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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

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|February 13, 2026
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Summary
This summary is machine-generated.

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.

Keywords:
AssamIndiadigital solutionmaternal healthprotocol

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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.