Diagnosing the Unknown for Care and Advancing Science (DUCAS)

诊断未知的护理和推进科学 (DUCAS)

• 批准号: 10682163
• 负责人: Euan A Ashley
• 金额: $ 470.51万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-19 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10682163
• 关键词: Address; Amalgam; Automation; Bioinformatics; Biomedical Research; Caring; Clinic; Clinical; Clinical Research; Consent; Data; Data Analyses; Data Coordinating Center; Diagnosis; Diagnostic; Diagnostics Research; Disease; Ecosystem; Ensure; Environment; Etiology; Evaluation; Family; Genomics; Goals; Healthcare; Healthcare Systems; Industry Standard; Infrastructure; Institution; Knowledge; Lead; Machine Learning; Medical; Nomenclature; Patient Participation; Patient advocacy; Patient-Focused Outcomes; Patients; Persons; Process; Productivity; Research; Research Personnel; Research Support; Scheme; Science; Services; Therapeutic; Translational Research; United States National Institutes of Health; advocacy organizations; clinical care; data management; data science management; data sharing; design; experience; follow-up; genome-wide; medical schools; multidisciplinary; novel diagnostics; outreach; patient population; patient screening; programs; rare condition; remediation; response; scale up; timeline

PROJECT SUMMARY In our current healthcare system, it often takes years before patients with rare conditions and rare presentations of common conditions receive a diagnosis. In 2013, the National Institutes of Health supported the creation of the Undiagnosed Diseases Network (UDN) to address the needs of these patients, to facilitate the diagnostic process for those with undiagnosed conditions and generate new knowledge about underlying mechanisms of disease. The UDN was successful in solving medical mysteries, shortening diagnostic odysseys, and contributing to biomedical research discovery. In order to serve more patients, the UDN process must be scaled and integrated into broader healthcare and research ecosystems. As the Data Management Coordinating Center (DMCC) for a network of Diagnostic Centers of Excellence, Harvard Medical School will leverage experience in the UDN to create sustainable, nationally scaled infrastructure to support diagnosis, research, and care for those who are undiagnosed. This will be accomplished by bringing together experts in trans-institutional data sharing, data analysis, clinical care, bioinformatics, novel diagnostics, and translational research and creating three DMCC Cores - Administrative, Data Management, and Clinical Research Support - to address unmet needs of the undiagnosed. The Administrative Core will unite the DMCC and support activities of all three Cores. Together, the DMCC Cores will accomplish four aims: 1) Scale up UDN throughput by at least an order of magnitude to meet a pressing national need, 2) Leverage partnerships for sustainable coordination of diagnostic processes to increase patient autonomy while advancing opportunities for investigative science, 3) Maximize data mobility, interpretability, and shareability, and 4) Provide analytic service and data stewardship through the Data Management Core and Clinical Research Support Cores led by experts in genomics and AI teaming with clinicians and researchers.

项目总结