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Trial registered on ANZCTR


Registration number
ACTRN12617000980336
Ethics application status
Approved
Date submitted
2/07/2017
Date registered
7/07/2017
Date last updated
12/03/2018
Type of registration
Prospectively registered

Titles & IDs
Public title
Rethinking model of specialist diabetes care utilising eHealth to improve clinical outcomes in complex type 2 diabetes
Scientific title
The clinical efficacy of a new model of care employing eHealth intervention in type 2 diabetes patients with suboptimal glycaemic control attending an outpatient specialist clinic as compared to usual care.
Secondary ID [1] 291374 0
None
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Type 2 Diabetes 302364 0
Condition category
Condition code
Metabolic and Endocrine 301949 301949 0 0
Diabetes
Public Health 302255 302255 0 0
Health service research

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
In partnership with CSIRO, a mobile-based disease monitoring system (MDMS) has been developed for people with diabetes (MDMS- Diabetes). This system was modelled on a highly successful CSIRO platform that supports in-home cardiac rehabilitation which resulted in improvements in adherence and clinical outcomes . This platform has been modified to enable real time monitoring of blood glucose levels in patients with diabetes, and support patient care. The system comprises an app for iOS (Apple) and Android based smartphones, and a web-based clinical portal. The mobile app enables participants to use a Bluetooth-enabled glucose meter (AVIVA Connect, Roche) to automatically upload their BGL readings to the clinical portal. The mobile app also provides an insulin diary that allows participants to manually enter their insulin injections’ dose and time, along with free text comment for each dose (e.g. "before dinner"). These data are subsequently transmitted and uploaded to the clinical portal via a mobile internet connection such as Wi-Fi, 3G or 4G. The clinical portal presents the uploaded data in graphical and tabular formats, for the DNEs and endocrinologists to monitor and manage a patient's condition. Integrated alerts, which can be customised by clinicians, highlight out of range measures. Patients receive individual, computer generated alerts based on the frequency of BGL testing and BGL values. Individual patient screens enable a review of progress in advance of conventional outpatient encounters or in the course of telephone consultations. Through the portal, the clinicians can review the participants’ BGL data, insulin dosages, and send messages to the participants’ mobile phones. A summary of their diabetes care is also displayed based on the clinical information entered.

Using the MRMS platform, an alternative model of outpatient service delivery has been designed at Princess Alexandra Hospital , which incorporates the following elements:
1. Short or long-term monitoring of BGL, insulin dosage using the MRMS.
2. Targeting of intensive MRMS use to patients with suboptimal control.
3. Computer generated alerts sent to patient via text message.
4. Patient input before each clinic visit via online survey
5. Substitution of conventional in-person follow-up consultations with telephone or video-consultations

The participants will be followed up for 12 months.
Intervention code [1] 297400 0
Treatment: Other
Comparator / control treatment
The control group will have routine care provided by the endocrinology staff. The control group will be provided with standard glucose meters if their current glucose meter is more than 2 years old and followed up as per current model of care.

The current model of diabetes care at a tertiary hospital, the Princess Alexandra Hospital (PAH), entails regular outpatient clinic visits to access a multidisciplinary team led by an endocrinologist. The interval between patient visits is determined by an endocrinologist - based on glycaemic control and comorbidities. This can vary between 4 weeks to 6 months. Typically, a person with an HbA1c over 8% would be reviewed within 3 months. Visits may involve patients travelling for long distances; prolonged wait times at the clinic and absence from their workplace. Access to BGL data is often mediated through patient provided paper records, or data dumps from a variety of commercial glucose meters. This process can be unreliable and inefficient. Patients with sub-optimal glycaemic control often require insulin dose adjustment.
Control group
Active

