Evaluate the Value of Telehomecare for Diabetes

Background

BlueStar is a smart-phone enabled application that is designed to serve as a virtual coach for patients. The app sends daily evidence-based, real-time messages as well as longitudinal feedback on how to improve diabetes management. Benefits have been demonstrated in time periods as brief as three months. One US based study showed a decrease in hospitalizations and emergency department visits among participants who use the application. The BlueStar application is the first application in the USA to be given FDA approval as a Mobile Prescription Therapy. There is a need to explore the effectiveness, utility and cost of the intervention in context of Canadian healthcare, before it can be scaled across the system.

This study is based on a model of "integrated knowledge translation", where the knowledge users of the study have been central to the development of the research project from the very beginning. By using this integrated knowledge translation strategy, this study is far more likely to demonstrate impact in health system policy and decision-making.

Research Objective:

The primary objective is to determine if a smart-phone based application designed to improve diabetes self-management and experience of care among patients with Type II diabetes improves clinical outcomes, patient experience and health system costs compared to the control group.

Study Hypothesis:

Patients randomized to receive the BlueStar application will have improved HbA1c levels compared with the control group. The intervention group will also show improved self-reported outcomes related to quality of life, disease self-management and experience of care. The intervention will also reduce episodes of self-reported hypoglycemia.

Intervention:

As part of the intervention, patients will be given a Samsung Smart phone with the BlueStar application pre-loaded. Participants will be able to interact with the application over the study period however they would like. They can enter a range of baseline clinical information. They are also able to enter ongoing information related to diabetes management including blood glucose values, food intake and activity levels.

Based on this information, the BlueStar system will attempt to improve diabetes management through two processes. First, the app provides customized, real-time, evidence based messages that impact motivation, behavior and education. The messaging is based on the Trans Theoretical Model on Behavior Change, which incorporates motivation, education and affirmation to create sustained behavior changes for positive health. The app also contains a library of videos that patient can access at any time including information on healthy eating, complications of unmanaged diabetes and how to use a glucometer.

Second, the application facilitates the transfer of this data to the clinician through Smart Visit reports that provides a clinical overview of their diabetes including recent blood sugar readings. The app will remind participants to print this document and bring it to clinical appointments every 3 months. However, if advised by their clinician, participants can print the smart report more frequently and send via fax to the clinician. This may be required for example if rapid titration of insulin and close monitoring of blood sugars are required.

Throughout the study participants will be able to contact their usual clinician at the diabetes education center if they have any questions about the application or the information presented. If the clinician is unable to answer the question they will have clear protocols on who to triage the question to (OTN IT support, PI etc.).

Study Design:

The study is a randomized, wait-list-control trial with 300 participants. The outcome assessors will be blinded to group allocation to compare the impact of the BlueStar application to usual care.

Participants will be randomized into one of two groups: an immediate treatment group (ITG) and a wait-list-control (WLC). The ITG group will immediately begin using the application, for a total duration of six months. The WLC will receive usual care for the first three months, at which point they will cross over to the intervention arm and use the application for a total of 3 months.

Recruitment:

Participants will be recruited from three institutions across Ontario, Canada over a 3 month period. The sites include the Diabetes Health Center in Thunder Bay, the Diabetes Education Center at North York General Hospital, and the Diabetes Education Centers belonging to the William Osler Health System in Brampton and Etobicoke, Ontario. These sites serve a diverse range of patients with diabetes and other complex health and social care needs, representing a wide range of the population of Ontario, including a large population of aboriginal people and new immigrants. Patients are typically followed at these clinics with appointments every 3 months.

Baseline Information:

The following information will be collected at baseline from all participants:

1. HbA1c: Patients will require an HbA1c value within 2 weeks of the enrollment date.
2. Baseline characteristics: Baseline information including demographics and health status will be collected using a case report form (CRF).
3. Standardized patient-reported outcome measures(PROMs)/patient-reported experience measures (PREMs): A set of standardized questionnaires related to the study hypothesis.
4. Patient reported health outcomes and utilization

Data Management:

All data generated by participants through the BlueStar application will be stored on OTN's highly secure, Toronto based data centers.

Utilization data generated through the BlueStar application will also be stored on the OTN data centers.

Management of additional research data for this multi-center study will be centrally coordinated by the Applied Health Research Centre (AHRC), which is a not-for-profit academic research organization at St. Michael's Hospital in Toronto, Canada. The AHRC has created and will host a secure, web-based data entry system, using REDCap™ software. Research assistants will enter clinical data and outcomes into the REDCap database, and administer patient surveys through this tool. AHRC will determine the randomization sequence. Data quality and completeness will be monitored on a weekly basis by the AHRC data manager throughout the data collection period, which is 6 months after randomization.

Healthcare utilization and cost outcome measures will be obtained from health administrative data available through the Institute for Clinical Evaluative Sciences (ICES). At the time of study enrollment, patients will be asked to provide consent to link their Ontario Health Insurance Plan (OHIP) number to health administrative data. This data will be used to determine frequency and intensity of healthcare utilization and overall individual costs using methods developed for use with Ontario data.

Data Analyses:

All analyses will be intention to treat.

Qualitative Realist Evaluation - Background:

In order to understand the contextual influences and practical processes by which the BlueStar application is implemented in practice, the investigators will use methods of qualitative Realist Evaluation. Realist Evaluation is a methodology used to "unpack the black box of implementation", examining the actual actions required by those involved in implementation to ensure the BlueStar application is taken up and used by the patients, caregivers, and health care providers involved. This methodology enables a rigorous assessment of the contextual influences and strategies by which the application is adopted or rejected, enabling researchers to understand how and why the implementation succeeds or fails.

Objectives:

The objective of the qualitative realist evaluation component of this study is to (a) understand how the BlueStar application is implemented in practice, (b) explore participants' perspectives of the usability and acceptability of the BlueStar application, and (c) examine the key issues associated with scaling applications such as BlueStar up across Ontario.

Methods:

The Realist Evaluation will occur alongside the pragmatic randomized trials described above, and will include two key methods. The first is qualitative interviews with key stakeholders involved in the implementation process, and the second is observations of the introduction and use of the virtual care interventions among participants. Specifically, qualitative interviews will be conducted with participants at each implementation site. Participants recruited for interviews will include 4 to 6 patients at each site (caregivers will be invited to participate in those interviews as well); 3 to 5 health care providers involved in the implementation process at each site (including at least one physician in each location); 2-4 organizational leaders who oversee the implementation process at each site (for example, Diabetes Education Centre Managers); and 5-7 health system decision makers involved in the implementation of virtual care initiatives in Ontario (for example, Local Health Integration Network leaders, Ministry of Health and Long Term Care staff and OTN leaders).

Qualitative interviews will include questions about (a) participants' experiences of learning about and using the technology; (b) changes to health care provider workflow required to effectively use the technology; (c) organizational changes required to support the technology; and (d) health system barriers and facilitators to effective implementation and evaluation. These qualitative interviews will be audio recorded and transcribed verbatim, and analyzed using thematic analysis strategies by the investigator team to identify key themes related to the implementation and evaluation of the virtual care initiatives in actual contexts of health care delivery in Ontario.

Observations as a qualitative method in this study will involve a researcher sitting in on the Health Care Provider (HCP) education session (led by the application service provider) in which the Blue Star application is introduced at 2 of the sites. The researcher will take detailed notes regarding how the technology is introduced to HCPs, any questions raised by HCPs, and general observations around the initial perception of the technology. Where possible, the researcher will take notes on how the HCP interact with the technology to understand its capabilities.