{"id":{"repo_id":"umkc","oai_identifier":"oai:mospace.umsystem.edu:10355/112360"},"canonical_url":"https://search.dev.ndltd.org/etd/umkc/oai:mospace.umsystem.edu:10355/112360","repository":{"repo_id":"umkc","name":"University of Missouri - Kansas City","base_url":"https://mospace.umsystem.edu/oai/request"},"display":{"title":"Social determinants of health in patients with congenital rare disease","abstract":"Rare and orphan diseases represent a substantial public health challenge, yet population-level evidence describing how social determinants of health, institutional context, and patient experience shape outcomes remains limited. Although rare diseases are often framed primarily through genetic and clinical complexity, patients also navigate fragmented care, delayed diagnosis, variable insurance coverage, geographic barriers, and inconsistent access to specialty services. This research examined these issues using a multi-method framework that combined large-scale real-world inpatient data with an exploratory patient-reported outcomes pilot.The primary analyses used Oracle Real-World Data® to identify adult inpatient encounters. In fully adjusted mortality models, rare encounter status were independently associated with increased inpatient death; 59% higher odds of mortality compared with non-rare encounters. A readmission analysis extended these findings to post-discharge vulnerability. In the fully adjusted model, rare encounter status was associated with approximately 25% higher odds of 30-day readmission. In the patient-reported outcomes (PROs) pilot demonstrated the feasibility and importance of integrating patient experience into rare disease research. Although the pilot was limited by survey attrition and insufficient repeated encounter reporting, it revealed barriers not observable in administrative data. These findings demonstrate that integrating real-world data with PROs framework for understanding rare disease disparities and supports future work aimed at earlier diagnosis, improved care coordination, and more equitable access to rare disease care.","abstract_html":"Rare and orphan diseases represent a substantial public health challenge, yet population-level evidence describing how social determinants of health, institutional context, and patient experience shape outcomes remains limited. Although rare diseases are often framed primarily through genetic and clinical complexity, patients also navigate fragmented care, delayed diagnosis, variable insurance coverage, geographic barriers, and inconsistent access to specialty services. This research examined these issues using a multi-method framework that combined large-scale real-world inpatient data with an exploratory patient-reported outcomes pilot.The primary analyses used Oracle Real-World Data® to identify adult inpatient encounters. In fully adjusted mortality models, rare encounter status were independently associated with increased inpatient death; 59% higher odds of mortality compared with non-rare encounters. A readmission analysis extended these findings to post-discharge vulnerability. In the fully adjusted model, rare encounter status was associated with approximately 25% higher odds of 30-day readmission. In the patient-reported outcomes (PROs) pilot demonstrated the feasibility and importance of integrating patient experience into rare disease research. Although the pilot was limited by survey attrition and insufficient repeated encounter reporting, it revealed barriers not observable in administrative data. These findings demonstrate that integrating real-world data with PROs framework for understanding rare disease disparities and supports future work aimed at earlier diagnosis, improved care coordination, and more equitable access to rare disease care.","abstract_has_math":false,"creators":["Staley, Joshua Michael"],"institution":"University of Missouri--Kansas City","degree_name":"Ph.D. (Doctor of Philosophy)","degree_level":"Doctoral","degree_discipline":"Pharmaceutical Sciences (UMKC)","degree_department":null,"school":null,"contributors":[],"advisors":["Allsworth, Jenifer E.","Wyckoff, Gerald J."],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026","date_published":"2026","updated_at":"2026-07-24T05:17:10Z","subjects":[],"languages":["en_US"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10355/112360","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Allsworth, Jenifer E.","Wyckoff, Gerald J."]},{"key":"dc:creator","label":"Author","values":["Staley, Joshua Michael"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-06-23T19:09:20Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-06-23T19:09:20Z"]},{"key":"dc:date.issued","label":"Date","values":["2026"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Pharmaceutical Sciences (UMKC)","Biomedical and Health Informatics (UMKC)"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D. (Doctor of Philosophy)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Missouri--Kansas City"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10355/112360"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Vita","Title from PDF of title page viewed July 10, 2026","Dissertation advisors: Jenifer E. Allsworth and Gerald J. Wyckoff","Includes bibliographical references (pages 190-200)","Dissertation (Ph.D.)