Theses and Dissertations

Date of Award

5-2023

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematics

First Advisor

Dr. Kristina Vatcheva

Second Advisor

Dr. Santanu Chakraborty

Third Advisor

Dr. Mrinal Kanti Roychowdhury

Abstract

Antibiotics are widely used to treat bacterial infections, but their misuse leads to antibiotic resistance. Antibiotic resistance is one of the biggest threats to global health, food security, and development today. Antibiotic resistance leads to higher medical costs, prolonged hospital stays, and increased mortality. Antimicrobial stewardship is an approach to measure and improve the appropriate use of antibiotics in healthcare settings. Data science has the potential to support these programs by providing insights into antibiotic prescribing patterns, identifying areas for improvement, and predicting patient outcomes. We explored the role of data science in hospital antibiotic stewardship programs, including statistical methods and data visualization techniques. We conducted statistical analysis to identify trends and seasonality in antibiotic usage using autoregressive integrated moving average (ARIMA) models and generalized additive models (GAMs). We developed a pilot interactive dashboard for hospital inpatient antibiotic stewardship using Python. The dashboard visualizes trends in the antibiotic stewardship metric days of therapy (DOT) by various categories, such as indication, therapeutic class, and period. The use of digital dashboards in healthcare is becoming increasingly popular, and our work demonstrates the potential of data visualization tools in hospital antibiotic stewardship.

Comments

Copyright 2023 Saikou Jawla. All Rights Reserved.

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