\"Healthcare systems engineering is challenging due to the complexity, geographic expansiveness, inertial properties, and the heterogeneous sub-systems, with varying vested interests. Additionally, humans comprise many of the forms and functions, and are independent, with resistance and uncertainty in their decision-making that adds complexity. Human-centered systems modeling approaches are therefore needed to capture this unique aspect of a healthcare system and to enhance understanding of emergent healthcare properties. This dissertation focuses on integrating systems modeling within healthcare and emphasizes the importance of incorporating human decision-making. Moreover, the incorporation of a human-centered approach yields particularly valuable insights into the decision-making processes that influence the implementation of new healthcare technology. The first step in this work was to use Monte Carlo simulation techniques for concept exploration. The second project was to capture patient and physician stakeholder needs through targeted surveys using the Theory of Planned Behavior. Finally, an early-generation system model based on an agent-based modeling approach was developed with the survey responses as input data. It also made use of publicly available regional health data to create a more generalizable approach. As a proof of concept for this approach, we applied it to the implementation of mobile radiation oncology in a rural setting\"-- Abstract, p. iii
","abstract_html":"<p>"Healthcare systems engineering is challenging due to the complexity, geographic expansiveness, inertial properties, and the heterogeneous sub-systems, with varying vested interests. Additionally, humans comprise many of the forms and functions, and are independent, with resistance and uncertainty in their decision-making that adds complexity. Human-centered systems modeling approaches are therefore needed to capture this unique aspect of a healthcare system and to enhance understanding of emergent healthcare properties. This dissertation focuses on integrating systems modeling within healthcare and emphasizes the importance of incorporating human decision-making. Moreover, the incorporation of a human-centered approach yields particularly valuable insights into the decision-making processes that influence the implementation of new healthcare technology. The first step in this work was to use Monte Carlo simulation techniques for concept exploration. The second project was to capture patient and physician stakeholder needs through targeted surveys using the Theory of Planned Behavior. Finally, an early-generation system model based on an agent-based modeling approach was developed with the survey responses as input data. It also made use of publicly available regional health data to create a more generalizable approach. As a proof of concept for this approach, we applied it to the implementation of mobile radiation oncology in a rural setting"-- Abstract, p. iii</p>","abstract_has_math":false,"creators":["Price, Alex"],"institution":"Missouri University of Science and Technology","degree_name":"Ph. D. in Systems Engineering","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T03:18:26Z","subjects":["Agent-based model","human-centered","Engineering","Systems Science"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsmine.mst.edu/doctoral_dissertations/3302","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Price, Alex"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:type","label":"Dc Type","values":["Dissertation - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. D. in Systems Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Missouri University of Science and Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Agent-based model","human-centered","Engineering","Systems Science"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsmine.mst.edu/doctoral_dissertations/3302"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["\"Healthcare systems engineering is challenging due to the complexity, geographic expansiveness, inertial properties, and the heterogeneous sub-systems, with varying vested interests. Additionally, humans comprise many of the forms and functions, and are independent, with resistance and uncertainty in their decision-making that adds complexity. Human-centered systems modeling approaches are therefore needed to capture this unique aspect of a healthcare system and to enhance understanding of emergent healthcare properties. This dissertation focuses on integrating systems modeling within healthcare and emphasizes the importance of incorporating human decision-making. Moreover, the incorporation of a human-centered approach yields particularly valuable insights into the decision-making processes that influence the implementation of new healthcare technology. The first step in this work was to use Monte Carlo simulation techniques for concept exploration. The second project was to capture patient and physician stakeholder needs through targeted surveys using the Theory of Planned Behavior. Finally, an early-generation system model based on an agent-based modeling approach was developed with the survey responses as input data. It also made use of publicly available regional health data to create a more generalizable approach. As a proof of concept for this approach, we applied it to the implementation of mobile radiation oncology in a rural setting\"-- Abstract, p. iii
"]},{"key":"dc:title","label":"Title","values":["A Human-Centered Framework for Oncological Healthcare System Modeling Applied to Mobile Radiation Delivery"]}]}],"canonical_facts":{"dc:creator":["Price, Alex"],"dc:description.abstract":["\"Healthcare systems engineering is challenging due to the complexity, geographic expansiveness, inertial properties, and the heterogeneous sub-systems, with varying vested interests. Additionally, humans comprise many of the forms and functions, and are independent, with resistance and uncertainty in their decision-making that adds complexity. Human-centered systems modeling approaches are therefore needed to capture this unique aspect of a healthcare system and to enhance understanding of emergent healthcare properties. This dissertation focuses on integrating systems modeling within healthcare and emphasizes the importance of incorporating human decision-making. Moreover, the incorporation of a human-centered approach yields particularly valuable insights into the decision-making processes that influence the implementation of new healthcare technology. The first step in this work was to use Monte Carlo simulation techniques for concept exploration. The second project was to capture patient and physician stakeholder needs through targeted surveys using the Theory of Planned Behavior. Finally, an early-generation system model based on an agent-based modeling approach was developed with the survey responses as input data. It also made use of publicly available regional health data to create a more generalizable approach. As a proof of concept for this approach, we applied it to the implementation of mobile radiation oncology in a rural setting\"-- Abstract, p. iii
"],"dc:identifier":["https://scholarsmine.mst.edu/doctoral_dissertations/3302"],"dc:subject":["Agent-based model","human-centered","Engineering","Systems Science"],"dc:title":["A Human-Centered Framework for Oncological Healthcare System Modeling Applied to Mobile Radiation Delivery"],"dc:type":["Dissertation - Open Access"],"thesis:degree_name":["Ph. D. in Systems Engineering"],"thesis:institution_name":["Missouri University of Science and Technology"]},"updated_at":"2026-07-24T03:18:26Z"}