--School of Medicine, Division of Pharmaceutical Sciences. University of Missouri--Kansas City, 2026"]},{"key":"dc:description.abstract","label":"Abstract","values":["Rare and orphan diseases represent a substantial public health challenge, yet population-level evidence describing how social determinants of health, institutional context, and patient experience shape outcomes remains limited. Although rare diseases are often framed primarily through genetic and clinical complexity, patients also navigate fragmented care, delayed diagnosis, variable insurance coverage, geographic barriers, and inconsistent access to specialty services. This research examined these issues using a multi-method framework that combined large-scale real-world inpatient data with an exploratory patient-reported outcomes pilot.The primary analyses used Oracle Real-World Data® to identify adult inpatient encounters. In fully adjusted mortality models, rare encounter status were independently associated with increased inpatient death; 59% higher odds of mortality compared with non-rare encounters. A readmission analysis extended these findings to post-discharge vulnerability. In the fully adjusted model, rare encounter status was associated with approximately 25% higher odds of 30-day readmission. In the patient-reported outcomes (PROs) pilot demonstrated the feasibility and importance of integrating patient experience into rare disease research. Although the pilot was limited by survey attrition and insufficient repeated encounter reporting, it revealed barriers not observable in administrative data. These findings demonstrate that integrating real-world data with PROs framework for understanding rare disease disparities and supports future work aimed at earlier diagnosis, improved care coordination, and more equitable access to rare disease care."]},{"key":"dc:title","label":"Title","values":["Social determinants of health in patients with congenital rare disease"]}]}],"canonical_facts":{"dc:contributor.advisor":["Allsworth, Jenifer E.","Wyckoff, Gerald J."],"dc:creator":["Staley, Joshua Michael"],"dc:date.accessioned":["2026-06-23T19:09:20Z"],"dc:date.available":["2026-06-23T19:09:20Z"],"dc:date.issued":["2026"],"dc:description":["Vita","Title from PDF of title page viewed July 10, 2026","Dissertation advisors: Jenifer E. Allsworth and Gerald J. Wyckoff","Includes bibliographical references (pages 190-200)","Dissertation (Ph.D.)--School of Medicine, Division of Pharmaceutical Sciences. University of Missouri--Kansas City, 2026"],"dc:description.abstract":["Rare and orphan diseases represent a substantial public health challenge, yet population-level evidence describing how social determinants of health, institutional context, and patient experience shape outcomes remains limited. Although rare diseases are often framed primarily through genetic and clinical complexity, patients also navigate fragmented care, delayed diagnosis, variable insurance coverage, geographic barriers, and inconsistent access to specialty services. This research examined these issues using a multi-method framework that combined large-scale real-world inpatient data with an exploratory patient-reported outcomes pilot.The primary analyses used Oracle Real-World Data® to identify adult inpatient encounters. In fully adjusted mortality models, rare encounter status were independently associated with increased inpatient death; 59% higher odds of mortality compared with non-rare encounters. A readmission analysis extended these findings to post-discharge vulnerability. In the fully adjusted model, rare encounter status was associated with approximately 25% higher odds of 30-day readmission. In the patient-reported outcomes (PROs) pilot demonstrated the feasibility and importance of integrating patient experience into rare disease research. Although the pilot was limited by survey attrition and insufficient repeated encounter reporting, it revealed barriers not observable in administrative data. These findings demonstrate that integrating real-world data with PROs framework for understanding rare disease disparities and supports future work aimed at earlier diagnosis, improved care coordination, and more equitable access to rare disease care."],"dc:identifier.uri":["https://hdl.handle.net/10355/112360"],"dc:language.iso":["en_US"],"dc:title":["Social determinants of health in patients with congenital rare disease"],"dc:type":["Thesis"],"thesis:degree_discipline":["Pharmaceutical Sciences (UMKC)","Biomedical and Health Informatics (UMKC)"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Ph.D. (Doctor of Philosophy)"],"thesis:institution_name":["University of Missouri--Kansas City"]},"updated_at":"2026-07-24T05:17:10Z"}