Cardiac Arrest (Disorder) Clinical Trial
— PDWSOfficial title:
Cluster Randomized Trial of the Patient Deterioration Warning System in Emergency Departments
| Verified date | February 2021 |
| Source | University of Southern Denmark |
| Contact | n/a |
| Is FDA regulated | No |
| Health authority | |
| Study type | Interventional |
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.
| Status | Active, not recruiting |
| Enrollment | 6500 |
| Est. completion date | December 31, 2021 |
| Est. primary completion date | April 8, 2019 |
| Accepts healthy volunteers | No |
| Gender | All |
| Age group | 18 Years and older |
| Eligibility | Inclusion Criteria: - All adult patients admitted to the emergency department Exclusion Criteria: - Critically ill patients who die during their admission - Orthopedic patients with minor injuries |
| Country | Name | City | State |
|---|---|---|---|
| Denmark | Hospital of South Western Jutland | Esbjerg | Jylland |
| Denmark | Odense University Hospital | Odense | Fyn |
| Lead Sponsor | Collaborator |
|---|---|
| University of Southern Denmark | Hospital of South Western Jutland, Odense University Hospital |
Denmark,
Armstrong 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. — View Citation
Brabrand 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. — View Citation
Brier 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. — View Citation
Centre for Clinical Practice at NICE (UK). Acutely Ill Patients in Hospital: Recognition of and Response to Acute Illness in Adults in Hospital [Internet]. London: National Institute for Health and Clinical Excellence (UK); 2007 Jul. Available from http://www.ncbi.nlm.nih.gov/books/NBK45947/ — View Citation
Clifton 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. — View Citation
Fuhrmann L, Lippert A, Perner A, Østergaard 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. — View Citation
Görges M, Staggers N. Evaluations of physiological monitoring displays: a systematic review. J Clin Monit Comput. 2008 Feb;22(1):45-66. Epub 2007 Dec 7. Review. — View Citation
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. — View Citation
Kellett 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. — View Citation
Kidholm 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. — View Citation
Murray 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. — View Citation
Schmidt 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. — View Citation
Smith 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. Epub 2006 Aug 30. — View Citation
* Note: There are 13 references in all — Click here to view all references
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | 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. | Admission length (1-7 days) | |
| Secondary | 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. | 35 weeks | |
| Secondary | 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. | 35 weeks | |
| Secondary | Reduction in length of stay | Evaluation of differences in length of stay for patients admitted during the intervention and control arms respectively. | Admission length (1-7 days) | |
| Secondary | 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. | Admission length (1-7 days) |