The Center for Complexity and Self-Management of Chronic Disease (CSCD) will address the growing problem of chronic disease. One of the critical cores in accomplishing that objective is the Administrative Core (ACORE). The ACORE will provide the oversight and infrastructure for the CSCD Center. The Executive Committee, the group that will facilitate the operationalization of the Center's scientific vision and resource allocation will be embedded in the ACORE. The ACORE will be responsible for the overall evaluation of the Center and financial stewardship and health. It will be the link to interdisciplinary colleagues and the External Advisory Committee.
The aims specific to the ACORE are 1) To leverage complexity to advance the science of self-management for the promotion of health in chronic illness by a) providing consultation and mentorship to interdisciplinary teams around innovative methods for analyzing the effects of complex interventions; b)providing interdisciplinary forums, seminars, workshops and brainstorming sessions;c) establishing a resource bank (with Methods/Analytics Core) with tools (measurement, technology, and /or intervention manuals) that can be used in studies or further developed for other populations;and 2) to develop plans to sustain the CSCD and the interdisciplinary teams who are in its membership by a) facilitating new and continued Center membership through the development of an integrated communication strategy that includes relevant disciplines throughout the University and neighboring health system, b) using real time data quarterly to inform the need for upgrades in processes and c) evaluating outcomes on a biannual basis to facilitate any required changes to improve sustainability. In short, the ACORE will be the working engine for the Center that will enable both the Pilot and Methods/Analytics Cores to be successful in completing their aims.

Agency
National Institute of Health (NIH)
Institute
National Institute of Nursing Research (NINR)
Type
Exploratory Grants (P20)
Project #
1P20NR015331-01
Application #
8821269
Study Section
Special Emphasis Panel (ZNR1-REV-M (17))
Project Start
Project End
Budget Start
2014-09-26
Budget End
2015-07-31
Support Year
1
Fiscal Year
2014
Total Cost
$174,645
Indirect Cost
$62,303
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Tang, Ming; Gao, Chao; Goutman, Stephen A et al. (2018) Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering. Neuroinformatics :
Costa, Deena Kelly; Moss, Marc (2018) The Cost of Caring: Emotion, Burnout, and Psychological Distress in Critical Care Clinicians. Ann Am Thorac Soc 15:787-790
Kalinin, Alexandr A; Higgins, Gerald A; Reamaroon, Narathip et al. (2018) Deep learning in pharmacogenomics: from gene regulation to patient stratification. Pharmacogenomics 19:629-650
Marino, Simeone; Xu, Jiachen; Zhao, Yi et al. (2018) Controlled feature selection and compressive big data analytics: Applications to biomedical and health studies. PLoS One 13:e0202674
Casida, Jesus M; Aikens, James E; Craddock, Heidi et al. (2018) Development and Feasibility of Self-Management Application in Left-Ventricular Assist Devices. ASAIO J 64:159-167
Dinov, Ivo D; Palanimalai, Selvam; Khare, Ashwini et al. (2018) Randomization-Based Statistical Inference: A Resampling and Simulation Infrastructure. Teach Stat 40:64-73
Kalinin, Alexandr A; Allyn-Feuer, Ari; Ade, Alex et al. (2018) 3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification. Sci Rep 8:13658
Sepehrband, Farshid; Lynch, Kirsten M; Cabeen, Ryan P et al. (2018) Neuroanatomical morphometric characterization of sex differences in youth using statistical learning. Neuroimage 172:217-227
Stelmokas, Julija; Yassay, Lance; Giordani, Bruno et al. (2017) Translational MRI Volumetry with NeuroQuant: Effects of Version and Normative Data on Relationships with Memory Performance in Healthy Older Adults and Patients with Mild Cognitive Impairment. J Alzheimers Dis 60:1499-1510
Huang, Zhengnan; Zhang, Hongjiu; Boss, Jonathan et al. (2017) Complete hazard ranking to analyze right-censored data: An ALS survival study. PLoS Comput Biol 13:e1005887

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