NCT03375658: PDWS

Evaluation of the Patient Deterioration Warning System

Status unknown NA Last updated 23 February 2021

What this trial tests

NA trial testing PDWS Intervension in Patient Transfer to Intensive Care Unit (Procedure) in 6,500 participants. Status unknown.

Timeline

18 May 2018

Primary endpoint
8 April 2019

31 December 2021

Quick facts

Lead sponsor	University of Southern Denmark
Phase	NA
Status	Status unknown
Study type	INTERVENTIONAL
Allocation	non randomized
Design	parallel
Masking	none
Primary purpose	supportive care
Enrollment	6,500
Start date	18 May 2018
Primary completion	8 April 2019
Estimated completion	31 December 2021
Sites	2 locations across Denmark

Drugs / interventions tested

• PDWS Intervension

Conditions studied

• Patient Transfer to Intensive Care Unit (Procedure) — all drugs for Patient Transfer to Intensive Care Unit (Procedure) →
• Respiratory Arrest (Disorder) — all drugs for Respiratory Arrest (Disorder) →
• Cardiac Arrest (Disorder) — all drugs for Cardiac Arrest (Disorder) →
• Patient Died in Hospital (Finding) — all drugs for Patient Died in Hospital (Finding) →

Sponsor

University of Southern Denmark

Who can join

18 and older, any sex, with Patient Transfer to Intensive Care Unit (Procedure) or Respiratory Arrest (Disorder). Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The overall goal of the project is to reduce the number of unexpected patient deteriorations by 50% at Emergency Departments (ED) by investigating if the novel Patient Deterioration Warning Systems (PDWS), can improve clinicians' ability to identify deterioration at an earlier stage.

A third of all acute medical patients with normal vital signs at arrival, experience a deterioration in vital signs during the 24 first hours. This can potentially lead to dire consequences for these patients, as the risk of deterioration is present across all severity levels. The utilization of patient monitoring systems in the dispersed and shared working environments of EDs and acute wards may help to identify some of the reasons for failure to rescue patients. Thus, quantifying the extent to which a patient is being monitored, may be an aid to bridge the current gap between usage of automated and manual monitoring as clinical work will continue to depend on tacit knowledge and intuition.

Several systems and protocols have been established to swiftly deal with identified deterioration. Most systems struggle with issues of clinical adherence and are difficult to assess on-the-fly, and in some cases nurses failed to notice abnormality in 43% of patients experiencing deterioration. Although the trajectories of patients' vital signs have been identified as more important than the initial scoring value, most of the widely used Track and Trigger systems lack a temporal aspect. Furthermore, a limited number of these Track and Trigger systems have been integrated into real time clinical decision support systems, which has not evolved much in the last decades.

The PDWS deals with these challenges by aggregating and summarizing all vital values measured with the ED's patient monitors in the ongoing admission to intuitively present the state and trajectory. The investigators intend to determine if making the PDWS system available to nurses and physicians throughout the entire ED improves their ability to identify patients at risk of deterioration. To make this assessment, the PDWS will be evaluated in a cluster randomized trial (CRT) at two ED facilities in Denmark. The CRT is structured in three 5-week intervention, and three 5-week control periods, separated by a washout period of at least one week. The primary outcome is in-hospital deterioration - defined as transfer to the intensive care unit, heart/respiratory failure or death. The effect the PDWS will be assessed by comparing the proportions of events in each study arm using Pearsons's chi-squared test on these two samples. Furthermore, the technical and economical effects are evaluated using the Technology Acceptance Model, and the Model for Assessment of Telemedicine.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.