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Tracking and debriefing birth data at scale: A mobile phone application to improve obstetric and neonatal care in Bihar, India.

  • Author(s): Spindler, Hilary;
  • Dyer, Jessica;
  • Bagchi, Kingshuk;
  • Ranjan, Vikash;
  • Christmas, Amelia;
  • Cohen, Susanna R;
  • Sterling, Mona;
  • Shah, Malay Bharat;
  • Das, Aritra;
  • Mahapatra, Tanmay;
  • Walker, Dilys
  • et al.

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This analysis assessed changes over time in skill and knowledge related to the use of evidence-based practices associated with quality of maternal and neonatal care during a nurse midwife mentoring intervention at primary health clinics (PHCs) in Bihar, India.


Nurse midwife mentors (NMMs) entered live birth observation data into a mobile App from 320 PHCs.


The NMMs completed prompted questions in the App after every live birth witnessed. The App consisted of questions around three main themes, "What went well?", "What needed improvement?" and "What can be done differently next time?".


Observational data from 5,799 births was recorded by 120 NMMs in 320 PHCs. Knowledge and skill during normal spontaneous vaginal deliveries and complicated deliveries with either a postpartum haemorrhage or non-vigorous infant all showed statistically significant improvement (< .001) over time using a Chi-squared test for trend with a mean increase of 41% across all indicators.

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