Clinical trial NCT03690128: Individual Early Warning Score (I-EWS)
Official title: Individual Early Warning Score (I-EWS) - Does Clinical Assessment Improve Detection of Acute Deterioration in Hospitalized Patients - a Cluster-randomized Trial
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Early Warning Score
Risk Stratification
Keywords: Clinical deterioration
Risk stratification
Patient Safety
Early Warning Score
Monitoring
Clinical assessment
Lead sponsor: Herlev Hospital
Sponsor class: OTHER
First posted: 2018-10-01
Enrollment: 150000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: A prospective, cluster randomized, cross-over, non-inferiority study
Primary purpose: PREVENTION

Brief 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.

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.

Eligibility criteria: 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).

Primary outcomes:
measure: All Cause mortality at 30 days
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day
timeFrame: Assessed after one year, after completion of the study
Secondary outcomes:
measure: Length of hospital stay
timeFrame: 30 days
measure: All Cause mortality at 2 days
timeFrame: 2 days (48 hours) after index admission
measure: All Cause mortality at 7 days
timeFrame: 7 days (168 hours) after index admission
Other outcomes:
measure: Frequency of changes in I-EWS scores that lead to an escalation or de-escalation in the escalation protocol
timeFrame: Assessed after one year, after completion of the study
measure: Comparison of changes in EWS score due to I-EWS modification (intervention group) and due to temporary or chronic acceptable values (control group)
timeFrame: Assessed after one year, after completion of the study
measure: The number of Cardiac arrests* during hospital stay, reported in numbers (%)
timeFrame: Assessed after one year, after completion of the study
measure: The number of Cardiac arrests* during hospital stay, reported in number per 10,000 ward days
timeFrame: Assessed after one year, after completion of the study
measure: Scores generating a call for Mobile Emergency team (MET) reported in absolute number (%)
timeFrame: Assessed after one year, after completion of the study
measure: Scores generating a call for Mobile Emergency team (MET) reported in absolute per 10,000 ward days
timeFrame: Assessed after one year, after completion of the study
measure: Scores generating a call for the attending doctor, reported in absolute number (%)
timeFrame: Assessed after one year, after completion of the study
measure: Scores generating a call for the attending doctor, reported per 10,000 ward days
timeFrame: Assessed after one year, after completion of the study
measure: All cause mortality - Subgroup analysis of patients admitted to Herlev-Gentofte Hospital
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients admitted to Nordsjaellands Hospital
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients admitted to Bispebjerg Hospital
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients admitted to Glostrup Hospital (Medical Ward)
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients admitted to Amager-Hvidovre Hospital
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients admitted to Zealand University Hospital
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients admitted to Slagelse Hospital
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients admitted to Holbaek Hospital
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients Age ≤ 39 years
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients Age 40 to 69 years
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients Age ≥ 70 years
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients diagnosed with cardiovascular disease
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients diagnosed with cancer disease
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients diagnosed with pulmonary disease
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients diagnosed with infectious disease
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients diagnosed with neurological disease
timeFrame: 30 days after index admission
measure: All cause mortality - Subgroup analysis of patients diagnosed with surgical condition
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Herlev-Gentofte Hospital
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Nordsjaellands Hospital
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Bispebjerg Hospital
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Amager-Hvidovre Hospital
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Zealand University Hospital
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Slagelse Hospital
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients admitted to Holbaek Hospital
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients Age ≤ 39 years
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients Age 40 to 69 years
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients Age ≥ 70 years
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with cancer
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with cardiovascular disease
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with pulmonary disease
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with infectious disease
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with neurological disease
timeFrame: 30 days after index admission
measure: The number of NEWS/I-EWS scores per patient per day - Subgroup analysis of patients diagnosed with surgical condition
timeFrame: 30 days after index admission
Locations:
city: Copenhagen
country: Denmark
facility: Bispebjerg Hospital
state: Capital Region Of Denmark
city: Copenhagen
country: Denmark
facility: Amager & Hvidovre Hospital
state: Capital Region Of Denmark
city: Copenhagen
country: Denmark
facility: Herlev & Gentofte Hospital
state: Capital Region Of Denmark
city: Glostrup
country: Denmark
facility: Rigshospital, Glostrup, Medical Ward
state: Capital Region Of Denmark
city: Hillerød
country: Denmark
facility: Nordsjaellands Hospital
state: Capital Region Of Denmark
city: Holbæk
country: Denmark
facility: Holbaek Hospital
state: Region Of Zealand
city: Roskilde
country: Denmark
facility: Zealand University Hospital (Roskilde & Køge)
state: Region Of Zealand
city: Slagelse
country: Denmark
facility: Slagelse Sygehus
state: Region Of Zealand
Study officials:
affiliation: Department of Cardiology, Herlev Hospital
name: Kasper Iversen, MD, DMSci
role: STUDY_DIRECTOR
References:
citation: 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.
citation: 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.