A Novel Mobile App and Population Management System to Manage Rheumatoid Arthritis Flares: Protocol for a Randomized Controlled Trial

Penny Wang, Dee Luo, Fengxin Lu, Josephine S Elias, Adam B Landman, Kaleb D Michaud, Yvonne C Lee, Penny Wang, Dee Luo, Fengxin Lu, Josephine S Elias, Adam B Landman, Kaleb D Michaud, Yvonne C Lee

Abstract

Background: Rheumatoid arthritis flares have a profound effect on patients, causing pain and disability. However, flares often occur between regularly scheduled health care provider visits and are, therefore, difficult to monitor and manage. We sought to develop a mobile phone app combined with a population management system to help track RA flares between visits.

Objective: The objective of this study is to implement the mobile app plus the population management system to monitor rheumatoid arthritis disease activity between scheduled health care provider visits over a period of 6 months.

Methods: This is a randomized controlled trial that lasts for 6 months for each participant. We aim to recruit 190 patients, randomized 50:50 to the intervention group versus the control group. The intervention group will be assigned the mobile app and be prompted to answer daily questionnaires sent to their mobile devices. Both groups will be assigned a population manager, who will communicate with the participants via telephone at 6 weeks and 18 weeks. The population manager will also communicate with the participants in the intervention group if their responses indicate a sustained increase in rheumatoid arthritis disease activity. To assess patient satisfaction, the primary outcomes will be scores on the Treatment Satisfaction Questionnaire for Medication as well as the Perceived Efficacy in Patient-Physician Interactions questionnaire at 6 months. To determine the effect of the mobile app on rheumatoid arthritis disease activity, the primary outcome will be the Clinical Disease Activity Index at 6 months.

Results: The trial started in November 2016, and an estimated 2.5 years will be necessary to complete the study. Study results are expected to be published by the end of 2019.

Conclusions: The completion of this study will provide important data regarding the following: (1) the assessment of validated outcome measures to assess rheumatoid arthritis disease activity with a mobile app between routinely scheduled health care provider visits, (2) patient engagement in monitoring their condition, and (3) communication between patients and health care providers through the population management system.

Trial registration: ClinicalTrials.gov NCT02822521, https://ichgcp.net/clinical-trials-registry/NCT02822521 (Archived by WebCite at http://www.webcitation.org/6xed3kGPd).

Keywords: arthritis, rheumatoid; mobile applications; symptom flare up; telemedicine.

Conflict of interest statement

Conflicts of Interest: This project was funded by an Independent Grant for Learning and Change from Pfizer, Inc. YLC has stock in Express Scripts. ABL is a Senior Advisor for Ranked Health, a nonprofit organization that evaluates digital health apps.

©Penny Wang, Dee Luo, Fengxin Lu, Josephine S Elias, Adam B Landman, Kaleb D Michaud, Yvonne C Lee. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 11.04.2018.

Figures

Figure 1
Figure 1
Study schematic showing the roles of research assistants at study visits versus the roles of population managers who communicate with subjects between study visits. Research assistants are blinded to the randomization, whereas population managers are not blinded. Pt = patient.
Figure 2
Figure 2
Screenshots of interface of RA Flare Mobile App.
Figure 3
Figure 3
Web-based dashboard interface used by population managers to monitor participants’ responses to the app.
Figure 4
Figure 4
The flare algorithm compares Rheumatoid Arthritis Disease Activity Index-5 (RADAI-5) responses over a period of 2 weeks compared with the previous 2 weeks’ average. If the participant’s RADAI-5 score increases by more than 30% from the previous 2 weeks’ reading, the dashboard will generate an alert to the population manager.

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