The Administrative Component of the """"""""Patient-centered Information Commons (""""""""PIC"""""""") will be responsible for managing the overall conduct of this project. The management plan, headed by an Executive Team that includes the co-PIs, Drs. Isaac Kohane and Shawn Murphy, and the Executive Director, Susanne Churchill, has proposed a model based on this group's ten year experience with the i2b2 U54 National Center for Biomedical Computing. This plan focuses on the development and sustenance of a truly interactive and collaborative working group that involves all of the interdisciplinary domains required by this big data science project. Regularly structured interactions, progress reporting and ongoing evaluation are proposed to insure that progress is monitored, challenges identified, and solutions devised to address bottlenecks. Leadership will rely on a number of advisory bodies, including the NIH Science Team, an internal Scientific Advisory Board with expertise in areas affecting but not directly proposed for our research (e.g., patient privacy), an External Advisory Committee to be configured after award, and very importantly, a Users'Group constituted from potential end users in the community. The Admin Team will be responsible for developing and maintaining a dissemination strategy for the open source tools and procedures emerging from our work. Significant effort will be devoted to assuring compliance with all financial, regulatory and reporting requirements. This team will be fully engaged in the DB2K Consortium activities, including participation in its advisory bodies, dedicated meetings and other activities still to be defined.
Sound management is essential to the successful outcome of a large project such as this and necessary to justify return on federal investment. This group is fully commited to this end, a commitment justified by our previous experience with a similarly scaled project which has been widely adopted at the international level.
|Yu, Zhi; Kim, Seoyoung C; Vanni, Kathleen et al. (2018) Association between inflammation and systolic blood pressure in RA compared to patients without RA. Arthritis Res Ther 20:107|
|Neykov, Matey; Hejblum, Boris P; Sinnott, Jennifer A (2018) Kernel machine score test for pathway analysis in the presence of semi-competing risks. Stat Methods Med Res 27:1099-1114|
|Agniel, Denis; Kohane, Isaac S; Weber, Griffin M (2018) Biases in electronic health record data due to processes within the healthcare system: retrospective observational study. BMJ 361:k1479|
|Can, Anil; Castro, Victor M; Dligach, Dmitriy et al. (2018) Lipid-Lowering Agents and High HDL (High-Density Lipoprotein) Are Inversely Associated With Intracranial Aneurysm Rupture. Stroke 49:1148-1154|
|Boag, Willie; Doss, Dustin; Naumann, Tristan et al. (2018) What's in a Note? Unpacking Predictive Value in Clinical Note Representations. AMIA Jt Summits Transl Sci Proc 2017:26-34|
|Xia, Yin; Cai, Tianxi; Cai, T Tony (2018) Multiple Testing of Submatrices of a Precision Matrix with Applications to Identification of Between Pathway Interactions. J Am Stat Assoc 113:328-339|
|Brown, Adam S; Patel, Chirag J (2018) A review of validation strategies for computational drug repositioning. Brief Bioinform 19:174-177|
|Xia, Yin; Cai, Tianxi; Cai, T Tony (2018) Two-Sample Tests for High-Dimensional Linear Regression with an Application to Detecting Interactions. Stat Sin 28:63-92|
|Kerpedjiev, Peter; Abdennur, Nezar; Lekschas, Fritz et al. (2018) HiGlass: web-based visual exploration and analysis of genome interaction maps. Genome Biol 19:125|
|Kothari, Cartik; Wack, Maxime; Hassen-Khodja, Claire et al. (2018) Phelan-McDermid syndrome data network: Integrating patient reported outcomes with clinical notes and curated genetic reports. Am J Med Genet B Neuropsychiatr Genet 177:613-624|
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