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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control Arm - standard EWS procedure | Active Comparator | 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. |
|
| Intervention Arm - I-EWS | Active Comparator | 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. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| I-EWS with incorporated clinical assessment (Trigger Tool) | Behavioral | 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. |
| 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 |
| 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. |
| 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) |
Inclusion Criteria:
Participating hospitals are
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Kasper Iversen, MD, DMSci | Department of Cardiology, Herlev Hospital | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Bispebjerg Hospital | Copenhagen | Capital Region of Denmark | 2400 | Denmark | ||
| Amager & Hvidovre Hospital |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35599143 | Derived | 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. | |
| 31915173 |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| SAP | No | Yes | No | Statistical Analysis Plan | Jul 11, 2019 | Jul 11, 2019 | SAP_002.pdf |
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| ID | Term |
|---|---|
| D000075902 | Clinical Deterioration |
| ID | Term |
|---|---|
| D018450 | Disease Progression |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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A prospective, cluster randomized, cross-over, non-inferiority study
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| Standard EWS - Control (Trigger Tool) | Behavioral | Standard EWS - Based on principles of National Early Warning Score (NEWS) |
|
| 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 |
| 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 |
| 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 |
| Derived |
| 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. |