Patient Transfer to Intensive Care Unit (Procedure)PDWSNCT03375658
Evaluation of the Patient Deterioration Warning System
A study testing PDWS Intervension in people with Patient Transfer to Intensive Care Unit (Procedure) and Respiratory Arrest (Disorder), run by University of Southern Denmark at 2 sites in Denmark.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Patient Transfer to Intensive Care Unit (Procedure), Respiratory Arrest (Disorder), Cardiac Arrest (Disorder)
- What is being tested?
- PDWS Intervension
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 6,500 participants
- Where
- 2 sitesDenmark
- Study dates
- 18 May 2018to 31 Dec 2021
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- All adult patients admitted to the emergency department
Who cannot join
- Critically ill patients who die during their admission
- Orthopedic patients with minor injuries
Trial locations and contacts
2 sites in 1 country.
Denmark2 sites
Hospital of South Western Jutland
Esbjerg, Jylland, 6700
Odense University Hospital
Odense, Fyn, 5000
About this study
Official title: Cluster Randomized Trial of the Patient Deterioration Warning System in Emergency Departments
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.
Read more
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.
- Conditions
- Patient Transfer to Intensive Care Unit (Procedure), Respiratory Arrest (Disorder), Cardiac Arrest (Disorder), Patient Died in Hospital (Finding)
- Being tested
- PDWS Intervension
- Keywords
- Information Science: Algorithms, Information Science: Informatics: Nursing Informatics, Information Science: Data Display: Computer graphics, Diagnosis: Diagnostic Techiques and Procedures: Monitoring, Physiologic, Health care facilities, Manpower and services: Health services: Emergency Medical Services: Triage
- Medical subject headings
- Apnea, Heart Arrest, Signs and Symptoms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
PDWS IntervensionOther
Patients admitted to the emergency department in the intervention period will have their vital values presented on the PDWS in addition to existing patient monitoring systems
| Study group | Role | What they receive |
|---|---|---|
| Intervention arm | Experimental | All vital signs registered as part of usual care are used for modelling patients state and trajectories and made available to clinicans via the Patient Deterioration Warning System in nursing and physician offices. Receives: Other: PDWS Intervension |
| Control arm | No intervention | Usual care |
What is being measured
The primary outcome is the main question the study is designed to answer.
In-hospital deterioration
Defined as transfer to intensive care units, heart/respiratory failure, and in-hospital mortality. Events are reviewed by experts to exclude cases expected of deterioration at time of arrival.
Measured: Admission length (1-7 days)
Secondary outcomes (4)
Economic effect of PDWS
Cost effective analysis of savings in DKK between differences in primary outcomes in intervention and control arms of the study when inspecting DRG associations.
Measured: 35 weeks
Acceptance of novel patient monitoring system
Technology Acceptance Model based evaluation of the clinicians' perception of the novel system's usefulness and ease of use.
Measured: 35 weeks
Reduction in length of stay
Evaluation of differences in length of stay for patients admitted during the intervention and control arms respectively.
Measured: Admission length (1-7 days)
Monitoring load effect
Does the automatic presentation of patients average severity defined by registered vital signs affect how much patients are monitored during their admission. Degree of monitoring as defined as monitor load.
Measured: Admission length (1-7 days)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Dec 2017
- Study start18 May 2018
- Primary completion8 Apr 2019
- Study completion31 Dec 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (13)Papers the sponsor has linked to this study.
- Other trials for Patient Transfer to Intensive Care Unit (Procedure)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 6,500 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Southern Denmark
- Sponsor type
- University, hospital or other
- Collaborators
- Odense University Hospital, Hospital of South Western Jutland
- Responsible party
- Principal investigator, Thomas Schmidt, University of Southern Denmark
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03375658
- Sponsor's protocol ID
- PDWS
- Acronym
- PDWS
- Status last verified
- Feb 2021
- First submitted
- 6 Oct 2017
- Last updated
- 23 Feb 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Henriksen DP, Brabrand M, Lassen AT. Prognosis and risk factors for deterioration in patients admitted to a medical emergency department. PLoS One. 2014 Apr 9;9(4):e94649. doi: 10.1371/journal.pone.0094649. eCollection 2014.
PubMed 24718637Kellett J, Emmanuel A, Deane B. Who will be sicker in the morning? Changes in the Simple Clinical Score the day after admission and the subsequent outcomes of acutely ill unselected medical patients. Eur J Intern Med. 2011 Aug;22(4):375-81. doi: 10.1016/j.ejim.2011.03.005. Epub 2011 Apr 8.
PubMed 21767755Armstrong B, Walthall H, Clancy M, Mullee M, Simpson H. Recording of vital signs in a district general hospital emergency department. Emerg Med J. 2008 Dec;25(12):799-802. doi: 10.1136/emj.2007.052951.
