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临床试验/NCT03690128
NCT03690128已完成不适用

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

Herlev Hospital16 个研究点 分布在 1 个国家目标入组 150,000 人开始时间: 2018年10月1日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
已完成
入组人数
150,000
试验地点
16
主要终点
All Cause mortality at 30 days

研究概览

简要总结

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.

详细描述

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.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Prevention
盲法
None

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • 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

排除标准

  • 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).

研究组 & 干预措施

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.

干预措施: Standard EWS - Control (Trigger Tool) (Behavioral)

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.

干预措施: I-EWS with incorporated clinical assessment (Trigger Tool) (Behavioral)

结局指标

主要结局

All Cause mortality at 30 days

时间窗: 30 days after index admission

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

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

时间窗: Assessed after one year, after completion of the study

次要结局

  • All Cause mortality at 7 days(7 days (168 hours) after index admission)
  • All Cause mortality at 2 days(2 days (48 hours) after index admission)
  • Length of hospital stay(30 days)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Kasper Iversen

Principal Investigator, Associate Professor, Consultant, DMSci

Herlev Hospital

研究点 (16)

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