Increasing Impact of Mobile Health Programs: SAHELI for Maternal and Child Care


  • Shresth Verma Google Research India
  • Gargi Singh Google Research India
  • Aditya Mate Google Research India Harvard University
  • Paritosh Verma Google Research India Purdue University
  • Sruthi Gorantla Google Research India Indian Institute of Science, Bangalore
  • Neha Madhiwalla ARMMAN
  • Aparna Hegde ARMMAN
  • Divy Thakkar Google Research India
  • Manish Jain Google Research India
  • Milind Tambe Google Research India
  • Aparna Taneja Google Research India



Multiagent Systems, Restless Multi-Armed Bandits, Population Health, Social Impact


Underserved communities face critical health challenges due to lack of access to timely and reliable information. Nongovernmental organizations are leveraging the widespread use of cellphones to combat these healthcare challenges and spread preventative awareness. The health workers at these organizations reach out individually to beneficiaries; however such programs still suffer from declining engagement. We have deployed SAHELI, a system to efficiently utilize the limited availability of health workers for improving maternal and child health in India. SAHELI uses the Restless Multiarmed Bandit (RMAB) framework to identify beneficiaries for outreach. It is the first deployed application for RMABs in public health, and is already in continuous use by our partner NGO, ARMMAN. We have already reached ~100K beneficiaries with SAHELI, and are on track to serve 1 million beneficiaries by the end of 2023. This scale and impact has been achieved through multiple innovations in the RMAB model and its development, in preparation of real world data, and in deployment practices; and through careful consideration of responsible AI practices. Specifically, in this paper, we describe our approach to learn from past data to improve the performance of SAHELI’s RMAB model, the real-world challenges faced during deployment and adoption of SAHELI, and the end-to-end pipeline.




How to Cite

Verma, S., Singh, G., Mate, A., Verma, P., Gorantla, S., Madhiwalla, N., Hegde, A., Thakkar, D., Jain, M., Tambe, M., & Taneja, A. (2023). Increasing Impact of Mobile Health Programs: SAHELI for Maternal and Child Care. Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 15594-15602.



IAAI Technical Track on deployed Highly Innovative Applications of AI