We receive many emails enquiring about progress. As answering these takes time away from processing submissions, please email only if absolutely necessary. We are working hard to process registration and update requests as quickly as possible.

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been endorsed by the ANZCTR. Before participating in a study, talk to your health care provider and refer to this information for consumers
Trial registered on ANZCTR

Registration number
Ethics application status
Not yet submitted
Date submitted
Date registered
Date last updated
Date data sharing statement initially provided
Type of registration
Prospectively registered

Titles & IDs
Public title
The feasibility of using the clinical health tracker app and web-interface to assess surgical risk in elective surgical patients.
Scientific title
The feasibility of using the clinical health tracker app and web-interface to assess peri-operative risk in elective surgical patients.
Secondary ID [1] 298309 0
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Perioperative risk in elective surgical patients 312941 0
Condition category
Condition code
Anaesthesiology 311431 311431 0 0
Surgery 311515 311515 0 0
Other surgery

Study type
Description of intervention(s) / exposure
This study aims to assess whether a cross platform smartphone app, the Clinical Health Tracker App which reports the location of the participant's phone every 5 minutes and reports step data from HealthKit (iOS) and Google Fit (Android) when the phone has a Wi-Fi connection connection. The data reported from the app can be used to derive several measures that assess a patient's level of activity and participation, which represent a patient's level of disability. This information on disability could then potentially be used to predict surgical risk and outcome.

To use the Clinical Health Tracker app, patients must own a smartphone. Patients will be provided with information on how to download and activate the app before surgery and how to remove it once the data is collected (3 months after discharge from hospital). This app is free to download from the app store. This app will be downloaded at least 2 weeks prior to surgery.

The Clinical Health Tracker App does not require any training to use as it works in the background. There are surveys in the app that are activated by push activation that are used to reactivate the app should it stop sending data. Hence, the patient only needs to download the app onto their smartphone and leave the app on their phone- the app will report the step and GPS data automatically in the background for 3 months post surgery.

Intervention code [1] 314541 0
Diagnosis / Prognosis
Intervention code [2] 314542 0
Treatment: Devices
Comparator / control treatment
No control group
Control group

Primary outcome [1] 320153 0
Feasibility of smartphone follow up
The number of patients who consent and use the app will be measured, as well as a a record the number of days of complete data for each participant.
This will be assessed by analysing data obtained from the app on an excel spreadsheet.
Timepoint [1] 320153 0
3 months post surgery
Primary outcome [2] 320154 0
Step count outcomes
Includes proportion of time spent inactive, daily step count, distance walked, average walking speed. This is a composite outcome
This will be assessed through summary data on an excel spreadsheet derived from the app.

Timepoint [2] 320154 0
3 months post surgery
Primary outcome [3] 320155 0
Hospital Outcomes
Number of days free from hospital, nursing home care or rehabilitation at 3 months and death during hospital stay and at 3 months. This is a composite outcome
This data will be collected through medical records
Timepoint [3] 320155 0
3 months post surgery
Secondary outcome [1] 370728 0
Patient satisfaction
Patient satisfaction with the use of a smartphone app for follow-up will be assessed with a survey designed specifically for this study
Timepoint [1] 370728 0
3 months post surgery
Secondary outcome [2] 370909 0
GPS outcomes
Includes time spent at home, linear distance travelled, number of locations visited, minimum convex polygon activity space (area of a polygon that bounds the GPS locations) and standard deviation ellipse activity space (the area of an ellipse plotted from the mean longitude and latitude). This is a composite outcome.
This will be assessed through summary data on an excel spreadsheet derived from the app.

NB: This is a Primary Outcome
Timepoint [2] 370909 0
3 months post surgery

Key inclusion criteria
Undergoing elective surgery greater than 14 days from recruitment
Aged over 18
Own a smartphone
Minimum age
18 Years
Maximum age
No limit
Both males and females
Can healthy volunteers participate?
Key exclusion criteria
Refusal or inability to give informed consent
Undergoing cardiothoracic surgery

Study design
Purpose of the study
Allocation to intervention
Non-randomised trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Not applicable
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Not applicable
Masking / blinding
Open (masking not used)
Who is / are masked / blinded?

Intervention assignment
Single group
Other design features
Not Applicable
Type of endpoint(s)
Statistical methods / analysis
Continuous data will be described by mean (standard deviation) or median [interquartile range] depending upon normality of distribution. Categorical data will be summarised as number (percentage).

Where repeated measures exist, population average point estimates and between group comparisons will employ generalised estimating equations.
Concordance between like measures will be assessed by Lin’s concordance correlation statistic and Bland-Altman limits of agreement and correlation by Pearson or Spearman correlation coefficient, depending on appropriateness, and Bland-Altman Analysis.

