Mobile Tuberculosis Treatment Support Tools to Increase Treatment Success in Patients with Tuberculosis in Argentina: Protocol for a Randomized Controlled Trial

Sarah Iribarren, Hannah Milligan, Kyle Goodwin, Omar Alfonso Aguilar Vidrio, Cristina Chirico, Hugo Telles, Daniela Morelli, Barry Lutz, Jennifer Sprecher, Fernando Rubinstein, Sarah Iribarren, Hannah Milligan, Kyle Goodwin, Omar Alfonso Aguilar Vidrio, Cristina Chirico, Hugo Telles, Daniela Morelli, Barry Lutz, Jennifer Sprecher, Fernando Rubinstein

Abstract

Background: Tuberculosis (TB) is an urgent global health threat and the world's deadliest infectious disease despite being largely curable. A critical challenge is to ensure that patients adhere to the full course of treatment to prevent the continued spread of the disease and development of drug-resistant disease. Mobile health interventions hold promise to provide the required adherence support to improve TB treatment outcomes.

Objective: This study aims to evaluate the effectiveness of the TB treatment support tools (TB-TSTs) intervention on treatment outcomes (success and default) and to assess patient and provider perceptions of the facilitators and barriers to TB-TSTs implementation.

Methods: The TB-TSTs study is an open-label, randomized controlled trial with 2 parallel groups in which 400 adult patients newly diagnosed with TB will be randomly assigned to receive usual care or usual care plus TB-TSTs. Participants will be recruited on a rolling basis from 4 clinical sites in Argentina. The intervention consists of a smartphone progressive web app, a treatment supporter (eg, TB nurse, physician, or social worker), and a direct adherence test strip engineered for home use. Intervention group participants will report treatment progress and interact with a treatment supporter using the app and metabolite urine test strip. The primary outcome will be treatment success. Secondary outcomes will include treatment default rates, self-reported adherence, technology use, and usability. We will assess patients' and providers' perceptions of barriers to implementation and synthesize lessons learned. We hypothesize that the TB-TSTs intervention will be more effective because it allows patients and TB supporters to monitor and address issues in real time and provide tailored support. We will share the results with stakeholders and policy makers.

Results: Enrollment began in November 2020, with a delayed start due to the COVID-19 pandemic, and complete enrollment is expected by approximately July 2022. Data collection and follow-up are expected to be completed 6 months after the last patient is enrolled. Results from the analyses based on the primary end points are expected to be submitted for publication within a year of data collection completion.

Conclusions: To our knowledge, this randomized controlled trial will be the first study to evaluate a patient-centered remote treatment support strategy using a mobile tool and a home-based direct drug metabolite test. The results will provide robust scientific evidence on the effectiveness, implementation, and adoption of mobile health tools. The findings have broader implications not only for TB adherence but also more generally for chronic disease management and will improve our understanding of how to support patients facing challenging treatment regimens.

Trial registration: ClinicalTrials.gov NCT04221789; https://ichgcp.net/clinical-trials-registry/NCT04221789.

International registered report identifier (irrid): DERR1-10.2196/28094.

Keywords: digital health; direct drug metabolite test; disease management; infectious disease; mHealth; mobile phone; tuberculosis.

Conflict of interest statement

Conflicts of Interest: Some of the authors are developers (SI, KG, and OAAV) and evaluators (SI, HM, CC, HT, and FR) of the software.

©Sarah Iribarren, Hannah Milligan, Kyle Goodwin, Omar Alfonso Aguilar Vidrio, Cristina Chirico, Hugo Telles, Daniela Morelli, Barry Lutz, Jennifer Sprecher, Fernando Rubinstein. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 21.06.2021.

Figures

Figure 1
Figure 1
Recruitment flow diagram. TB: tuberculosis.
Figure 2
Figure 2
Patient app features.
Figure 3
Figure 3
Intervention overview. TB: tuberculosis.

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