Data-Driven Decision-Making for Medications Management Modalities
To address this and many other challenges in regard to medications mismanagement, I take advantage of data-driven methodologies where a decision-making framework for identifying optimal medications management strategies will be established based on real-world data. This data-driven approach has the advantage of supporting decision-making processes by data analytics, and hence, the decision made can be validated by verifiable data. Thus, compared to merely theoretical methods, my methodology will be more applicable to patients as the ultimate beneficiaries of the healthcare system.
Based on this premise, in this dissertation I attempt to analyze and advance three streams of research that are influenced by issues involving the management of medications/treatments for different medical contexts. In particular, I will discuss (1) management of medications/treatment modalities for new-onset of diabetes after solid organ transplantations and (2) epidemic of opioid prescription and abuse.
- Author (aut): Boloori, Alireza
- Thesis advisor (ths): Saghafian, Soroush
- Thesis advisor (ths): Fowler, John
- Committee member: Gel, Esma
- Committee member: Cook, Curtiss B
- Committee member: Montgomery, Douglas C.
- Publisher (pbl): Arizona State University