Trial Review

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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
Scientific title
Auto-escalation of deteriorating patients using real-time vital signs monitoring in acute care settings
Secondary ID [1] 295964 0
Nil
Universal Trial Number (UTN)
U1111-1219-4342
Trial acronym
None
Linked study record
None

Health condition
Health condition(s) or problem(s) studied:
Vital Signs Monitoring 309472 0
Patient Deterioration 309473 0
Condition category
Condition code
Public Health 308307 308307 0 0
Health service research

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
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.
Intervention code [1] 312289 0
Early Detection / Screening
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.
Control group
Active

Outcomes
Primary outcome [1] 307280 0
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.
Timepoint [1] 307280 0
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.
Secondary outcome [1] 351356 0
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.
Timepoint [1] 351356 0
The escalation process could be generated upon every calculation of early warning score – 2-4 hourly until patient discharge.

Eligibility
Key inclusion criteria
Patients on General Medicine ward of North Shore Hospital (male and female).
Minimum age
18 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
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.

Study design
Purpose
Screening
Duration
Longitudinal
Selection
Random sample
Timing
Prospective
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).

Recruitment
Recruitment status
Not yet recruiting
Date of first participant enrolment
Anticipated
1/06/2019
Actual
Date of last participant enrolment
Anticipated
30/09/2019
Actual
Date of last data collection
Anticipated
30/11/2019
Actual
Sample size
Target
30
Accrual to date
Final
Recruitment outside Australia
Country [1] 20820 0
New Zealand
State/province [1] 20820 0
Auckland

Funding & Sponsors
Funding source category [1] 300561 0
Other Collaborative groups
Name [1] 300561 0
Precision Driven Health Research Partnership
Country [1] 300561 0
New Zealand
Primary sponsor type
University
Name
Auckland University of Technology
Address
55 Wellesley Street East, Auckland City Campus, Auckland, 1010, New Zealand
Country
New Zealand
Secondary sponsor category [1] 300144 0
None
Name [1] 300144 0
Address [1] 300144 0
Country [1] 300144 0

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 301353 0
Health and Disability Ethics Committee - Central
Ethics committee address [1] 301353 0
133 Molesworth Street
Thorndon
Wellington 6011
Ethics committee country [1] 301353 0
New Zealand
Date submitted for ethics approval [1] 301353 0
23/10/2018
Approval date [1] 301353 0
21/12/2018
Ethics approval number [1] 301353 0
18/CEN/216

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).
Trial website
www.vitalsassist.com
Trial related presentations / publications
None
Public notes
None

Contacts
Principal investigator
Name 86714 0
A/Prof Hamid GholamHosseini
Address 86714 0
Auckland University of Technology
55, Wakefield Street East
Auckland Central, NZ.
Auckland 114
Private Bag 92006
Country 86714 0
New Zealand
Phone 86714 0
+64 9 921 9999
Fax 86714 0
Email 86714 0
[email protected]
Contact person for public queries
Name 86715 0
A/Prof Hamid GholamHosseini
Address 86715 0
Auckland University of Technology
55, Wakefield Street East
Auckland Central, NZ.
Auckland 114
Private Bag 92006
Country 86715 0
New Zealand
Phone 86715 0
+64 9 921 9999
Fax 86715 0
Email 86715 0
[email protected]
Contact person for scientific queries
Name 86716 0
A/Prof Hamid GholamHosseini
Address 86716 0
Auckland University of Technology
55, Wakefield Street East
Auckland Central, NZ.
Auckland 114
Private Bag 92006
Country 86716 0
New Zealand
Phone 86716 0
+64 9 921 9999
Fax 86716 0
Email 86716 0
[email protected]

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No
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.


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.