TB Research

Directly Observed Therapy to Measure Adherence to Tuberculosis Medication in Observational Research: Protocol for a Prospective Cohort Study

Elizabeth J. Ragan, Christopher Gill, Matthew Banos, Tara C. Bouton, Jennifer Rooney, C. Robert Horsburgh, Robin M. Warren, Bronwyn Myers, et al. (9 authors)

JMIR Research Protocols · 2021-02

Abstract

BACKGROUND: A major challenge for prospective, clinical tuberculosis (TB) research is accurately defining a metric for measuring medication adherence. OBJECTIVE: We aimed to design a method to capture directly observed therapy (DOT) via mobile health carried out by community workers. The program was created specifically to measure TB medication adherence for a prospective TB cohort in Western Cape Province, South Africa. METHODS: Community workers collect daily adherence data on mobile smartphones. Participant-level adherence, program-level adherence, and program function are systematically monitored to assess DOT program implementation. A data dashboard allows for regular visualization of indicators. Numerous design elements aim to prevent or limit data falsification and ensure study data integrity. RESULTS: The cohort study is ongoing and data collection is in progress. Enrollment began on May 16, 2017, and as of January 12, 2021, a total of 236 participants were enrolled. Adherence data will be used to analyze the study's primary aims and to investigate adherence as a primary outcome. CONCLUSIONS: The DOT program includes a mobile health application for data collection as well as a monitoring framework and dashboard. This approach has potential to be adapted for other settings to improve the capture of medication adherence in clinical TB research. TRIAL REGISTRATION: Clinicaltrials.gov NCT02840877; https://clinicaltrials.gov/ct2/show/NCT02840877.

MeSH terms

  • Medicine
  • Dashboard
  • Data collection
  • Tuberculosis
  • Observational study
  • Metric (unit)
  • Cohort study
  • Cohort
  • Protocol (science)
  • Prospective cohort study
  • Family medicine