Outcomes
Primary outcome [1] 301370 0
Change in HbA1c. HbA1c is measured in serum using high performance liquid chromatography method.
Timepoint [1] 301370 0
0, 3, 6 and 12 months
Secondary outcome [1] 332453 0
Patient Satisfaction using a questionnaire designed specifically for the study for both controls and intervention. The Service User Technology Acceptability Questionnaire (SUTAQ) will be used for the intervention group at 6 and 12 months of follow up.
Timepoint [1] 332453 0
0,6 and 12 months
Secondary outcome [2] 332455 0
Time to target HbA1c;
Timepoint [2] 332455 0
12 months
Secondary outcome [3] 332456 0
Quality of Life assessed using AQOL (Assessment of Quality of Life) questionnaire.
Timepoint [3] 332456 0
12 months
Secondary outcome [4] 332457 0
Number of clinic appointments. This data will be accessed from the hospital electronic medical records.
Timepoint [4] 332457 0
12 months
Secondary outcome [5] 332458 0
Adherence to diabetes complication screening. This will be assessed based on the management plan drawn for each diabetes participant at the beginning of the study.
Timepoint [5] 332458 0
12 months
Secondary outcome [6] 336545 0
Costs from patient perspective. This will be assessed based on their travel related costs,time off work and need for a carer. A patient questionnaire designed specifically for this study will be used to collect data.
Timepoint [6] 336545 0
12 months
Secondary outcome [7] 336645 0
Health care provider satisfaction. This will be assessed by a questionnaire designed specifically for this study.
Timepoint [7] 336645 0
6 months and end of study ( after the last participant has finished 12 month follow up)
Secondary outcome [8] 336646 0
Percentage of participants achieving target HbA1c
Timepoint [8] 336646 0
6 and 12 months
Secondary outcome [9] 336647 0
Blood Pressure,
Timepoint [9] 336647 0
0, 3, 6 and 12 months
Secondary outcome [10] 336648 0
Serum Lipid Profile
Timepoint [10] 336648 0
0, 3, 6 and 12 months
Secondary outcome [11] 336649 0
Body Mass Index
Timepoint [11] 336649 0
0, 3, 6 and 12 months
Secondary outcome [12] 336650 0
Hypoglycaemia events in the 12th month of follow up. This will be assessed by the review of the webportal and glucose meter.
Timepoint [12] 336650 0
6 and 12 months
Secondary outcome [13] 336651 0
Hypoglycaemia events requiring assistance (that is requiring help from another person or medical support to correct hypoglycaemia). This will be assessed by accessing medical records and participant questionnaire.
Timepoint [13] 336651 0
6 and 12 months
Secondary outcome [14] 336658 0
Cost from Health care provider perspective. This is assessed by collecting costs related to clinician time, hospital appointments, hospital admissions, general practitioner visits, and medications. This will be ascertained by a patient questionnaire, times as recorded by the research nurse and by review of medical records.
Timepoint [14] 336658 0
12 months
Secondary outcome [15] 336661 0
Number of patients discharged as a result of 'good' glycaemic control. The evaluation of 'good' glycaemic control will be as ascertained by the treatment clinician, based on the individual management plan . This data will be accessed from the hospital electronic medical records.
Timepoint [15] 336661 0
12 months
Secondary outcome [16] 336662 0
Failed to attend rates at clinic appointments. This data will be accessed from the hospital electronic medical records.
Timepoint [16] 336662 0
12 months
Secondary outcome [17] 336720 0
Type of clinic appointments ( that is whether telehealth or outpatient face to face appointments). This data will be obtained from the hospital electronic records.
Timepoint [17] 336720 0
12 months

Eligibility
Key inclusion criteria
Type 2 Diabetes Mellitus ( diagnosed for at least 6 months) attending the outpatient clinic at the Princess Alexandra Hospital

HbA1c > 8% ( done within 4 weeks of the trial)

Age > 18 yrs

Using a smartphone/tablet

Able to communicate in English
Minimum age
18 Years
Maximum age
No limit
Gender
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
No access to reliable internet connection (3G/4G/Wi-Fi)
Pregnant
Type 1 DM
Complex unstable medical conditions (participants likely to require frequent hospital admissions unrelated to diabetes glycaemic control; those on weaning doses of medications which can impact on glycaemic control and those with bariatric surgery in the last one year)
Enrolled in another interventional study

Study design
Purpose of the study
Treatment
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Central randomization by REDCAP software
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Stratified randomization - REDCAP software
New patient referred to the clinic
Patient on insulin
Masking / blinding
Open (masking not used)
Who is / are masked / blinded?



Intervention assignment
Parallel
Other design features
Phase
Not Applicable
Type of endpoint(s)
Efficacy
Statistical methods / analysis
It is a pilot pragmatic RCT. A sample size estimation to show a mean difference of HbA1c of 0.5% between the two arms with a power of 0.8 and alpha of 0.05 using the Student’s t test revealed that we would require 124 participants in each arm (SD of 1.4). Recruitment of this number of patients was considered unfeasible. We will recruit 44 patients with 20 patients in each arm ( allowing for an attrition rate of 10%). This sample size of 20 was selected on the basis of previous studies.