PubMed 19033493Brier J, Carolyn M, Haverly M, Januario ME, Padula C, Tal A, Triosh H. Knowing 'something is not right' is beyond intuition: development of a clinical algorithm to enhance surveillance and assist nurses to organise and communicate clinical findings. J Clin Nurs. 2015 Mar;24(5-6):832-43. doi: 10.1111/jocn.12670. Epub 2014 Sep 19.
PubMed 25236182Brabrand M, Hallas J, Knudsen T. Nurses and physicians in a medical admission unit can accurately predict mortality of acutely admitted patients: a prospective cohort study. PLoS One. 2014 Jul 14;9(7):e101739. doi: 10.1371/journal.pone.0101739. eCollection 2014.
PubMed 25019354Schmidt T, Bech CN, Brabrand M, Wiil UK, Lassen A. Factors related to monitoring during admission of acute patients. J Clin Monit Comput. 2017 Jun;31(3):641-649. doi: 10.1007/s10877-016-9876-y. Epub 2016 Apr 12.
PubMed 27067076Acutely Ill Patients in Hospital: Recognition of and Response to Acute Illness in Adults in Hospital [Internet]. London: National Institute for Health and Clinical Excellence (NICE); 2007 Jul. Available from http://www.ncbi.nlm.nih.gov/books/NBK45947/
PubMed 21204323Clifton DA, Wong D, Clifton L, Wilson S, Way R, Pullinger R, Tarassenko L. A large-scale clinical validation of an integrated monitoring system in the emergency department. IEEE J Biomed Health Inform. 2013 Jul;17(4):835-42. doi: 10.1109/JBHI.2012.2234130.
PubMed 25055312Fuhrmann L, Lippert A, Perner A, Ostergaard D. Incidence, staff awareness and mortality of patients at risk on general wards. Resuscitation. 2008 Jun;77(3):325-30. doi: 10.1016/j.resuscitation.2008.01.009. Epub 2008 Mar 14.
PubMed 18342422Murray A, Kellett J, Huang W, Woodworth S, Wang F. Trajectories of the averaged abbreviated Vitalpac early warning score (AbEWS) and clinical course of 44,531 consecutive admissions hospitalized for acute medical illness. Resuscitation. 2014 Apr;85(4):544-8. doi: 10.1016/j.resuscitation.2013.12.015. Epub 2013 Dec 21.
PubMed 24361459Smith GB, Prytherch DR, Schmidt P, Featherstone PI, Knight D, Clements G, Mohammed MA. Hospital-wide physiological surveillance-a new approach to the early identification and management of the sick patient. Resuscitation. 2006 Oct;71(1):19-28. doi: 10.1016/j.resuscitation.2006.03.008. Epub 2006 Aug 30.
PubMed 16945465Gorges M, Staggers N. Evaluations of physiological monitoring displays: a systematic review. J Clin Monit Comput. 2008 Feb;22(1):45-66. doi: 10.1007/s10877-007-9106-8. Epub 2007 Dec 7.
PubMed 18064532Kidholm K, Ekeland AG, Jensen LK, Rasmussen J, Pedersen CD, Bowes A, Flottorp SA, Bech M. A model for assessment of telemedicine applications: mast. Int J Technol Assess Health Care. 2012 Jan;28(1):44-51. doi: 10.1017/S0266462311000638.
PubMed 22617736
Study at a glance
From the registry record, last updated by the sponsor on 23 Feb 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Cluster Randomized Trial of the Patient Deterioration Warning System in Emergency Departments
- ClinicalTrials.gov ID
- NCT03375658
- Acronym / sponsor ID
- PDWS / PDWS
- Conditions
- Patient Transfer to Intensive Care Unit (Procedure), Respiratory Arrest (Disorder), Cardiac Arrest (Disorder), Patient Died in Hospital (Finding)
- Keywords
- Information Science: Algorithms, Information Science: Informatics: Nursing Informatics, Information Science: Data Display: Computer graphics, Diagnosis: Diagnostic Techiques and Procedures: Monitoring, Physiologic, Health care facilities, Manpower and services: Health services: Emergency Medical Services: Triage
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 6,500 participants (actual)
- Lead sponsor
- University of Southern DenmarkUniversity, hospital or other
- Collaborators
- Odense University Hospital, Hospital of South Western Jutland
- Study start
- 18 May 2018 (actual)
- Primary completion
- 8 Apr 2019 (actual)
- Study completion
- 31 Dec 2021 (estimated)
- First posted
- 18 Dec 2017 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Supportive care
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Intervention arm | Experimental | Other: PDWS IntervensionAll vital signs registered as part of usual care are used for modelling patients state and trajectories and made available to clinicans via the Patient Deterioration Warning System in nursing and physician offices. |
| Control arm | No intervention | –Usual care |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- All adult patients admitted to the emergency department
Key exclusion criteria (2 listed)
- Critically ill patients who die during their admission
- Orthopedic patients with minor injuries
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| PDWS IntervensionPatients admitted to the emergency department in the intervention period will have their vital values presented on the PDWS in addition to existing patient monitoring systems | Other | Intervention arm |
Primary outcome
In-hospital deterioration
Time frame: Admission length (1-7 days)
Defined as transfer to intensive care units, heart/respiratory failure, and in-hospital mortality. Events are reviewed by experts to exclude cases expected of deterioration at time of arrival.
