Data Analysis

The Health Analytics Consortium (HAC) is an open incubator for collaboration and digital scholarship that emphasizes team-based transdisciplinary data science and advanced health analytics. A core mission of HAC is to foster integration of innovative research, development, education and training, and outreach in data and health sciences.

 The University of Michigan Health System provides leadership and support of “Collaborative Quality Initiatives” (CQIs) which seek to address some of the most common, complex, and costly areas of surgical and medical care. CQI Coordinating Centers, led by UMHS faculty, work collaboratively with health care providers throughout Michigan to collect data to a centralized registry; analyze and share data to identify processes that lead to improved delivery of care and outcomes, and guide quality improvement interventions. 

 This is an open-access archive of a diverse collection of datasets that can be used for demonstrations, algorithm development, instrument testing, exploratory analytics and hands-on experiential practice of data-driven inference. The data are classified by type. Meta-data is provided to frame the information into the scope of specific driving motivational challenges. Observed and simulated data are included in the SOCR Data archive. The data can be redistributed (CC-BY).

 ABL consults and collaborates with investigative teams in nursing, contributing their expertise to the designing of experiments, statistical analysis planning (including sample size justification), statistical analysis in support of grants, and preparing/submitting grant proposals.

The Center for Complexity and Self-management of Chronic Disease (CSCD) advances the science of self-management (SM) by addressing complexity, including the study of complex multi-component interventions and SM for people with complex comorbid conditions. In addition, the Center provides the infrastructure to facilitate interdisciplinary approaches and expand the pool of investigative teams who are equipped to successfully develop and implement externally funded programs of research in self-management.

 The Statistics Online Computational Resource (SOCR) designs, validates and freely disseminates knowledge, scientific discoveries and learning materials. Specifically, SOCR provides portable online aids for probability, statistics, methods and analytics education, technology based instruction, and statistical computing.

 Synthetic Patient Data Sets (HAPI FHIR server in AWS)

UMHS Data Set Catalog is a listing of data sets available to various constituents within the University, along with associated metadata that describes what each data set contains, how it can be accessed, who its stakeholders are, and what its history has been.
An online, searchable directory of data assets (e.g. Disease Registries, Financial Data, Biospecimen Collections, Government Health Data, Quality Data), institutional or departmental, that have the potential for data reuse by the broader UMHS constituency.

 (Longitudinal Online Research and Imaging System) is a web-based data and project management software for neuroimaging research studies. It is an OPEN SOURCE framework for storing and processing behavioural, clinical, neuroimaging and genetic data. LORIS also makes it easy to manage large datasets acquired over time in a longitudinal study, or at different locations in a large multi-site study.

XNAT is an open source imaging informatics platform, developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data.  Learn more here