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Background <p>Digital 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&#xa0;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.</p> Methods <p>We integrated deidentified administrative data from Babyl (<i>n</i> = 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.</p> Results <p>The platform recorded 3.90&#xa0;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; <i>P</i> &lt; .001), malaria by 246 cases (95% CI -258 to -234; <i>P</i> &lt; .001), gastritis by 137 cases (95% CI -146 to -127; <i>P</i> &lt; .001), and urinary tract infections by 114 cases (95% CI -124 to -105; <i>P</i> &lt; .001). Post-discontinuation, monthly increases ranged from 1 case (gastritis, diarrhea, urinary tract infections) to 10 cases (respiratory infections), suggesting demand reversal to facilities.</p> Conclusions <p>National-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.</p>

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Telemedicine implementation and healthcare utilization in Rwanda: interrupted time series of babyl digital health services from 2015 to 2024

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月20日

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  • Felix K. Rubuga,
  • Gashaija Absolomon,
  • Thierry Claudien Uhawenimana,
  • Yvonne Delphine Nsaba-Uwera,
  • Jean Muhire,
  • Jean Damascene Hagenimana,
  • Emmanuel Christian Nyabyenda,
  • Piero Irakiza,
  • Muhammed Semakula,
  • Eric Remera,
  • James Humuza,
  • Jeanine Condo

摘要

Background

Digital 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.

Methods

We 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.

Results

The 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.

Conclusions

National-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.