Identification of Suspected Tuberculosis Using A Pharmamed Chatbot Based on Health Services in The City of Padang

Abstract

Introduction: TB disease is the first of the 10 leading causes of death in the world, and Indonesia is the 3rd highest country after India and China. The Minister of Health said there were 824,000 people suspected of having TB and asked all health officials to prioritize surveillance efforts to find people with TB detected by name by address. The TB cure rate in West Sumatra Province in 2020 is 76.9% and has not reached the national target of 85% and the city of Padang is only 23%. Objective: The purpose of this study is to find suspected cases of TB using the Pharmamed Chatbot, by name and by address so that they are easy to find to overcome TB. Methods: This type of research is quantitative descriptive of suspected TB cases using a 20-question chatbot to obtain social data by name and by address and suspected cases of TB. Results: The results of 838 respondents obtained 91 people suspected of TB, the composition of respondents BPJS 78.5% and 22.5%, not BPJS. BPJS respondents of productive age 15-24 years 26.91% and age range 45-64 years 34.4%. Chatbots are relatively successful and innovative as digital health in obtaining patients with suspected TB and the initial steps for TB control. It is necessary to develop a more complete chatbot and further research on TB disease prevention in Indonesia