Determinants of treatment success for tuberculosis cases in Sumatra, Indonesia

Background: Mycobacterium tuberculosis, the bacteria that causes tuberculosis (TB), attacks 80% of the lungs and 20% of the extrathoracic area. Tuberculosis is currently a worldwide health problem, and no country is free from this disease. This disease continues to show increasing morbidity and mortality rates, so it needs attention from various parties to support the success of its treatment. Purpose: To determine the success of tuberculosis treatment in Sumatra, Indonesia. Method: Quantitative research with a cross-sectional study design to determine the success of Pulmonary Tuberculosis (TB) treatment. The data used are secondary data sourced from the Tuberculosis Information System of the South Sumatra Provincial Health Office in January-December 2023. The sampling technique used total sampling, namely 3.127 respondents. The independent variables in this study include; age, education, employment status, previous health conditions, diabetes status, and HIV status, while the dependent variable is the efficacy of pulmonary TB treatment. Results: The average age of respondents suffering from pulmonary TB was 45.18 years, male, and not civil servants. New treatment history, standard treatment status, no history of DM, and most of them were HIV negative. There was a significant relationship between previous treatment history (p = 0.011), history of DM (p = 0.009), and HIV status (p = 0.0001) with the success of pulmonary TB treatment. However, the variables of age, gender, occupation and treatment status did not have a significant relationship (p > 0.05). Conclusion: There is a significant relationship between previous treatment history, history of DM and HIV status with the success of pulmonary TB treatment. However, the variables of age, gender, occupation and treatment status do not have a significant relationship. Suggestion: Health services should periodically evaluate and improve TB treatment program strategies to identify existing problems. Routine data analysis needs to be carried out both descriptively and analytically so that the available data is not just a collection of meaningless data.