Statistical analysis will be done using Stata 15 (StataCorp. 2017. Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC). Primary analyses will be based on ‘intention to treat’ . A per protocol analysis will also be done. Differences between groups at baseline and the endpoint will be compared using either the Student’s t-test or Mann-Whitney U-test as appropriate. Differences in repeated measurements will be compared using Mixed-effects Model, adjusting for any significant explanatory variables. A p value of less than 0.05 will be considered statistically significant.

A subgroup analysis of the participants new to the service and on insulin shall be carried out. Participants who are on insulin might require dose adjustments and thus might use the MRMS to interact with health care providers more often. Participants being referred to the specialist diabetes service might have different characteristics to the diabetes patients, already known to the service, with sub-optimal control despite specialist input.

An economic analysis will be undertaken from the perspective of the healthcare system and patient perspective. The research costs will be excluded from this analysis so that the intervention group can be compared to a usual care group. This enables results to be generalised beyond a research setting. We will collect data to accurately record costs at the patient and health care provider levels. Cost data will include time required to train patients by the staff regarding the glucose meter and software. The outcome data as outlined above will enable both cost-efficacy and cost-utility analyses to be performed. Sensitivity analyses will enable these estimates to be adjusted for expected cost reductions associated with increased use and price reduction as the technology improves.

Recruitment
Recruitment status
Active, not recruiting
Date of first participant enrolment
Anticipated
Actual
Date of last participant enrolment
Anticipated
Actual
Date of last data collection
Anticipated
Actual
Sample size
Target
Accrual to date
Final
Recruitment in Australia
Recruitment state(s)
QLD
Recruitment hospital [1] 7609 0
Princess Alexandra Hospital - Woolloongabba
Recruitment postcode(s) [1] 15510 0
4102 - Woolloongabba

Funding & Sponsors
Funding source category [1] 295846 0
Government body
Name [1] 295846 0
Telehealth Seed funding, Department of Health. Queensland Health
Address [1] 295846 0
Queensland Health
Location
Queensland Health Building
147-163 Charlotte Street
Brisbane Queensland Australia

Postal address
GPO Box 48 Brisbane, Queensland 4001 Australia
Country [1] 295846 0
Australia
Primary sponsor type
Individual
Name
Anish Menon
Address
Centre for Online Health, University of Queensland
Ground Floor, Building 33
PA Hospital
Woolloongabba
QLD -4102
Country
Australia
Secondary sponsor category [1] 294701 0
Individual
Name [1] 294701 0
Prof Len Gray
Address [1] 294701 0
Centre for Online Health, University of Queensland
Ground Floor, Building 33
PA Hospital
Woolloongabba
QLD -4102
Country [1] 294701 0
Australia
Secondary sponsor category [2] 294703 0
Individual
Name [2] 294703 0
A/Prof Anthony Russell
Address [2] 294703 0
Dept of Diabetes & Endocrinology
Main Building, Princess Alexandra Hospital
Woolloongabba
QLD -4102
Country [2] 294703 0
Australia
Secondary sponsor category [3] 294704 0
Individual
Name [3] 294704 0
Dr Farhad Fatehi
Address [3] 294704 0
Centre for Online Health, University of Queensland
Ground Floor, Building 33
PA Hospital
Woolloongabba
QLD -4102
Country [3] 294704 0
Australia
Secondary sponsor category [4] 294705 0
Individual
Name [4] 294705 0
Dr Dominique Bird
Address [4] 294705 0
Centre for Online Health, University of Queensland
Ground Floor, Building 33
PA Hospital
Woolloongabba
QLD -4102
Country [4] 294705 0
Australia
Secondary sponsor category [5] 294706 0
Individual
Name [5] 294706 0
Dr Mohan Karunanithi
Address [5] 294706 0
The Australian E-Health Research Centre
CSIRO Health and Biosecurity. Level 5 - UQ Health Sciences Building 901/16,
Royal Brisbane and Women's Hospital, Herston, 4029, Brisbane, Queensland,
Country [5] 294706 0
Australia
Secondary sponsor category [6] 295722 0
Individual
Name [6] 295722 0
Darsy Darshan
Address [6] 295722 0
Centre for Health Services Research | Faculty of Medicine | The University of Queensland
Level 5, R-Wing, Princess Alexandra Hospital, Ipswich Rd, Woolloongabba QLD 4102
Country [6] 295722 0
Australia

