Analyzing and Predicting Low-Listenership Trends in a Large-Scale Mobile
  Health Program: A Preliminary Investigation
Arshika Lalan Shresth Verma Kumar Madhu Sudan Amrita Mahale Aparna Hegde Milind Tambe Aparna Taneja
Mobile health programs are becoming an increasingly popular medium for
dissemination of health information among beneficiaries in less privileged
communities. Kilkari is one of the world's largest mobile health programs which
delivers time sensitive audio-messages to pregnant women and new mothers. We
have been collaborating with ARMMAN, a non-profit in India which operates the
Kilkari program, to identify bottlenecks to improve the efficiency of the
program. In particular, we provide an initial analysis of the trajectories of
beneficiaries' interaction with the mHealth program and examine elements of the
program that can be potentially enhanced to boost its success. We cluster the
cohort into different buckets based on listenership so as to analyze
listenership patterns for each group that could help boost program success. We
also demonstrate preliminary results on using historical data in a time-series
prediction to identify beneficiary dropouts and enable NGOs in devising timely
interventions to strengthen beneficiary retention.