ArticleBMC primary care2026
Telemedicine implementation and healthcare utilization in Rwanda: interrupted time series of babyl digital health services from 2015 to 2024.
Article in BMC primary care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- From Integrated Care to Learning Systems.Healthcare (Basel, Switzerland) · 2026Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
backgroundDigital health platforms are transforming primary care delivery in low- and middle-income countries. Babyl provided Rwanda’s first nationwide telemedicine service from 2019 to September 2023, integrating nurse-led triage with physician oversight, e-prescriptions, and national health insurance. Despite processing 3.9 million consultations, evidence on population-level impacts of scaled telemedicine services like Babyl in sub-Saharan Africa remains limited. This study aimed to quantify the association between national-scale telemedicine implementation and facility-based healthcare utilization for common primary care conditions in Rwanda, using interrupted time series analysis to estimate immediate and sustained effects across introduction and discontinuation periods.
methodsWe integrated deidentified administrative data from Babyl (n = 3,899,788 consultations), Rwanda’s Health Management Information System (2015–2024). We employed two analytical approaches: (1) descriptive analysis of user demographics, insurance coverage, and clinical characteristics; (2) segmented regression with interrupted time series modeling using ordinary least squares with Newey-West heteroskedasticity- and autocorrelation-consistent standard errors to quantify level and slope changes across pre-intervention, intervention, and post-discontinuation periods for gastritis, diarrhea, urinary tract infections, malaria, and respiratory infections.
resultsThe platform recorded 3.90 million consultations (2019–2023), with 75.4% covered by community-based health insurance and 54.7% among female patients. Task-shifting was substantial: triage nurses managed 44.2% of consultations, senior nurses 25.6%, and general practitioners 30.2%. Interrupted time series analysis revealed immediate reductions in facility-based cases following Babyl’s introduction: respiratory infections decreased by 1055 cases (95% CI -1098 to -1011; P < .001), malaria by 246 cases (95% CI -258 to -234; P < .001), gastritis by 137 cases (95% CI -146 to -127; P < .001), and urinary tract infections by 114 cases (95% CI -124 to -105; P < .001). Post-discontinuation, monthly increases ranged from 1 case (gastritis, diarrhea, urinary tract infections) to 10 cases (respiratory infections), suggesting demand reversal to facilities.
conclusionsNational-scale telemedicine implementation was associated with substantial reductions in facility-based consultations for common conditions and successful task-shifting to nurses. The post-discontinuation reversal patterns underscore telemedicine’s role in healthcare access. Future digital health initiatives should prioritize sustainable financing, system interoperability, and regulatory frameworks to maintain service continuity.
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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 Socratic graph.