JMIR Publications

ABSTRACT

Background:

Introducing self-collected health data from patients with diabetes into consultation can be beneficial for both patients and clinicians. Patients can be more proactive in their disease management and clinicians can provide more tailored medical services. Optimally, electronic health record systens (EHRs) should be able to receive self-collected health data in a medical data standard representation such as Fast Healthcare Interoperability Resources (FHIR) from patients systems such as mHealth apps and to display it directly to their users, the clinicians. However, while Norwegian EHRs are working on implementing FHIR, no solution or graphical interface is available today to display self-collected health data.

Objective:

The objective of this study was to design and assess a dashboard for displaying relevant self-collected health data from patients with diabetes to clinicians.

Methods:

The design relied on an iterative participatory process containing workshops involving patients, clinicians and researchers to define which information should be available and how it should be displayed. The assessment is based on a case study presenting an in-stance of the dashboard populated with the data collected from one patient with diabetes type 1 (in-house researcher) face to face with fourteen clinicians. We performed a qualitative analysis based on usability, functionality and expectation using responses to questionnaires that were distributed to the fourteen clinicians at the end of the workshops and collected before the participants left. The qualitative assessment was guided by the Standards for Reporting Qualitative Research (SRQR).

Results:

We created a dashboard permitting clinicians to 1) assess the reliability of self-collected health data, 2) list all collected data including medical calculations and 3) point out medical situations to investigate for improving the situation of the patients. The dashboard uses a combination of tables, graphs and other visual representations to display the relevant information. The assessment showed that the clinicians think that this type of solution will be useful during consultations every day, especially for patients living in remote areas or the ones being technologically interested.

Conclusions:

Displaying self-collected health data during consultations is not enough for clinicians, the data reliability has to be assured and the relevant information needs to be extracted and displayed along with the data to ease the introduction during a medical encounter. The pre-study assessment showed that 1) the system provides relevant information to meet clinicians’ need and 2) that clinicians were eager to start using it during consultations. The system is currently being tested in a medical trial since November 2018 and the first results concerning its assessment in a real-life situation are expected in the beginning of next year (2020).