Date of Award
Doctor of Philosophy (PhD)
Stanfield, Paul M.
The primary goal of this research is to determine the strategic system integration opportunities for a segmented healthcare system with cost minimization and efficacy maximization objectives. This research is inspired in part by the Defense Logistics Agency, which is trying to assess the impact of integrating treatment selection processes across service clinicians. Specifically, physician bias, patient volumes, leveraging economies of scale or costing structures, and complex treatment efficacy calculations are considered by mathematically modeling three forms of integration. Multiple objective optimization problems are used to define efficient frontiers based on cost and treatment efficacy. A novel comparative analysis method is applied to measure improvements in efficient frontiers and a customized genetic algorithm solution is applied for the more complex treatment selection problem. Results indicate that more integrated treatment selection protocols lead to decreases in cost alongside increases in efficacy. Complex healthcare systems or systems with higher variability in performance factors are found to have the greatest opportunity for performance improvement. The three studies in this research apply systems engineering concepts to flexibly characterize and parameterize systems; inform policy including characteristics of attractive treatments; and capture system dynamics and insights. However, this research is not intended to dictate treatments to health professionals; set policy or give practitioners optimal allocations; fully capture all of the intricacies of the treatment design process; or constrain research processes associated with treatment design.
Simpson, LaKausha Tanette, "Designing Medical Treatment Protocols To Improve Healthcare Supply Chain Management" (2014). Dissertations. 73.