U M - sporedata/researchdesigneR GitHub Wiki

• The University of Michigan (U-M) offers a wide array of health datasets through various research centers and initiatives, including the Precision Health Analytics Platform and the Institute for Health Policy and Innovation (IHPI). These datasets encompass electronic health records (EHRs), extensive administrative claims databases, and genetic data. The Precision Health initiative, for instance, provides access to health data for over 5 million Michigan Medicine patients and genetic data for over 80,000 participants in the Michigan Genomics Initiative.

• IHPI maintains a repository of high-value datasets that include HCUP databases, Medicaid, Medicare, and commercial claims data, available for use by its members.

• U-M research teams have conducted legal, qualitative, and quantitative analyses to understand the gaps and opportunities in data sharing. These analyses revealed that current laws do not fully protect the myriad ways data can be generated, shared, and used, particularly from an industry perspective. Despite these regulatory limitations, most people want to be notified if their biospecimens might be commercialized, making participant trust and institutional responsibility critical.

• The insights from these studies informed the creation of U-M's data-sharing policy, which emphasizes transparent, responsible, and ethical data stewardship. U-M developed an opt-in consent system for patients agreeing to share their data within its biobank, which has been extended to the broader patient population accessing health care services through Michigan Medicine.

The University of Michigan provides structured templates and data models to facilitate the integration and analysis of their health datasets. These templates support standardized data formats, making it easier for researchers to conduct comprehensive studies and comparisons across different data sources.

• Facility & Resource profile templates

• When utilizing the University of Michigan (U-M) health datasets for research, it's crucial to adhere to the university's stringent data security guidelines.
• Researchers must ensure that human subject data is maintained with appropriate levels of anonymity, confidentiality, or de-identification.
• Researchers are required to outline their data management and security procedures in their IRB applications, adhering to core data security controls as outlined by U-M's policies.
• Identifiable data should be limited to essential personnel, and sensitive information should be encrypted, especially when stored on portable devices.
• Maintaining data integrity is essential, especially when dealing with longitudinal studies or time-series analysis. Although U-M datasets may not explicitly skew dates, researchers should be cautious of any modifications or de-identifications applied to the data, consulting available documentation to ensure accurate interpretation.

University of Michigan datasets are used in a variety of research projects, including:

• Public Health: Monitoring and addressing public health issues, such as diabetes and asthma, through collaborative quality initiatives.
• Genomic Studies: Research on genetic predispositions to certain diseases using data from the Michigan Genomics Initiative.
• Clinical Research: Studies on disease prevalence, treatment outcomes, and patient demographics.
• Healthcare Policy: Analysis of healthcare delivery and policy impacts using insurance claims and clinical data.

The datasets include a wide range of variables such as:

• Genetic Data: Genotype and phenotype information from genomic studies.
• Clinical Data: Diagnoses, treatment plans, and outcomes.
• Healthcare Utilization: Data on healthcare services usage and costs.
• Demographic Information: Age, gender, ethnicity, and socioeconomic status.

• Data Integration: Combining datasets from different sources can be challenging due to varying data formats and standards.
• Privacy Concerns: Ensuring patient confidentiality while using detailed health data is a constant challenge.
• Data Completeness: Not all datasets are complete or up-to-date, which may affect research findings.
• Access Restrictions: Certain datasets may require specific permissions and agreements to access.

• U-M's policies
• The University of Michigan
• MIDAS - University of Michigan
• Sharing Health Data: The Why, the Will, and the Way Forward
• Center for Healthcare Outcomes & Policy - University of Michigan
• Radiopharmaceuticals for nuclear endocrinology at the University of Michigan
• CT-based definition of thoracic lymph node stations: an atlas from the University of Michigan
• The University of Michigan Dioxin Exposure Study: population survey results and serum concentrations for polychlorinated dioxins, furans, and biphenyls

Researchers affiliated with the University of Michigan or partnering institutions can access these datasets by adhering to institutional data use agreements and protocols. For specific data access, refer to the respective data access platforms and contact information.

Researchers at the University of Michigan must register with the appropriate data access platforms, complete required training, and follow data use protocols to gain access to health datasets. Specific access procedures and requirements are available through the University of Michigan's data access websites.

• Precision Health - University of Michigan

[1] Grossmann C, Chua PS, Ahmed M, Greene SM. Sharing Health Data: The Why, the Will, and the Way Forward. 2023.

[2] Grossmann C, Chua PS, Ahmed M, Greene SM. CASE STUDY: The University of Michigan - Sharing Health Data. National Academies Press (US). 2022.