Date of Graduation
Bachelor of Science in Industrial Engineering
Tuberculosis is an infectious disease, and different treatments have been discovered over the years. However, patients may develop various drug resistance levels that affect the likelihood of becoming cured or dying. In this study, we sought to employ data visualization to explore the relationship between treatment trajectory, as indicated by smear and culture results in the follow-up tests and patient outcomes. A large sample of patients have been broken down by demographics including age, gender, and drug resistance status. Sankey diagrams were used to visualize the pathway progression of the patients over time split between two time periods- months 0-6 and months 6-24. It was determined that the most crucial months of treatment for all drug resistant types were during months 0-2, since there was high variability within that time frame for all demographics. It was also observed that younger patients were much more varying test results. It is thus recommended that the standards be updated to test every month for the first nine months of treatment in order to better track the pathway variety and that younger patients be more closely monitored throughout the treatment process. Future studies may investigate the possibility of creating a prediction diagram for patient pathway progression based on demographic status and past medical information.
tuberculosis, Moldova, data modeling, data visualization, patient progression
Jenkins, J. (2019). Data Visualization of Treatment Outcomes for Tuberculosis Patients. Industrial Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/ineguht/64