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Trial registered on ANZCTR
Registration number
ACTRN12618001559202
Ethics application status
Approved
Date submitted
30/08/2018
Date registered
18/09/2018
Date last updated
9/01/2019
Date data sharing statement initially provided
9/01/2019
Type of registration
Prospectively registered
Titles & IDs
Public title
Vital Signs Monitoring and Clinical Decision Support System for Early Detection of Deteriorating Patients
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Scientific title
Auto-escalation of deteriorating patients using real-time vital signs monitoring in acute care settings
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Secondary ID [1]
295964
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Nil
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Universal Trial Number (UTN)
U1111-1219-4342
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Trial acronym
None
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Linked study record
None
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Health condition
Health condition(s) or problem(s) studied:
Vital Signs Monitoring
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Patient Deterioration
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Condition category
Condition code
Public Health
308307
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0
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Health service research
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Intervention/exposure
Study type
Observational
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Patient registry
False
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Target follow-up duration
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Target follow-up type
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Description of intervention(s) / exposure
We propose the development of a smart and remote monitoring and alarm system for use by hospital staff. The information (blood pressure, heart rate, pulse volume and temperature) will be collated and used to make assessment of the patients’ state of well-being.
Wireless devices such as finger clip pulse oximeter, arm-cuff blood pressure, digital ear thermometer, 2-lead ECG monitor and mobile phone communication will be employed in the proposed system to provide a user friendly and accurate vitals monitoring. The vital sings can be collected using wearable and wireless devices without interrupting the usual activities of the patients. Due to the availability of mobile phone technology among doctors and nurses, the alarms and other important information will be transmitted via a mobile phone system to the nursing station and/or to the clinician.
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Intervention code [1]
312289
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Early Detection / Screening
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Comparator / control treatment
We will compare our results with the current practice at ward for monitoring of vitals using the ward collected early warning score (EWS) and also by comparing the ward escalations criteria during the study validation (4-6 months). This outcome will also be validated with two different methods, i.e. comparing with similar monitoring systems and by agreement using Kappa analysis.
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Control group
Active
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Outcomes
Primary outcome [1]
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Early detection of deteriorating patient when compared to the traditional methods. We will use the historic early warning score data (for the entire duration of the study validation) and compare it with the validation dataset to analyse the early detection of deteriorating patients. Also, this outcome will be validated by agreement with the expert using Kappa analysis.
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Assessment method [1]
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Timepoint [1]
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The vital signs will be collected 2-4 hourly depending on the hospital ward’s protocols until patient’s discharge. The data will be collected for 4-6 months post implementation.
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Secondary outcome [1]
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Staff time saved in auto-escalation of deteriorating patient compared to the manual method. This outcome will be validated with two different methods, i.e. comparing with the current ward monitoring system and by agreement using Kappa analysis.
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Assessment method [1]
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Timepoint [1]
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The escalation process could be generated upon every calculation of early warning score – 2-4 hourly until patient discharge.
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Eligibility
Key inclusion criteria
Patients on General Medicine ward of North Shore Hospital (male and female).
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Minimum age
18
Years
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Maximum age
No limit
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Sex
Both males and females
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Can healthy volunteers participate?
No
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Key exclusion criteria
Exclusion of refusal of inform consent; Hodkinson AMT 7/10 or less (Hodkinson H. M., 1972), patients deemed unsuitable by medical or nursing staff, terminally ill patients and patients on any other monitoring device.
Reference: Hodkinson H. M. (1972). EVALUATION OF A MENTAL TEST SCORE FOR ASSESSMENT OF MENTAL IMPAIRMENT IN THE ELDERLY. Age and Ageing, 1, 233-238.
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Study design
Purpose
Screening
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Duration
Longitudinal
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Selection
Random sample
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Timing
Prospective
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Statistical methods / analysis
For sample size calculation it is assumed that the significance level of 0.05, power of 0.95, the effect size of 0.6 (mean difference 1.2 and SD 2). The calculation returned the sample size of 30. Also from our previous research experience (Anaesthesia monitoring using 30 patients, we propose the minimum sample size to be 30, which is achievable in one and a half year (50% of the whole project time). All the above calculations are carried out using G*Power 3.1.3 (Reference: Faul, F., Erdfelder, E., Lang, A.-G. & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175-191).
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Recruitment
Recruitment status
Not yet recruiting
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Date of first participant enrolment
Anticipated
1/06/2019
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Actual
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Date of last participant enrolment
Anticipated
30/09/2019
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Actual
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Date of last data collection
Anticipated
30/11/2019
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Actual
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Sample size
Target
30
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Accrual to date
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Final
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Recruitment outside Australia
Country [1]
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New Zealand
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State/province [1]
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Auckland
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Funding & Sponsors
Funding source category [1]
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Other Collaborative groups
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Name [1]
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Precision Driven Health Research Partnership
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Address [1]
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181, Grafton Road, Grafton, Auckland, 1010, New Zealand
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Country [1]
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New Zealand
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Primary sponsor type
University
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Name
Auckland University of Technology
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Address
55 Wellesley Street East, Auckland City Campus, Auckland, 1010, New Zealand
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Country
New Zealand
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Secondary sponsor category [1]
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None
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Name [1]
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Address [1]
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Country [1]
300144
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Ethics approval
Ethics application status
Approved
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Ethics committee name [1]
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Health and Disability Ethics Committee - Central
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Ethics committee address [1]
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133 Molesworth Street Thorndon Wellington 6011
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Ethics committee country [1]
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New Zealand
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Date submitted for ethics approval [1]
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23/10/2018
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Approval date [1]
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21/12/2018
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Ethics approval number [1]
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18/CEN/216
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Summary
Brief summary
We propose the development of a smart vital signs monitoring system for use by hospital staff. The information (blood pressure, heart rate, oxigen saturrration, and temperature) will be used to assess the patient’s state of wellness. The vital signs can be collected using wearable and wireless devices (vital signs devices) without interrupting the usual activities of the patients. Due to the availability of mobile phone technology among doctors and nurses, the alarms and other relevant information will be transmitted via a mobile phone to the clinicians. Impact of the proposed system will be measured as 1) time saved in the collection of routine observations, 2) reduced time taken for alerting a critical care outreach team through the automated presentation of the Early Warning Score (EWS), and 3) reduced hospital length of stay (LOS).
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Trial website
www.vitalsassist.com
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Trial related presentations / publications
None
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Public notes
None
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Contacts
Principal investigator
Name
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A/Prof Hamid GholamHosseini
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Address
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Auckland University of Technology
55, Wakefield Street East
Auckland Central, NZ.
Auckland 114
Private Bag 92006
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Country
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New Zealand
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Phone
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+64 9 921 9999
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Fax
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Email
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[email protected]
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Contact person for public queries
Name
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Hamid GholamHosseini
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Address
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Auckland University of Technology
55, Wakefield Street East
Auckland Central, NZ.
Auckland 114
Private Bag 92006
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Country
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New Zealand
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Phone
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+64 9 921 9999
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Fax
86715
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Email
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[email protected]
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Contact person for scientific queries
Name
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Hamid GholamHosseini
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Address
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Auckland University of Technology
55, Wakefield Street East
Auckland Central, NZ.
Auckland 114
Private Bag 92006
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Country
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New Zealand
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Phone
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+64 9 921 9999
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Fax
86716
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Email
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[email protected]
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Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
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No/undecided IPD sharing reason/comment
The individual participant data or any otehr trial related data will not be made available due to the privacy and security.
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What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
Documents added manually
No documents have been uploaded by study researchers.
Documents added automatically
No additional documents have been identified.
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