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Chat-Based Decision Support System for the Maternal Health Journey in Assam, India: Protocol for a Mixed Methods
Ashita Munjral1, Swapnil Rawat2, Charlotte E Warren3
1Maternal Health, Population Council Consultancy, New Delhi, Delhi, India.
JMIR Research Protocols
|February 13, 2026
Summary
The e-SAATHI chatbot improves maternal health (MH) by providing personalized support, increasing antenatal care (ANC) and postnatal care (PNC) service uptake in Assam, India. This digital tool enhances health-seeking behaviors and outcomes in underserved regions.
Area of Science:
- Digital Health Interventions
- Maternal Health
- Public Health
Background:
- Assam, India, faces the nation's highest maternal mortality ratio, primarily due to limited access and quality of maternal health (MH) care.
- Inadequate antenatal (ANC) and postnatal (PNC) services are exacerbated by socioeconomic barriers and weak healthcare infrastructure.
- Digital tools, such as mobile messaging and chatbots, have demonstrated success in improving maternal care in similar settings.
Purpose of the Study:
- To assess the acceptability, feasibility, and effectiveness of the e-SAATHI chatbot in enhancing MH information access and service uptake.
- To increase ANC/PNC utilization, promote respectful care, and gather insights for scaling digital health solutions.
- To improve maternal and newborn care quality scores and service uptake indicators.
Main Methods:
- A phased approach involving co-design, pilot testing, and large-scale enrollment of pregnant and postpartum women.
- Chatbot deployment delivering weekly personalized, stage-specific MH information from early pregnancy to postpartum.
- Training of healthcare providers for onboarding and feedback, alongside data collection through interviews, surveys, facility assessments, and chatbot analytics.
Main Results:
- As of August 2025, 210 facilities onboarded and 201,813 women enrolled, with ongoing data collection.
- The study will compare pre- and post-intervention quantitative data on service uptake and qualitative data on user experiences.
- Primary outcome: change in composite quality score of maternal and newborn care; secondary outcomes: service uptake, knowledge, self-care, and satisfaction.
Conclusions:
- The e-SAATHI chatbot presents a scalable digital strategy to enhance maternal health in diverse sociodemographic and linguistic settings.
- Personalized, timely support via chatbot can improve health-seeking behaviors and outcomes in Assam and globally.
- The project provides valuable insights for optimizing digital health strategies in low-resource regions.
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