ArticleThe European respiratory journal2018
Evaluating the potential costs and impact of digital health technologies for tuberculosis treatment support.
Article in The European respiratory journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
34 citing papers in PubMed, 5 syntheses or guidelines pooled it, 63 citations in OpenAlex.
- Comparative Effectiveness of Digital Health Technologies in Tuberculosis Treatment: Systematic Review and Network Meta-Analysis of Randomized Controlled Trials.JMIR mHealth and uHealth · 2025Pooled it
- Rethinking Tuberculosis Morbidity Quantification: A Systematic Review and Critical Appraisal of TB Disability Weights in Cost-Effectiveness Analyses.PharmacoEconomics · 2024Pooled it
- Cost and cost-effectiveness of digital technologies for support of tuberculosis treatment adherence: a systematic review.BMJ global health · 2024Pooled it
- Mapping the effectiveness of the community tuberculosis care programs: a systematic review.Systematic reviews · 2023Pooled it
- eHealth in TB clinical management.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022Pooled it
- Adverse events among persons with TB using in-person vs. electronic directly observed therapy.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2023Trial
- Nurses' Experiences of Video Direct Observed Treatment at a Local Tuberculosis Clinic in a High-Income Country: A Qualitative Study.Nursing open · 2026Article
- Preferences of Patients With Tuberculosis for AI-Assisted Remote Health Management: Discrete Choice Experiment.Journal of medical Internet research · 2025Article
- Article
- Success factors and measures for scaling patient-facing digital health technologies from leaders' insights.BMC health services research · 2025Article
- Effectiveness and Acceptability of Video-Observed Therapy for Tuberculosis Treatment Monitoring: A Scoping Review.Iranian journal of public health · 2025Review
- Effectiveness of Digital Health Interventions to Enhance Continuity of Care in Patients with Pulmonary Tuberculosis: A Systematic Review of Randomized Controlled Trials.Patient preference and adherence · 2025Review
- Costs of Digital Adherence Technologies for Tuberculosis Treatment Support, 2018-2021.Emerging infectious diseases · 2024Article
- Cost of digital technologies and family-observed DOT for a shorter MDR-TB regimen: a modelling study in Ethiopia, India and Uganda.BMC health services research · 2023Article
- Article
- Effect of mobile health reminders on tuberculosis treatment outcomes in Shanghai, China: A prospective cohort study.Frontiers in public health · 2023Article
- Digitizing tuberculosis treatment monitoring in Wuhan city, China, 2020-2021: Impact on medication adherence.Frontiers in public health · 2023Article
- The engagement of nursing and healthcare researchers with digital technologies: lessons learnt in an Australian university.Journal of research in nursing : JRN · 2022Article
- Clinical standards for drug-susceptible pulmonary TB.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022Article
- Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review.JMIR mHealth and uHealth · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
Abstract
Ensuring adherence and support during treatment of tuberculosis (TB) is a major public health challenge. Digital health technologies could help improve treatment outcomes. We considered their potential cost and impact on treatment for active or latent TB in Brazil.Decision analysis models simulated two adult cohorts with 1) drug-susceptible active TB, and 2) multidrug-resistant TB, and two cohorts treated with isoniazid for latent TB infection (LTBI): 1) close contacts of persons with active TB, and 2) others newly diagnosed with LTBI. We evaluated four digital support strategies: two different medication monitors, synchronous video-observed therapy (VOT), and two-way short message service (SMS). Comparators were standard directly observed treatment for active TB and self-administered treatment for LTBI. Projected outcomes included costs (2016 US dollars), plus active TB cases and disability-adjusted life years averted among persons with LTBI.For individuals with active TB, medication monitors and VOT are projected to lead to substantial (up to 58%) cost savings, in addition to alleviating inconvenience and cost to patients of supervised treatment visits. For LTBI treatment, SMS and medication monitors are projected to be the most cost-effective interventions. However, all projections are limited by the scarcity of published estimates of clinical effect for the digital technologies.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.