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JMIR Res Protoc. 2020 Feb 10;9(2):e16657. doi: 10.2196/16657.

Measuring the Effects of Sharing Mobile Health Data During Diabetes Consultations: Protocol for a Mixed Method Study.

Author information

1
Norwegian Center for E-health Research, University Hospital of North Norway, Tromsø, Norway.
2
Department of Clinical Medicine, University of Tromsø-The Arctic University of Norway, Tromsø, Norway.
3
Department of Computer Science, University of Tromsø-The Arctic University of Norway, Tromsø, Norway.
4
Department of Internal Medicine, University Hospital of North Norway, Tromsø, Norway.
5
Department of Community Medicine, University of Tromsø-The Arctic University of Norway, Tromsø, Norway.
6
Centre for Quality Improvement and Development, University Hospital of North Norway, Tromsø, Norway.
7
Faculty of Health and Sport Science, University of Agder, Grimstad, Norway.
#
Contributed equally

Abstract

BACKGROUND:

There is rising demand for health care's limited resources. Mobile health (mHealth) could be a solution, especially for those with chronic illnesses such as diabetes. mHealth can increases patients' options to self-manage their health, improving their health knowledge, engagement, and capacity to contribute to their own care decisions. However, there are few solutions for sharing and presenting patients' mHealth data with health care providers (HCPs) in a mutually understandable way, which limits the potential of shared decision making.

OBJECTIVE:

Through a six-month mixed method feasibility study in Norway, we aim to explore the impacts that a system for sharing patient-gathered data from mHealth devices has on patients and HCPs during diabetes consultations.

METHODS:

Patients with diabetes will be recruited through their HCPs. Participants will use the Diabetes Diary mobile phone app to register and review diabetes self-management data and share these data during diabetes consultations using the FullFlow data-sharing system. The primary outcome is the feasibility of the system, which includes HCP impressions and expectations (prestudy survey), usability (System Usability Scale), functionalities used and data shared during consultations, and study-end focus group meetings. Secondary outcomes include a change in the therapeutic relationship, patient empowerment and wellness, health parameters (HbA1c and blood pressure), and the patients' own app-registered health measures (blood glucose, medication, physical activity, diet, and weight). We will compare measures taken at baseline and at six months, as well as data continuously gathered from the app. Analysis will aim to explain which measures have changed and how and why they have changed during the intervention.

RESULTS:

The Full Flow project is funded for 2016 to 2020 by the Research Council of Norway (number 247974/O70). We approached 14 general practitioner clinics (expecting to recruit 1-2 general practitioners per clinic) and two hospitals (expecting to recruit 2-3 nurses per hospital). By recruiting through the HCPs, we expect to recruit 74 patients with type 2 and 33 patients with type 1 diabetes. Between November 2018 and July 2019, we recruited eight patients and 15 HCPs. During 2020, we aim to analyze and publish the results of the collected data from our patient and HCP participants.

CONCLUSIONS:

We expect to better understand what is needed to be able to share data. This includes potential benefits that sharing patient-gathered data during consultations will have on patients and HCPs, both individually and together. By measuring these impacts, we will be able to present the possibilities and challenges related to a system for sharing mHealth data for future interventions and practice. Results will also demonstrate what needs to be done to make this collaboration between HCPs and patients successful and subsequently further improve patients' health and engagement in their care.

KEYWORDS:

data sharing; diabetes; mHealth; patient-gathered data; therapeutic relationship

PMID:
32039818
DOI:
10.2196/16657
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