4 secondary outcomes
Economic effect of PDWS
Time frame: 35 weeks
Acceptance of novel patient monitoring system
Time frame: 35 weeks
Reduction in length of stay
Time frame: Admission length (1-7 days)
Monitoring load effect
Time frame: Admission length (1-7 days)
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Feb 2021.
- Background: PubMed 24718637Henriksen DP, Brabrand M, Lassen AT. Prognosis and risk factors for deterioration in patients admitted to a medical emergency department. PLoS One. 2014 Apr 9;9(4):e94649. doi: 10.1371/journal.pone.0094649. eCollection 2014.
- Background: PubMed 21767755Kellett J, Emmanuel A, Deane B. Who will be sicker in the morning? Changes in the Simple Clinical Score the day after admission and the subsequent outcomes of acutely ill unselected medical patients. Eur J Intern Med. 2011 Aug;22(4):375-81. doi: 10.1016/j.ejim.2011.03.005. Epub 2011 Apr 8.
- Background: PubMed 19033493Armstrong B, Walthall H, Clancy M, Mullee M, Simpson H. Recording of vital signs in a district general hospital emergency department. Emerg Med J. 2008 Dec;25(12):799-802. doi: 10.1136/emj.2007.052951.
- Background: PubMed 25236182Brier J, Carolyn M, Haverly M, Januario ME, Padula C, Tal A, Triosh H. Knowing 'something is not right' is beyond intuition: development of a clinical algorithm to enhance surveillance and assist nurses to organise and communicate clinical findings. J Clin Nurs. 2015 Mar;24(5-6):832-43. doi: 10.1111/jocn.12670. Epub 2014 Sep 19.
- Background: PubMed 25019354Brabrand M, Hallas J, Knudsen T. Nurses and physicians in a medical admission unit can accurately predict mortality of acutely admitted patients: a prospective cohort study. PLoS One. 2014 Jul 14;9(7):e101739. doi: 10.1371/journal.pone.0101739. eCollection 2014.
- Background: PubMed 27067076Schmidt T, Bech CN, Brabrand M, Wiil UK, Lassen A. Factors related to monitoring during admission of acute patients. J Clin Monit Comput. 2017 Jun;31(3):641-649. doi: 10.1007/s10877-016-9876-y. Epub 2016 Apr 12.
- Background: PubMed 21204323Acutely Ill Patients in Hospital: Recognition of and Response to Acute Illness in Adults in Hospital [Internet]. London: National Institute for Health and Clinical Excellence (NICE); 2007 Jul. Available from http://www.ncbi.nlm.nih.gov/books/NBK45947/
- Background: PubMed 25055312Clifton DA, Wong D, Clifton L, Wilson S, Way R, Pullinger R, Tarassenko L. A large-scale clinical validation of an integrated monitoring system in the emergency department. IEEE J Biomed Health Inform. 2013 Jul;17(4):835-42. doi: 10.1109/JBHI.2012.2234130.
- Background: PubMed 18342422Fuhrmann L, Lippert A, Perner A, Ostergaard D. Incidence, staff awareness and mortality of patients at risk on general wards. Resuscitation. 2008 Jun;77(3):325-30. doi: 10.1016/j.resuscitation.2008.01.009. Epub 2008 Mar 14.
- Background: PubMed 24361459Murray A, Kellett J, Huang W, Woodworth S, Wang F. Trajectories of the averaged abbreviated Vitalpac early warning score (AbEWS) and clinical course of 44,531 consecutive admissions hospitalized for acute medical illness. Resuscitation. 2014 Apr;85(4):544-8. doi: 10.1016/j.resuscitation.2013.12.015. Epub 2013 Dec 21.
- Background: PubMed 16945465Smith GB, Prytherch DR, Schmidt P, Featherstone PI, Knight D, Clements G, Mohammed MA. Hospital-wide physiological surveillance-a new approach to the early identification and management of the sick patient. Resuscitation. 2006 Oct;71(1):19-28. doi: 10.1016/j.resuscitation.2006.03.008. Epub 2006 Aug 30.
- Background: PubMed 18064532Gorges M, Staggers N. Evaluations of physiological monitoring displays: a systematic review. J Clin Monit Comput. 2008 Feb;22(1):45-66. doi: 10.1007/s10877-007-9106-8. Epub 2007 Dec 7.
- Individual participant dataSharing planned: No
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing PDWS Intervension in people with Patient Transfer to Intensive Care Unit (Procedure) and Respiratory Arrest (Disorder), run by University of Southern Denmark at 2 sites in Denmark.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 23 Feb 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Denmark. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
In-hospital deterioration (time frame: Admission length (1-7 days)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03375658, which also lists 13 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Feb 2021.