TB Research

FACTORS ASSOCIATED WITH TUBERCULOSIS TREATMENT SUCCESS IN BANTUL, INDONESIA: SECONDARY DATA ANALYSIS OF TUBERCULOSIS INFORMATION SYSTEM 2020–2022

SI Iskandar, Samsu Aryanto, Bantul District Health Office, Special Region of Yogyakarta, Indonesia, BS Wiratama

Abstract

Indonesia has the world's second-highest number of tuberculosis (TB) patients.Patients with TB frequently experience boredom and a lack of medication adherence, resulting in lower treatment rates.This study was conducted to identify factors associated with successful TB treatment using a Tuberculosis Information System (SITB), the centralized system used to record and report TB cases.We conducted the cross-sectional study using secondary data from SITB for 2020-2022.Treatment success was the sum of cure and treatment completion.Loss to follow-up, death, and treatment failure were defined as unsuccessful treatment.Age, gender, contact investigation, type of TB diagnosis, anatomical site, treatment history, diabetes status, and HIV status were the independent variables.The dependent variable was the treatment outcome.Inclusion criteria include TB patients over the age of 15 with treatment results, whereas incomplete data was excluded.Total sampling was used.We applied multiple logistic regression to analyze the factors associated with treatment results.Only 421 of the 1377 data obtained were complete and analyzed.Most of them received standard therapy (92.53%), aged 15-64 years (95.03%),females (96.30%), and had contact investigation (97.45%).The significant factors for TB treatment success were age (aOR 5.61; 95% CI 2.42-12.99),gender (aOR 2.68; 95% CI 1.01-7.07),type of TB diagnosis (aOR 0.43; 95% CI 0.19-0.99),and contact investigation (aOR 3.37; 95% CI 1.09-10.39).TB patients of productive age, female, bacteriologically confirmed, and performing a contact investigation had a greater probability of successful therapy.Multisectoral collaboration is required for tuberculosis control; contact tracing should be encouraged to improve treatment outcomes for tuberculosis in index cases and other risk factors should be explored to establish a population-level intervention.

MeSH terms

  • Tuberculosis
  • Computer science
  • Environmental health
  • Medicine