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 297128 0
Metro South Human Research Ethics Committee
Ethics committee address [1] 297128 0
Centres for Health Research
Princess Alexandra Hospital
Woolloongabba
QLD -4102
Ethics committee country [1] 297128 0
Australia
Date submitted for ethics approval [1] 297128 0
19/05/2016
Approval date [1] 297128 0
23/08/2016
Ethics approval number [1] 297128 0
HREC/16/QPAH/373

Summary
Brief summary
Current service model for specialist diabetes care is based in a tertiary setting and involves care by a multidisciplinary team led by the endocrinologist. Continuation of conventional approaches with unchanged outcomes will require dramatic and potentially unaffordable expansion of current services to meet the increasing demand.

The primary aim of this proposal is to determine the clinical efficacy of a new model of care employing mHealth (mobile Health) intervention in diabetes patients with suboptimal
glycaemic control attending an outpatient specialist clinic as compared to usual care. This study follows on from a proof of concept and feasibility of mobile-based remote monitoring for stabilisation of insulin therapy in type 2 diabetes.

Mobilehealth (Use of mobile technology like smartphone in health care management) create an opportunity to redesign outpatient services and meet unmet demands of existing healthcare. Collaboration between Diabetes and Endocrinology Department at Princess Alexandra Hospital (PAH), the UQ Centre for Online Health and the CSIRO has led to the development of a mobile-based remote monitoring system to support the management of complex outpatient diabetes patients. This system utilises a Bluetooth-enabled glucose meter to automatically transfer blood glucose levels to a clinician dashboard via an application installed on the patient’s smartphone. This will enable the endocrinologist/diabetes nurse to remotely monitor blood glucose levels and communicate with the patient in real time. The clinical data shall only be reviewed at set times decided by the clinician or on patient request and will not be continuously monitored. Patients receive individual alerts based on the frequency of BGL testing and BGL values. Individual patient screens enable a review of progress in advance of conventional outpatient encounters or during telephone consultations.

Type 2 diabetes patients attending the outpatient diabetes clinic at the PAH shall be invited to attend. They shall be randomised to the intervention or control group with both groups followed up for a year. Control group shall receive routine care. The intervention group shall use the mobile-based remote monitoring system. Based on the data received in the intervention group, the endocrinologist in liaison with the patient shall decide to substitute scheduled face to face clinic consultation with virtual clinics ( via videoconference
or telephone at home) if required. They will be required to get recommended pathology tests before their consultation as per routine practice. The patients have the option to enter via an online survey, relevant details before their intended clinic appointment.

The participants will be followed for 12 months. We expect the new model of care will improve diabetes-related clinical outcomes, with improvement in patient and health care provider satisfaction at similar or lower costs.
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 73074 0
Dr Anish Menon
Address 73074 0
Centre for Online Health, University of Queensland
Ground Floor, Building 33
PA Hospital
Woolloongabba
QLD -4102
Country 73074 0
Australia
Phone 73074 0
+61 7 3176 8187
Fax 73074 0
Email 73074 0
anish.menon@uq.net.au
Contact person for public queries
Name 73075 0
Dr Anish Menon
Address 73075 0
Centre for Online Health, University of Queensland
Ground Floor, Building 33
PA Hospital
Woolloongabba
QLD -4102
Country 73075 0
Australia
Phone 73075 0
+61 7 3176 8187
Fax 73075 0
Email 73075 0
anish.menon@uq.net.au
Contact person for scientific queries
Name 73076 0
Dr Anish Menon
Address 73076 0
Centre for Online Health, University of Queensland
Ground Floor, Building 33
PA Hospital
Woolloongabba
QLD -4102
Country 73076 0
Australia
Phone 73076 0
+61 7 3176 8187
Fax 73076 0
Email 73076 0
anish.menon@uq.net.au

No data has been provided for results reporting
Summary results
Have study results been published in a peer-reviewed journal?
Other publications
Have study results been made publicly available in another format?
Results – basic reporting
Results – plain English summary