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.
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
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
NONE
Enrollment
150,000
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.
Standard EWS - Based on principles of National Early Warning Score (NEWS)
Bispebjerg Hospital
Copenhagen, Capital Region of Denmark, Denmark
Amager & Hvidovre Hospital
Copenhagen, Capital Region of Denmark, Denmark
Herlev & Gentofte Hospital
Copenhagen, Capital Region of Denmark, Denmark
Rigshospital, Glostrup, Medical Ward
Glostrup Municipality, Capital Region of Denmark, Denmark
Nordsjaellands Hospital
Hillerød, Capital Region of Denmark, Denmark
Holbaek Hospital
Holbæk, Region of Zealand, Denmark
Zealand University Hospital (Roskilde & Køge)
Roskilde, Region of Zealand, Denmark
Slagelse Sygehus
Slagelse, Region of Zealand, Denmark
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
The number of NEWS/I-EWS scores per patient per day
Time frame: Assessed after one year, after completion of the study
Length of hospital stay
Calculated as days from date of index admission to date of discharge
Time frame: 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.
Time frame: 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.
Time frame: 7 days (168 hours) after index admission
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