Recruitment status
Not yet recruiting
Date of first participant enrolment
Date of last participant enrolment
Date of last data collection
Sample size
Accrual to date
Recruitment in Australia
Recruitment state(s)
Recruitment hospital [1] 13815 0
The Royal Adelaide Hospital - Adelaide
Recruitment hospital [2] 13816 0
Flinders Medical Centre - Bedford Park
Recruitment hospital [3] 13817 0
Lyell McEwin Hospital - Elizabeth Vale
Recruitment postcode(s) [1] 26568 0
5000 - Adelaide
Recruitment postcode(s) [2] 26569 0
5042 - Bedford Park
Recruitment postcode(s) [3] 26570 0
5112 - Elizabeth Vale

Funding & Sponsors
Funding source category [1] 302851 0
Self funded/Unfunded
Name [1] 302851 0
Address [1] 302851 0
Not applicable
Country [1] 302851 0
Primary sponsor type
Samuel Gluck
Intensive Care Unit
Royal Adelaide Hospital
1 Port Road
SA 5000
Secondary sponsor category [1] 302798 0
Name [1] 302798 0
Address [1] 302798 0
Country [1] 302798 0

Ethics approval
Ethics application status
Not yet submitted
Ethics committee name [1] 303426 0
Central Adelaide Local Health Network Human Research Ethics Committee
Ethics committee address [1] 303426 0
Level 3, Roma Mitchell House
136 North Terrace, ADELAIDE SA 5000

Ethics committee country [1] 303426 0
Date submitted for ethics approval [1] 303426 0
Approval date [1] 303426 0
Ethics approval number [1] 303426 0

Brief summary
The World Health Organisations International Classification of Function describes disability as the relationship between body function, activity levels and the level of participation. A patient’s level of disability has been shown to have adverse associations with surgical outcome. We have remotely measured patients’ activity and participation, continuously and objectively, using a cross platform smartphone application (app). The app reports step and Global Positioning System (GPS) data to a cloud database. Patients are generally accepting of this technology and show high levels of satisfaction with the process. We have used the data to generate meaningful outcomes for patients such as time spent at home and step counts. We have monitored patients prior to and following cardiothoracic surgery.
These data will have a role in perioperative assessment. Currently perioperative assessment is performed using questionnaires and clinical assessment. These achieve a C-statistic for mortality prediction of 0.8-0.9.
Machine learning techniques will enable the smartphone data to generate more accurate risk models for patients undergoing surgery and provide prediction for long-term patient-centred outcomes.
Our objective is to assess the feasibility for a larger study. We intend to conduct a multicentre study enrolling 500 smartphone owning patients undergoing surgery at one of three centres in South Australia. Patients will receive a letter with instructions on how to install our app pre-operatively and be followed up for 90 days.
We will report the time taken to achieve ethics and governance approval at each site and the number of patients who successfully activate the app at least seven days prior to surgery. We will report on the completeness of the step and GPS data from the individuals enrolled. We will use the data to power a larger study to predict days free from hospital at 90-days, time spent at home, daily step count and time spent inactive at 90-days.

Plain English Statement
Increasingly patients own smartphones. The multitude of sensors held in these devices allow for remote monitoring of patients. We believe that by using these data in a machine learning model, we will improve the prediction of risk of surgery, and also provide data on outcomes that are more meaningful to patients. We intend to assess the feasibility of using a smartphone app to monitor patients prior to and following surgery.
Trial website
Trial related presentations / publications
Public notes

Principal investigator
Name 93638 0
Dr Samuel Gluck
Address 93638 0
Intensive Care Unit
Royal Adelaide Hospital
1 Port Road
SA 5000
Country 93638 0
Phone 93638 0
+61 423 580 064
Fax 93638 0
Email 93638 0
Contact person for public queries
Name 93639 0
Dr Samuel Gluck
Address 93639 0
Intensive Care Unit
Royal Adelaide Hospital
1 Port Road
SA 5000
Country 93639 0
Phone 93639 0
+61 423 580 064
Fax 93639 0
Email 93639 0
Contact person for scientific queries
Name 93640 0
Dr Samuel Gluck
Address 93640 0
Intensive Care Unit
Royal Adelaide Hospital
1 Port Road
SA 5000
Country 93640 0
Phone 93640 0
+61 423 580 064
Fax 93640 0
Email 93640 0

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No/undecided IPD sharing reason/comment
All participant data will be de-identified to comply with SA Health Confidentiality Guidelines
What supporting documents are/will be available?
Informed consent form
Clinical study report
Summary results
No Results