My multidisciplinary healthcare background gives me a strong understanding of clinical services, health program, health-service management and the information needs of healthcare organizations. I have complemented this experience with practical data analytics training, including data cleaning, descriptive statistics, data visualization, hypothesis testing, regression analysis and machine-learning approaches such as logistic regression, decision trees and random forests.
I am particularly interested in using data to improve healthcare performance and decision-making. My recent analytics work has included analyzing emergency department data, comparing patient outcomes, developing admission-prediction models and evaluating models using ROC-AUC. I have also worked on health information systems concepts involving data quality, data harmonization, medical terminologies and record linkage.
My Monitoring & Evaluation background has strengthened my ability to work with indicators, program performance data, reporting requirements and evidence-based decision-making. Combined with my health-services management training, this enables me to understand not only how to analyze data, but also how analytical findings can be translated into practical actions for healthcare programmes and organizations.