 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.

    Time frame: 30 days after index admission

  18. 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.

    Time frame: 30 days after index admission

  19. 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.

    Time frame: 30 days after index admission

  20. 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.

    Time frame: 30 days after index admission

  21. 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.

    Time frame: 30 days after index admission

  22. 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.

    Time frame: 30 days after index admission

  23. 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.

    Time frame: 30 days after index admission

  24. 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.

    Time frame: 30 days after index admission

  25. 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.

    Time frame: 30 days after index admission

  26. 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.

    Time frame: 30 days after index admission

  27. 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.

    Time frame: 30 days after index admission

  28. 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.

    Time frame: 30 days after index admission

  29. 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.

    Time frame: 30 days after index admission

  30. 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.

    Time frame: 30 days after index admission

  31. 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.

    Time frame: 30 days after index admission

  32. 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.

    Time frame: 30 days after index admission

  33. 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.

    Time frame: 30 days after index admission

  34. 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.

    Time frame: 30 days after index admission

  35. 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.

    Time frame: 30 days after index admission

  36. 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.

    Time frame: 30 days after index admission

  37. 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.

    Time frame: 30 days after index admission

  38. 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.

    Time frame: 30 days after index admission

  39. 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.

    Time frame: 30 days after index admission

  40. 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.

    Time frame: 30 days after index admission

  41. 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.

    Time frame: 30 days after index admission

07

Study locations

8 sites
  • Bispebjerg Hospital
    Copenhagen, Capital Region of Denmark 2400, Denmark
  • Amager & Hvidovre Hospital
    Copenhagen, Capital Region of Denmark 2650, Denmark
  • Herlev & Gentofte Hospital
    Copenhagen, Capital Region of Denmark 2730, Denmark
  • Rigshospital, Glostrup, Medical Ward
    Glostrup Municipality, Capital Region of Denmark 2600, Denmark
  • Nordsjaellands Hospital
    Hillerød, Capital Region of Denmark 3400, Denmark
  • Holbaek Hospital
    Holbæk, Region of Zealand 4300, Denmark
  • Zealand University Hospital (Roskilde & Køge)
    Roskilde, Region of Zealand 4000, Denmark
  • Slagelse Sygehus
    Slagelse, Region of Zealand 4200, Denmark
08

References and documents

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. PubMed 35599143 ↗
  • 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. PubMed 31915173 ↗

Study documents

  • Statistical analysis plan · Jul 11, 2019

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: Undecided

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Nov 4, 2019, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT03690128
Lead sponsor
Herlev Hospital
Responsible party
Kasper Iversen (Principal Investigator, Associate Professor, Consultant, DMSci, Herlev Hospital) — Principal investigator
First posted
Oct 1, 2018
Start date
Oct 1, 2018
Primary completion
Oct 31, 2019
Completion
Oct 31, 2019
Last update
Nov 4, 2019

Study contacts

Kasper Iversen, MD, DMSci
study director · Department of Cardiology, Herlev Hospital

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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