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Using Text Messages for Critical Real-time Data Capture in the ANISA Study.

Mohammad Shahidul Islam1, Qazi Sadeq-ur Rahman, Tanvir Hossain

  • 1From the *Department of Microbiology, Child Health Research Foundation, Dhaka, Bangladesh; †Centre for Child and Adolescent Health, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh; and ‡CSL Software Resources Ltd., Dhaka, Bangladesh.

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Summary

This study demonstrates how text messaging technology can be effectively used for real-time data collection and monitoring in the Aetiology of Neonatal Infection in South Asia (ANISA) study, overcoming challenges in remote areas.

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Area of Science:

  • Public Health
  • Infectious Disease Epidemiology
  • Mobile Health (mHealth)

Background:

  • The Aetiology of Neonatal Infection in South Asia (ANISA) study utilizes text messaging for data recording and monitoring.
  • This approach is crucial for managing study activities in resource-limited settings.

Purpose of the Study:

  • To leverage text messaging technology for efficient randomization and monitoring within the ANISA study.
  • To address challenges of real-time data entry and monitoring in population-based studies conducted in remote areas.

Main Methods:

  • Child-health workers register newborns via text message, including study ID and age.
  • Physicians send text messages detailing infant age at illness assessment for serious bacterial infection (SBI) case identification.
  • A computer algorithm uses this data for newborn randomization into a control subcohort.
  • Text messages also facilitate alerts for referred SBI cases and specimen transport coordination.

Main Results:

  • The text messaging system enables real-time data entry for study randomization.
  • It allows for continuous monitoring of study activities and participant status.
  • The system effectively alerts healthcare providers and supervisors about critical patient referrals.

Conclusions:

  • Text messaging offers a viable solution for overcoming data entry and monitoring barriers in remote, population-based studies.
  • The ANISA study's system demonstrates the potential of mHealth for improving research infrastructure in underserved regions.